Python 2.1 Bible

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Unformatted text preview: 4807-7 cover 5/16/01 12:25 PM Page 1 100% 100% If Python 2.1 can do it, you can do it too . . . Packed with crystal-clear explanations, hands-on examples, and a complete language reference, this authoritative guide gives you all the tools you need for rapid application development with Python 2.1. From variables, expressions, and other basics to XML, multimedia, and multithreading, Python pros Dave Brueck and Stephen Tanner show you step by step how to master Python components, put them together, and create full-featured applications — in practically no time! Use the device contexts to draw graphics • Get up to speed on basics with a quick one-hour tutorial • Work with Python data types, expressions, and objectoriented features • Take advantage of Python operating system services and database features See the chat/whiteboard application in action • Create Web-savvy applications that can handle Internet data and parse XML • Build graphical applications using Tkinter and wxPython • Process sound and image files • Harness multithreading, encryption, tokenizing, and other advanced techniques Use scales and listboxes to design a color scheme • Use Python tools to create number-crunching routines and internationalized applications • Distribute Python applications and modules on a Windows or UNIX system BRUECK TANNER www.hungryminds.com $39.99 USA$59.99 Canada £29.99 UK Reader Level: Shelving Category: Beginning to Advanced Programming ISBN 0-7645-4807-7 *85 5 -AHCEJh Python 2.1 Python 2.1 Inside, you’ll find complete coverage of Python 2.1 COMPREHENSIVE ,!7IA7G4-feiahj!:p;N;t;T;t Bible Includes a complete language reference ONE HUNDRED PERCENT COMPREHENSIVE AUTHORITATIVE WHAT YOU NEED ONE HUNDRED PERCENT Master all major Python components and see how they work together Leverage Python standard libraries for rapid application development Harness XML, Unicode, and other cutting-edge technologies Python 2.1 INCLUDES A COMPLETE PYTHON LANGUAGE REFERENCE Dave Brueck and Stephen Tanner 4807-7 FM.F 5/24/01 8:57 AM Page i Python 2.1 Bible 4807-7 FM.F 5/24/01 8:57 AM Page ii 4807-7 FM.F 5/24/01 8:57 AM Page iii Python 2.1 Bible Dave Brueck and Stephen Tanner Hungry Minds, Inc. New York, NY ✦ Cleveland, OH ✦ Indianapolis, IN ✦ 4807-7 FM.F 5/24/01 8:57 AM Page iv Python 2.1 Bible Published by Hungry Minds, Inc. 909 Third Avenue New York, NY 10022 www.hungryminds.com Copyright © 2001 Hungry Minds, Inc. All rights reserved. No part of this book, including interior design, cover design, and icons, may be reproduced or transmitted in any form, by any means (electronic, photocopying, recording, or otherwise) without the prior written permission of the publisher. Library of Congress Catalog Card No.: 2001090703 ISBN: 0-7645-4807-7 Printed in the United States of America 10 9 8 7 6 5 4 3 2 1 1B/RS/QW/QR/IN Distributed in the United States by Hungry Minds, Inc. Distributed by CDG Books Canada Inc. for Canada; by Transworld Publishers Limited in the United Kingdom; by IDG Norge Books for Norway; by IDG Sweden Books for Sweden; by IDG Books Australia Publishing Corporation Pty. 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For general information on Hungry Minds’ products and services please contact our Customer Care Department within the U.S. at 800-762-2974, outside the U.S. at 317-572-3993 or fax 317-572-4002. For sales inquiries and reseller information, including discounts, premium and bulk quantity sales, and foreign-language translations, please contact our Customer Care Department at 800-434-3422, fax 317-572-4002 or write to Hungry Minds, Inc., Attn: Customer Care Department, 10475 Crosspoint Boulevard, Indianapolis, IN 46256. For information on licensing foreign or domestic rights, please contact our Sub-Rights Customer Care Department at 212-884-5000. For information on using Hungry Minds’ products and services in the classroom or for ordering examination copies, please contact our Educational Sales Department at 800-434-2086 or fax 317-572-4005. For press review copies, author interviews, or other publicity information, please contact our Public Relations Department at 317-572-3168 or fax 317-572-4168. For authorization to photocopy items for corporate, personal, or educational use, please contact Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, or fax 978-750-4470. LIMIT OF LIABILITY/DISCLAIMER OF WARRANTY: THE PUBLISHER AND AUTHOR HAVE USED THEIR BEST EFFORTS IN PREPARING THIS BOOK. THE PUBLISHER AND AUTHOR MAKE NO REPRESENTATIONS OR WARRANTIES WITH RESPECT TO THE ACCURACY OR COMPLETENESS OF THE CONTENTS OF THIS BOOK AND SPECIFICALLY DISCLAIM ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. THERE ARE NO WARRANTIES WHICH EXTEND BEYOND THE DESCRIPTIONS CONTAINED IN THIS PARAGRAPH. NO WARRANTY MAY BE CREATED OR EXTENDED BY SALES REPRESENTATIVES OR WRITTEN SALES MATERIALS. THE ACCURACY AND COMPLETENESS OF THE INFORMATION PROVIDED HEREIN AND THE OPINIONS STATED HEREIN ARE NOT GUARANTEED OR WARRANTED TO PRODUCE ANY PARTICULAR RESULTS, AND THE ADVICE AND STRATEGIES CONTAINED HEREIN MAY NOT BE SUITABLE FOR EVERY INDIVIDUAL. NEITHER THE PUBLISHER NOR AUTHOR SHALL BE LIABLE FOR ANY LOSS OF PROFIT OR ANY OTHER COMMERCIAL DAMAGES, INCLUDING BUT NOT LIMITED TO SPECIAL, INCIDENTAL, CONSEQUENTIAL, OR OTHER DAMAGES. Trademarks: All trademarks are the property of their respective owners. Hungry Minds, Inc., is not associated with any product or vendor mentioned in this book. is a trademark of Hungry Minds, Inc. 4807-7 FM.F 5/24/01 8:57 AM Page v 4807-7 FM.F 5/24/01 8:57 AM Page vi Credits Acquisitions Editor Debra Williams Cauley Project Coordinator Regina Snyder Project Editor Barbra Guerra Graphics and Production Specialists Brian Torwelle Technical Editor Joseph Traub Quality Control Technicians Laura Albert, Carl Pierce, Nancy Price, Charles Spencer Copy Editors Lisa Blake Luann Rouff Book Designer Drew R. Moore Editorial Manager Colleen Totz Proofreading and Indexing TECHBOOKS Production Services About the Authors Dave Brueck is a professional software developer who loves to use Python whenever possible. His current projects include developing networked games, developing Python interfaces to his stockbroker’s C SDK, and plotting to overturn various world governments. Previously Dave was a contributing author to 3D Studio Max R3 Bible by Kelly Murdock, published by Hungry Minds (formerly IDG Books Worldwide). Stephen Tanner is currently using Python to build a black-box software testing framework. His side projects include Python tools to perform probabilistic derivativestrading analysis, and to download mass quantities of .mp3s. Aside from their “real” jobs, Dave and Stephen enjoy convincing people to pay them big bucks for consulting jobs. 4807-7 FM.F 5/24/01 8:57 AM Page vii To Jennie, Rachael, and Jacob — thanks for being patient. To Pokey the Penguin — NOW who is going to the restaurant? To the weeds in my unfinished back yard — playtime is over. — Dave For great justice! — Stephen 4807-7 FM.F 5/24/01 8:57 AM Page viii 4807-7 FM.F 5/24/01 8:57 AM Page ix Preface P ython is an object-oriented, interpreted programming language useful for a wide range of tasks, from small scripts to entire applications. It is freely available in binary or source code form and can be used royalty-free on all major platforms including Windows, Macintosh, Linux, FreeBSD, and Solaris. Compared with most programming languages, Python is very easy to learn and is considered by many to be the language of choice for beginning programmers. Instead of outgrowing the language, however, experienced developers enjoy lower maintenance costs without missing out on any features found in other major languages such as C++, Java, or Perl. Python is well known for its usefulness as a rapid application development tool, and we often hear of Python projects that finish in hours or days instead of the weeks or months that would have been required with traditional programming languages. It boasts a rich, full-featured set of standard libraries as well as the ability to interface with libraries in other languages like C++. Despite being incredibly powerful and enabling very rapid application development, the real reason we love to use Python is that it’s just plain fun. Python is like a lever — with it, you can do some pretty heavy lifting with very little effort. It frees you from lots of annoying, mundane work, and before long you begin to wonder how you endured your pre-Python days. About This Book Although Python is a great first programming language, in this book we do assume that you already have some programming experience. The first section of the book introduces you to Python and tells you everything you need to know to get started. If you’re new to Python, then that section is definitely the place to start; otherwise, it serves as a useful language reference with many examples. We’ve worked hard to ensure that the book works well as a quick reference. Often the quickest way to understand a feature is to see it in use: Flip through the book’s pages and you’ll see that they are dripping with code examples. 4807-7 FM.F x 5/24/01 8:57 AM Page x Python 2.1 Bible All the examples in the book work and are things you can try on your own. Where possible, the chapters also build complete applications that have useful and interesting purposes. We’ve gone to great lengths to explain not only how to use each module or feature but also why such a feature is useful. What You Need Besides the book, all you need is a properly installed copy of Python. Appendix A lists some Python resources available online, but a good place to start is www.python.org; it has prebuilt versions of Python for all major platforms as well as the Python source code itself. Once you’ve downloaded Python you’ll be underway in a matter of minutes. If you’re a user of Microsoft Windows, you can download an excellent distribution of Python from www.activestate.com. ActiveState provides a single download that includes Python, a free development environment and debugger, and Win32 extensions. PythonWare (www.pythonware.com) also offers a distribution of Python that comes bundled with popular third-party Python modules. PythonWare’s version peacefully coexists with older versions of Python, and the small distribution size makes for a quick download. No matter which site you choose, Python is free, so go download it and get started. How the Book Is Organized We’ve tried to organize the book so that related topics are close together. If you find the topic of one chapter particularly interesting, chances are that the chapters before and after it will pique your interest too. Part I: The Python Language The first chapter in this section is a crash course in Python programming. If you have many programming languages under your belt or just want to whet your appetite, try out the examples in that chapter to get a feel for Python’s syntax and powerful features. The remaining chapters in this first section cover the same material as Chapter 1 but in much greater detail. They work equally well as an initial tutorial of the Python language and as a language reference for seasoned Pythonistas. 4807-7 FM.F 5/24/01 8:57 AM Page xi Preface Part II: Files, Data Storage, and Operating System Services This part covers Python’s powerful string and regular expression handling features and shows you how to access files and directories. In this section we also cover how Python enables you to easily write objects to disk or send them across network connections, and how to access relational databases from your programs. Part III: Networking and the Internet Python is an ideal tool for XML processing, CGI scripting, and many other networking tasks. This part guides you through Internet programming with Python, whether you need to send e-mail, run a Web site, or just amass the world’s largest .mp3 collection. Part IV: User Interfaces and Multimedia This part covers Tkinter and wxPython, two excellent tools for building a GUI in Python. In this part, we also cover Python’s text interface tools, including support for Curses. This section also delves into Python’s support for graphics and sound. Part V: Advanced Python Programming This part answers the questions that come up in larger projects: How do I create multithreaded Python applications? How can I optimize my code, or glue it to C libraries? How can I make my program behave correctly in other countries? We also cover Python’s support for number crunching and security. Part VI: Deploying Python Applications This part covers what you need to know to deploy your Python programs quickly and painlessly. Python’s distribution utilities are great for bundling and distributing applications on many platforms. Part VII: Platform-Specific Support Sometimes it’s nice to take advantage of an operating system’s strengths. This part addresses some Windows-specific topics (like accessing the registry), and some UNIX-specific topics (like file descriptors). xi 4807-7 FM.F xii 5/24/01 8:57 AM Page xii Python 2.1 Bible Appendixes Appendix A is a guide to online Python resources. Appendix B introduces you to IDLE and PythonWin — two great IDEs for developing Python programs. It also explains how to make Emacs handle Python code. Conventions Used in This Book Source code, function definitions, and interactive sessions appear in monospaced font. Comments appear in bold monospaced font preceded by a hash mark for easy reading. For example, this quick interpreter session checks the version of the Python interpreter. The >>> at the start of a line is the Python interpreter prompt and the text after the prompt is what you would type: >>> import sys # This is a comment. >>> print sys.version 2.0 (#8, Oct 16 2000, 17:27:58) [MSC 32 bit (Intel)] References to variables in function definitions appear in italics. For example, the function random.choice(seq) chooses a random element from the sequence seq and returns it. We divided up the writing of this book’s chapters between ourselves. So, throughout the book’s body, we use “I” (not “we”) to relate our individual opinions and experiences. What the Icons Mean Throughout the book, we’ve used icons in the left margin to call your attention to points that are particularly important. New Feature This icon indicates that the material discussed is new to Python 2.0 or Python 2.1. Note The Note icons tell you that something is important — perhaps a concept that may help you master the task at hand or something fundamental for understanding subsequent material. Tip Tip icons indicate a more efficient way of doing something or a technique that may not be obvious. 4807-7 FM.F 5/24/01 8:57 AM Page xiii Preface Caution CrossReference Caution icons mean that the operation we’re describing can cause problems if you’re not careful. We use the Cross-Reference icon to refer you to other sections or chapters that have more to say on a subject. Visit Us! We’ve set up a Web site for the book at www.pythonapocrypha.com. On the site you’ll find additional information, links to Python Web sites, and all the code samples from the book (so you can be lazy and not type them in). The Web site also has a section where you can give feedback on the book, and we post answers to common questions. Have fun and enjoy the book! xiii 4807-7 FM.F 5/24/01 8:57 AM Page xiv Acknowledgments A lthough this book represents many hours of work on our part, there are many others without whom we would have failed. First and foremost is Guido van Rossum, Python’s creator and Benevolent Dictator for Life. We’re glad he created such a cool language and that many others have joined him along the way. Many thanks go to the good people at Hungry Minds: Debra Williams Cauley, our acquisitions editor, for making it all possible; Barb Guerra, our project editor, for keeping everything on track; Joseph Traub, our technical editor, for clarifying exposition and squashing bugs; and Lisa Blake and Luann Rouff, our copy editors, who fixed more broken grammar and passive-voice constructions than a stick could be shaken at. 4807-7 FM.F 5/24/01 8:57 AM Page xv Contents at a Glance Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiv Part I: The Python Language . . . . . . . . . . . . . . . . . . . . . . . . . 1 Chapter 1: Python in an Hour . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Chapter 2: Identifiers, Variables, and Numeric Types . . . . . . . . . . . . . . . . 19 Chapter 3: Expressions and Strings . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Chapter 4: Advanced Data Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Chapter 5: Control Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Chapter 6: Program Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Chapter 7: Object-Oriented Python . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Chapter 8: Input and Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Part II: Files, Data Storage, and Operating System Services . . . . . 131 Chapter 9: Processing Strings and Regular Expressions Chapter 10: Working with Files and Directories . . . . . Chapter 11: Using Other Operating System Services . . Chapter 12: Storing Data and Objects . . . . . . . . . . . Chapter 13: Accessing Date and Time . . . . . . . . . . Chapter 14: Using Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 155 179 195 219 229 Part III: Networking and the Internet . . . . . . . . . . . . . . . . . . 245 Chapter 15: Networking . . . . . . . . . . . . . . . . . . . Chapter 16: Speaking Internet Protocols . . . . . . . . . Chapter 17: Handling Internet Data . . . . . . . . . . . . Chapter 18: Parsing XML and Other Markup Languages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 275 303 325 Part IV: User Interfaces and Multimedia . . . . . . . . . . . . . . . . 345 Chapter 19: Tinkering with Tkinter . . . . . . . . . . Chapter 20: Using Advanced Tkinter Widgets . . . . Chapter 21: Building User Interfaces with wxPython Chapter 22: Using Curses . . . . . . . . . . . . . . . . Chapter 23: Building Simple Command Interpreters Chapter 24: Playing Sound . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 371 391 415 433 453 4807-7 FM.F 5/24/01 8:57 AM Page xvi Part V: Advanced Python Programming . . . . . . . . . . . . . . . . . 465 Chapter 25: Processing Images . . . . . . . . . . . . Chapter 26: Multithreading . . . . . . . . . . . . . . . Chapter 27: Debugging, Profiling, and Optimization Chapter 28: Security and Encryption . . . . . . . . . Chapter 29: Writing Extension Modules . . . . . . . Chapter 30: Embedding the Python Interpreter . . . Chapter 31: Number Crunching . . . . . . . . . . . . Chapter 32: Using NumPy . . . . . . . . . . . . . . . Chapter 33: Parsing and Interpreting Python Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467 481 497 515 527 553 581 589 605 Part VI: Deploying Python Applications . . . . . . . . . . . . . . . . . 617 Chapter 34: Creating Worldwide Applications . . . . . . . . . . . . . . . . . . . . 619 Chapter 35: Customizing Import Behavior . . . . . . . . . . . . . . . . . . . . . . 629 Chapter 36: Distributing Modules and Applications . . . . . . . . . . . . . . . . 643 Part VII: Platform-Specific Support . . . . . . . . . . . . . . . . . . . . 659 Chapter 37: Windows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661 Chapter 38: UNIX-Compatible Modules . . . . . . . . . . . . . . . . . . . . . . . . 671 Appendix A: Online Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . 685 Appendix B: Python Development Environments . . . . . . . . . . . . . . . . 689 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 701 4807-7 FM.F 5/24/01 8:57 AM Page xvii Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiv Part I: The Python Language 1 Chapter 1: Python in an Hour . . . . . . . . . . . . . . . . . . . . . . . . 3 Jumping In: Starting the Python Interpreter . . . . . . . . . . . . . . . . . . . 3 Experimenting with Variables and Expressions . . . . . . . . . . . . . . . . . 4 Pocket calculator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Defining a Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Running a Python Program . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Looping and Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Integer division . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Looping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Branching with if-statements . . . . . . . . . . . . . . . . . . . . . . . . 8 Breaking and continuing . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Lists and Tuples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Tuples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Slicing and dicing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Dictionaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Reading and Writing Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Sample Program: Word Frequencies . . . . . . . . . . . . . . . . . . . . . . . 11 Loading and Using Modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Creating a Class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Some quick object jargon . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Object orientation, Python style . . . . . . . . . . . . . . . . . . . . . . 15 Keep off the grass — Accessing class members . . . . . . . . . . . . . 15 Example: the point class . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Recommended Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Chapter 2: Identifiers, Variables, and Numeric Types . . . . . . . . . . 19 Identifiers and Operators . . Reserved words . . . . Operators . . . . . . . . Numeric Types . . . . . . . . Integers . . . . . . . . . Long integers . . . . . . Floating point numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 20 20 21 21 21 22 4807-7 FM.F xviii 5/24/01 8:57 AM Page xviii Python 2.1 Bible Imaginary numbers . . . . . . Manipulating numeric types . Assigning Values to Variables . . . . Simple assignment statements Multiple assignment . . . . . . Augmented assignment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 23 26 26 27 27 Chapter 3: Expressions and Strings . . . . . . . . . . . . . . . . . . . . 29 Expressions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comparing numeric types . . . . . . . . . . . . . . . . . . . . . . . . . Compound expressions . . . . . . . . . . . . . . . . . . . . . . . . . . . Complex expressions . . . . . . . . . . . . . . . . . . . . . . . . . . . . Operator precedence . . . . . . . . . . . . . . . . . . . . . . . . . . . . Strings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . String literals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Manipulating strings . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comparing strings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Unicode string literals . . . . . . . . . . . . . . . . . . . . . . . . . . . . Converting Between Simple Types . . . . . . . . . . . . . . . . . . . . . . . . Converting to numerical types . . . . . . . . . . . . . . . . . . . . . . . Converting to strings . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 29 31 32 33 34 35 37 42 43 43 44 45 Chapter 4: Advanced Data Types . . . . . . . . . . . . . . . . . . . . . . 49 Grouping Data with Sequences . . . . . . . . . . . . . . Creating lists . . . . . . . . . . . . . . . . . . . . . Creating tuples . . . . . . . . . . . . . . . . . . . . Working with Sequences . . . . . . . . . . . . . . . . . Joining and repeating with arithmetic operators Comparing and membership testing . . . . . . . Accessing parts of sequences . . . . . . . . . . . Iterating with for...in . . . . . . . . . . . . . . . . . Using sequence utility functions . . . . . . . . . . Using Additional List Object Features . . . . . . . . . . Additional operations . . . . . . . . . . . . . . . . List object methods . . . . . . . . . . . . . . . . . Mapping Information with Dictionaries . . . . . . . . . Creating and adding to dictionaries . . . . . . . . Accessing and updating dictionary mappings . . Additional dictionary operations . . . . . . . . . Understanding References . . . . . . . . . . . . . . . . Object identity . . . . . . . . . . . . . . . . . . . . Counting references . . . . . . . . . . . . . . . . . Copying Complex Objects . . . . . . . . . . . . . . . . . Shallow copies . . . . . . . . . . . . . . . . . . . . Deep copies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 50 52 52 52 53 53 55 55 57 57 58 60 61 61 62 63 63 64 65 65 66 4807-7 FM.F 5/24/01 8:57 AM Page xix Contents Identifying Data Types . . . . . . . . . Working with Array Objects . . . . . . Creating arrays . . . . . . . . . . Converting between types . . . Array methods and operations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 68 68 69 71 Chapter 5: Control Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Making Decisions with If-Statements . . . . . . . Using For-Loops . . . . . . . . . . . . . . . . . . Anatomy of a for-loop . . . . . . . . . . . . Looping example: encoding strings . . . . Ranges and xranges . . . . . . . . . . . . . Breaking, continuing, and else-clauses . . Changing horses in midstream . . . . . . . Using While-Loops . . . . . . . . . . . . . . . . . Throwing and Catching Exceptions . . . . . . . Passing the buck: propagating exceptions Handling an exception . . . . . . . . . . . More on exceptions . . . . . . . . . . . . . Defining and raising exceptions . . . . . . Cleaning up with finally . . . . . . . . . . . Debugging with Assertions . . . . . . . . . . . . Assertions in Python . . . . . . . . . . . . Toggling assertions . . . . . . . . . . . . . Example: Game of Life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 74 74 75 76 77 78 79 79 80 80 81 82 82 83 83 84 84 Chapter 6: Program Organization . . . . . . . . . . . . . . . . . . . . . 87 Defining Functions . . . . . . . . . . . . . . . Pass by object reference . . . . . . . . All about parameters . . . . . . . . . . Arbitrary arguments . . . . . . . . . . Apply: passing arguments from a tuple A bit of functional programming . . . . Grouping Code with Modules . . . . . . . . . Laying out a module . . . . . . . . . . . Taking inventory of a module . . . . . Importing Modules . . . . . . . . . . . . . . . What else happens upon import? . . . Reimporting modules . . . . . . . . . . Exotic imports . . . . . . . . . . . . . . Locating Modules . . . . . . . . . . . . . . . Python path . . . . . . . . . . . . . . . Compiled files . . . . . . . . . . . . . . Understanding Scope Rules . . . . . . . . . Is it local or global? . . . . . . . . . . . Listing namespace contents . . . . . . Grouping Modules into Packages . . . . . . Compiling and Running Programmatically . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 88 88 89 90 90 91 91 92 92 93 93 94 94 94 95 95 95 96 96 97 xix 4807-7 FM.F xx 5/24/01 8:57 AM Page xx Python 2.1 Bible Chapter 7: Object-Oriented Python . . . . . . . . . . . . . . . . . . . . 99 Overview of Object-Oriented Python . . . . . . . . . . . . . . . . . . . . . . 99 Creating Classes and Instance Objects . . . . . . . . . . . . . . . . . . . . . 100 Creating instance objects . . . . . . . . . . . . . . . . . . . . . . . . . 101 More on accessing attributes . . . . . . . . . . . . . . . . . . . . . . . 101 Deriving New Classes from Other Classes . . . . . . . . . . . . . . . . . . . 102 Multiple inheritance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Creating a custom list class . . . . . . . . . . . . . . . . . . . . . . . . 104 Creating a custom string class . . . . . . . . . . . . . . . . . . . . . . 105 Creating a custom dictionary class . . . . . . . . . . . . . . . . . . . 106 Hiding Private Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Identifying Class Membership . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Overloading Standard Behaviors . . . . . . . . . . . . . . . . . . . . . . . . 108 Overloading basic functionality . . . . . . . . . . . . . . . . . . . . . 109 Overloading numeric operators . . . . . . . . . . . . . . . . . . . . . 111 Overloading sequence and dictionary operators . . . . . . . . . . . 112 Overloading bitwise operators . . . . . . . . . . . . . . . . . . . . . . 114 Overloading type conversions . . . . . . . . . . . . . . . . . . . . . . 115 Using Weak References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Creating weak references . . . . . . . . . . . . . . . . . . . . . . . . . 116 Creating proxy objects . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Chapter 8: Input and Output . . . . . . . . . . . . . . . . . . . . . . . 119 Printing to the Screen . . . . . . . . . . Accessing Keyboard Input . . . . . . . . raw_input . . . . . . . . . . . . . . input . . . . . . . . . . . . . . . . . Opening, Closing, and Positioning Files open . . . . . . . . . . . . . . . . . File object information . . . . . . close . . . . . . . . . . . . . . . . . File position . . . . . . . . . . . . . Writing Files . . . . . . . . . . . . . . . . Reading Files . . . . . . . . . . . . . . . Accessing Standard I/O . . . . . . . . . Using Filelike Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part II: Files, Data Storage, and Operating System Services . . . . . . . . . . . . . 119 120 120 121 121 122 123 123 123 124 125 126 127 131 Chapter 9: Processing Strings and Regular Expressions . . . . . . . 133 Using String Objects . . . . . . . . . . . . String formatting methods . . . . . String case-changing methods . . . String format tests (the is-methods) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 134 134 135 4807-7 FM.F 5/24/01 8:57 AM Page xxi Contents String searching methods . . . . . . . . . . . . . . . String manipulation methods . . . . . . . . . . . . . Using the String Module . . . . . . . . . . . . . . . . . . . Character categories . . . . . . . . . . . . . . . . . . Miscellaneous functions . . . . . . . . . . . . . . . . Defining Regular Expressions . . . . . . . . . . . . . . . . Regular expression syntax . . . . . . . . . . . . . . Backslashes and raw strings . . . . . . . . . . . . . Character groups and other backslash magic . . . Nongreedy matching . . . . . . . . . . . . . . . . . . Extensions . . . . . . . . . . . . . . . . . . . . . . . . Creating and Using Regular Expression Objects . . . . . Using regular expression objects . . . . . . . . . . . Applying regular expressions without compiling . Using Match Objects . . . . . . . . . . . . . . . . . . . . . group([groupid,...]) . . . . . . . . . . . . . . . . . . groups([nomatch]) . . . . . . . . . . . . . . . . . . . groupdict([nomatch]) . . . . . . . . . . . . . . . . . start([groupid]), end([groupid]), span([groupid]) re,string,pos,endpos, . . . . . . . . . . . . . . . . . Treating Strings as Files . . . . . . . . . . . . . . . . . . . Encoding Text . . . . . . . . . . . . . . . . . . . . . . . . . Using Unicode strings . . . . . . . . . . . . . . . . . Reading and writing non-ASCII strings . . . . . . . . Using the Unicode database . . . . . . . . . . . . . Formatting Floating Point Numbers . . . . . . . . . . . . fix(number,precision) . . . . . . . . . . . . . . . . . sci(number,precision) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 137 138 138 139 140 140 142 142 143 143 144 145 147 147 148 148 148 148 149 149 151 151 151 153 154 154 154 Chapter 10: Working with Files and Directories . . . . . . . . . . . . 155 Retrieving File and Directory Information . . . . . . The piecemeal approach . . . . . . . . . . . . The I-want-it-all approach . . . . . . . . . . . . Building and Dissecting Paths . . . . . . . . . . . . . Joining path parts . . . . . . . . . . . . . . . . Breaking paths into pieces . . . . . . . . . . . Other path modifiers . . . . . . . . . . . . . . Listing Directories and Matching File Names . . . . Obtaining Environment and Argument Information Environment variables . . . . . . . . . . . . . Current working directory . . . . . . . . . . . Command-line parameters . . . . . . . . . . . Example: Recursive Grep Utility . . . . . . . . . . . Copying, Renaming, and Removing Paths . . . . . . Copying and linking . . . . . . . . . . . . . . . Renaming . . . . . . . . . . . . . . . . . . . . . Removing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 156 159 161 161 162 162 163 165 165 165 166 166 168 168 168 169 xxi 4807-7 FM.F xxii 5/24/01 8:57 AM Page xxii Python 2.1 Bible Creating Directories and Temporary Files . Comparing Files and Directories . . . . . . Working with File Descriptors . . . . . . . . General file descriptor functions . . . Pipes . . . . . . . . . . . . . . . . . . . Other File Processing Techniques . . . . . Randomly accessing lines in text files Using memory-mapped files . . . . . Iterating over several files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 171 173 173 174 174 174 175 176 Chapter 11: Using Other Operating System Services . . . . . . . . . 179 Executing Shell Commands and Other Programs Spawning Child Processes . . . . . . . . . . . . . popen functions . . . . . . . . . . . . . . . spawn functions . . . . . . . . . . . . . . . fork . . . . . . . . . . . . . . . . . . . . . . . Process management and termination . . Handling Process Information . . . . . . . . . . . Retrieving System Information . . . . . . . . . . Managing Configuration Files . . . . . . . . . . . Understanding Error Names . . . . . . . . . . . . Handling Asynchronous Signals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 181 181 182 183 183 185 187 188 190 191 Chapter 12: Storing Data and Objects . . . . . . . . . . . . . . . . . . 195 Data Storage Overview . . . . . . . . . . . . . Text versus binary . . . . . . . . . . . . Compression . . . . . . . . . . . . . . . Byte order (“Endianness”) . . . . . . . Object state . . . . . . . . . . . . . . . . Destination . . . . . . . . . . . . . . . . On the receiving end . . . . . . . . . . . Loading and Saving Objects . . . . . . . . . . Pickling with pickle . . . . . . . . . . . The marshal module . . . . . . . . . . . Example: Moving Objects Across a Network Using Database-Like Storage . . . . . . . . . Converting to and from C Structures . . . . . Converting Data to Standard Formats . . . . Sun’s XDR format . . . . . . . . . . . . . Other formats . . . . . . . . . . . . . . . Compressing Data . . . . . . . . . . . . . . . zlib . . . . . . . . . . . . . . . . . . . . . gzip . . . . . . . . . . . . . . . . . . . . . zipfile . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 195 196 196 196 196 196 197 197 200 200 203 204 208 208 210 210 211 213 214 4807-7 FM.F 5/24/01 8:57 AM Page xxiii Contents Chapter 13: Accessing Date and Time . . . . . . . . . . . . . . . . . . 219 Telling Time in Python . . . . . . . . . . . . . Ticks . . . . . . . . . . . . . . . . . . . . TimeTuple . . . . . . . . . . . . . . . . . Stopwatch time . . . . . . . . . . . . . . Converting Between Time Formats . . . . . . Parsing and Printing Dates and Times . . . . Fancy formatting . . . . . . . . . . . . . Parsing time . . . . . . . . . . . . . . . . Localization . . . . . . . . . . . . . . . . Accessing the Calendar . . . . . . . . . . . . Printing monthly and yearly calendars Calendar information . . . . . . . . . . Leap years . . . . . . . . . . . . . . . . . Using Time Zones . . . . . . . . . . . . . . . . Allowing Two-Digit Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219 219 220 220 221 222 222 223 223 224 224 225 226 226 227 Chapter 14: Using Databases . . . . . . . . . . . . . . . . . . . . . . . 229 Using Disk-Based Dictionaries . . . . . . . . . DBM Example: Tracking Telephone Numbers Advanced Disk-Based Dictionaries . . . . . . dbm . . . . . . . . . . . . . . . . . . . . gdbm . . . . . . . . . . . . . . . . . . . . dbhash . . . . . . . . . . . . . . . . . . . Using BSD database objects . . . . . . Accessing Relational Databases . . . . . . . . Connection objects . . . . . . . . . . . Transactions . . . . . . . . . . . . . . . Cursor objects . . . . . . . . . . . . . . Example: “Sounds-Like” Queries . . . . . . . Examining Relational Metadata . . . . . . . . Example: Creating Auditing Tables . . . . . . Advanced Features of the DB API . . . . . . . Input and output sizes . . . . . . . . . . Reusable SQL statements . . . . . . . . Database library information . . . . . . Error hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part III: Networking and the Internet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 231 232 232 232 233 233 234 234 234 235 235 237 238 240 241 242 242 243 245 Chapter 15: Networking . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Networking Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247 Working with Addresses and Host Names . . . . . . . . . . . . . . . . . . . 248 xxiii 4807-7 FM.F xxiv 5/24/01 8:57 AM Page xxiv Python 2.1 Bible Communicating with Low-Level Sockets . . . . Creating and destroying sockets . . . . . Connecting sockets . . . . . . . . . . . . Sending and receiving data . . . . . . . . Using socket options . . . . . . . . . . . . Converting numbers . . . . . . . . . . . . Example: A Multicast Chat Application . . . . Using SocketServers . . . . . . . . . . . . . . . The SocketServer family . . . . . . . . . . Request handlers . . . . . . . . . . . . . . Processing Web Browser Requests . . . . . . . BaseHTTPRequestHandler . . . . . . . . SimpleHTTPRequestHandler . . . . . . . CGIHTTPRequestHandler . . . . . . . . . Example: form handler CGI script . . . . Handling Multiple Requests Without Threads asyncore . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 250 250 251 252 253 256 256 261 261 263 264 265 266 267 267 269 271 Chapter 16: Speaking Internet Protocols . . . . . . . . . . . . . . . . 275 Python’s Internet Protocol Support . . . Retrieving Internet Resources . . . . . . . Manipulating URLs . . . . . . . . . . Treating a URL as a file . . . . . . . URLopeners . . . . . . . . . . . . . Extended URL opening . . . . . . . Sending HTTP Requests . . . . . . . . . . Building and using request objects Sending and Receiving E-Mail . . . . . . . Accessing POP3 accounts . . . . . . Accessing SMTP accounts . . . . . Accessing IMAP accounts . . . . . . Transferring Files via FTP . . . . . . . . . Retrieving Resources Using Gopher . . . Working with Newsgroups . . . . . . . . . Using the Telnet Protocol . . . . . . . . . Connecting . . . . . . . . . . . . . . Reading and writing . . . . . . . . . Watching and waiting . . . . . . . . Other methods . . . . . . . . . . . . Writing CGI Scripts . . . . . . . . . . . . . Setting up CGI scripts . . . . . . . . Accessing form fields . . . . . . . . Advanced CGI functions . . . . . . . A note on debugging . . . . . . . . . A note on security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275 276 276 277 277 278 279 279 281 281 283 285 289 291 292 296 296 296 297 297 298 298 299 301 301 302 4807-7 FM.F 5/24/01 8:57 AM Page xxv Contents Chapter 17: Handling Internet Data . . . . . . . . . . . . . . . . . . . 303 Manipulating URLs . . . . . . . . . . . . . . . . Formatting Text . . . . . . . . . . . . . . . . . . Formatter interface . . . . . . . . . . . . Writer interface . . . . . . . . . . . . . . . Other module resources . . . . . . . . . . Reading Web Spider Robot Files . . . . . . . . Viewing Files in a Web Browser . . . . . . . . . Dissecting E-Mail Messages . . . . . . . . . . . Parsing a message . . . . . . . . . . . . . Retrieving header values . . . . . . . . . Other members . . . . . . . . . . . . . . . Address lists . . . . . . . . . . . . . . . . rfc822 utility functions . . . . . . . . . . . MIME messages . . . . . . . . . . . . . . . Working with MIME Encoding . . . . . . . . . . Encoding and decoding MIME messages Parsing multipart MIME messages . . . . Writing out multipart MIME messages . . Handling document types . . . . . . . . . Encoding and Decoding Message Data . . . . . Uuencode . . . . . . . . . . . . . . . . . . Base64 . . . . . . . . . . . . . . . . . . . . Quoted-printable . . . . . . . . . . . . . . Working with UNIX Mailboxes . . . . . . . . . . Working with MH mailboxes . . . . . . . Using Web Cookies . . . . . . . . . . . . . . . . Cookies . . . . . . . . . . . . . . . . . . . Morsels . . . . . . . . . . . . . . . . . . . Example: a cookie importer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303 304 304 305 306 307 308 309 309 309 310 310 311 311 312 312 313 313 316 317 317 318 319 320 320 321 322 322 323 Chapter 18: Parsing XML and Other Markup Languages . . . . . . . 325 Markup Language Basics . . . . . . . . . . . . Tags are for metatext . . . . . . . . . . Tag rules . . . . . . . . . . . . . . . . . . Namespaces . . . . . . . . . . . . . . . . Processing XML . . . . . . . . . . . . . Parsing HTML Files . . . . . . . . . . . . . . . HTMLParser methods . . . . . . . . . . Handling tags . . . . . . . . . . . . . . . Other parsing methods . . . . . . . . . Handling unknown or bogus elements Example: Bold Only . . . . . . . . . . . . . . . Example: Web Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325 326 326 327 327 327 328 328 328 329 330 331 xxv 4807-7 FM.F xxvi 5/24/01 8:57 AM Page xxvi Python 2.1 Bible Parsing XML with SAX . . . . . . . . . . . . . . . . Using a ContentHandler . . . . . . . . . . . . Example: blood-type extractor . . . . . . . . Using parser (XMLReader) objects . . . . . SAX exceptions . . . . . . . . . . . . . . . . . Parsing XML with DOM . . . . . . . . . . . . . . . . DOM nodes . . . . . . . . . . . . . . . . . . . Elements, attributes, and text . . . . . . . . The document node (DOM) . . . . . . . . . . Example: data import and export with DOM Parsing XML with xmllib . . . . . . . . . . . . . . . Elements and attributes . . . . . . . . . . . . XML handlers . . . . . . . . . . . . . . . . . . Other XMLParser members . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part IV: User Interfaces and Multimedia . . . . . . . . . . . . . . 334 334 335 336 337 338 338 338 339 339 341 342 343 343 345 Chapter 19: Tinkering with Tkinter . . . . . . . . . . . . . . . . . . . . 347 Getting Your Feet Wet . . . . . . . . . . Creating a GUI . . . . . . . . . . . . . . . Building an interface with widgets Widget options . . . . . . . . . . . Laying Out Widgets . . . . . . . . . . . . Packer options . . . . . . . . . . . Grid options . . . . . . . . . . . . . Example: Breakfast Buttons . . . . . . . Using Common Options . . . . . . . . . Color options . . . . . . . . . . . . Size options . . . . . . . . . . . . . Appearance options . . . . . . . . Behavior options . . . . . . . . . . Gathering User Input . . . . . . . . . . . Example: Printing Fancy Text . . . . . . Using Text Widgets . . . . . . . . . . . . Building Menus . . . . . . . . . . . . . . Using Tkinter Dialogs . . . . . . . . . . . File dialogs . . . . . . . . . . . . . Example: Text Editor . . . . . . . . . . . Handling Colors and Fonts . . . . . . . . Colors . . . . . . . . . . . . . . . . Fonts . . . . . . . . . . . . . . . . . Drawing Graphics . . . . . . . . . . . . . The canvas widget . . . . . . . . . Manipulating canvas items . . . . Using Timers . . . . . . . . . . . . . . . . Example: A Bouncing Picture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 348 348 349 349 350 351 352 354 354 355 355 355 356 357 359 360 361 362 362 365 365 366 366 366 367 368 368 4807-7 FM.F 5/24/01 8:57 AM Page xxvii Contents Chapter 20: Using Advanced Tkinter Widgets . . . . . . . . . . . . . 371 Handling Events . . . . . . . . . . . . . Creating event handlers . . . . . Binding mouse events . . . . . . Binding keyboard events . . . . Event objects . . . . . . . . . . . Example: A Drawing Canvas . . . . . . Advanced Widgets . . . . . . . . . . . Listbox . . . . . . . . . . . . . . . Scale . . . . . . . . . . . . . . . . Scrollbar . . . . . . . . . . . . . . Example: Color Scheme Customizer . Creating Dialogs . . . . . . . . . . . . . Supporting Drag-and-Drop Operations Using Cursors . . . . . . . . . . . . . . Designing New Widgets . . . . . . . . Further Tkinter Adventures . . . . . . Additional widgets . . . . . . . . Learning more . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 371 372 372 373 373 375 375 376 376 377 381 382 385 387 389 389 389 Chapter 21: Building User Interfaces with wxPython . . . . . . . . . 391 Introducing wxPython . . . . . . . . . . . . . Creating Simple wxPython Programs . . . . . Choosing Different Window Types . . . . . . Managed windows . . . . . . . . . . . . Nonmanaged windows . . . . . . . . . . Using wxPython Controls . . . . . . . . . . . Common controls . . . . . . . . . . . . Tree controls . . . . . . . . . . . . . . . Editor controls . . . . . . . . . . . . . . Controlling Layout . . . . . . . . . . . . . . . Specifying coordinates . . . . . . . . . Sizers . . . . . . . . . . . . . . . . . . . . Layout constraints . . . . . . . . . . . . Layout algorithms . . . . . . . . . . . . Using Built-in Dialogs . . . . . . . . . . . . . . Drawing with Device Contexts . . . . . . . . Adding Menus and Keyboard Shortcuts . . . Accessing Mouse and Keyboard Input . . . . Other wxPython Features . . . . . . . . . . . Clipboard, drag and drop, and cursors Graphics . . . . . . . . . . . . . . . . . . Date and time . . . . . . . . . . . . . . . Fonts . . . . . . . . . . . . . . . . . . . . HTML . . . . . . . . . . . . . . . . . . . Printing . . . . . . . . . . . . . . . . . . Other . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 392 394 394 395 399 399 400 401 401 402 403 406 407 407 408 411 412 412 413 413 413 413 414 414 414 xxvii 4807-7 FM.F xxviii 5/24/01 8:57 AM Page xxviii Python 2.1 Bible Chapter 22: Using Curses . . . . . . . . . . . . . . . . . . . . . . . . . . 415 A Curses Overview . . . . . . . . . . . . . . . . . . Starting Up and Shutting Down . . . . . . . . . . . Displaying and Erasing Text . . . . . . . . . . . . . Reading from the window (screen-scraping) Erasing . . . . . . . . . . . . . . . . . . . . . . Refreshing . . . . . . . . . . . . . . . . . . . . Boxes and lines . . . . . . . . . . . . . . . . . The window background . . . . . . . . . . . Example: masking a box . . . . . . . . . . . . Moving the Cursor . . . . . . . . . . . . . . . . . . Getting User Input . . . . . . . . . . . . . . . . . . Reading keys . . . . . . . . . . . . . . . . . . Other keyboard-related functions . . . . . . Fancy characters . . . . . . . . . . . . . . . . Reading mouse input . . . . . . . . . . . . . Example: yes, no, or maybe . . . . . . . . . . Managing Windows . . . . . . . . . . . . . . . . . . Pads . . . . . . . . . . . . . . . . . . . . . . . Stacking windows . . . . . . . . . . . . . . . Editing Text . . . . . . . . . . . . . . . . . . . . . . Using Color . . . . . . . . . . . . . . . . . . . . . . Numbering . . . . . . . . . . . . . . . . . . . Setting colors . . . . . . . . . . . . . . . . . . Tweaking the colors . . . . . . . . . . . . . . Example: A Simple Maze Game . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415 416 416 417 418 418 418 418 419 420 421 422 422 422 423 424 425 425 426 426 427 427 428 428 428 Chapter 23: Building Simple Command Interpreters . . . . . . . . . 433 Beginning with the End in Mind . . . Understanding the Lepto Language Creating a Lepto Lexical Analyzer . The shlex module . . . . . . . Putting shlex to work . . . . . Adding Interactive-Mode Features . Using the cmd module . . . . . Subclassing cmd.Cmd . . . . . Executing Lepto Commands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 433 435 436 436 437 440 440 442 445 Chapter 24: Playing Sound . . . . . . . . . . . . . . . . . . . . . . . . . 453 Sound File Basics . . . . . . . . . . . . . . . . Playing Sounds . . . . . . . . . . . . . . . . . Playing sound on Windows . . . . . . . Playing and recording sound on SunOS Examining Audio Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453 454 454 455 456 4807-7 FM.F 5/24/01 8:57 AM Page xxix Contents Reading and Writing Audio Files . . . . . . . . Reading and writing AIFF files with aifc . Reading and writing AU files with sunau Reading and writing WAV files with wave Example: Reversing an audio file . . . . . Reading IFF chunked data . . . . . . . . . Handling Raw Audio Data . . . . . . . . . . . . Examining a fragment . . . . . . . . . . . Searching and matching . . . . . . . . . . Translating between storage formats . . Manipulating fragments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part V: Advanced Python Programming . . . . . . . . . . . 456 457 458 458 458 460 461 461 462 462 463 465 Chapter 25: Processing Images . . . . . . . . . . . . . . . . . . . . . . 467 Image Basics . . . . . . . . . . . . . . . . . . . . Identifying Image File Types . . . . . . . . . . . Converting Between Color Systems . . . . . . Color systems . . . . . . . . . . . . . . . . Converting from one system to another Handling Raw Image Data . . . . . . . . . . . . Using the Python Imaging Library . . . . . . . Retrieving image information . . . . . . . Copying and converting images . . . . . Using PIL with Tkinter . . . . . . . . . . . Cropping and resizing images . . . . . . Modifying pixel data . . . . . . . . . . . . Other PIL features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467 468 469 469 470 472 472 473 474 475 476 476 480 Chapter 26: Multithreading . . . . . . . . . . . . . . . . . . . . . . . . 481 Understanding Threads . . . . . . . . . . . . . . . . . . . . . . . Spawning, Tracking, and Killing Threads . . . . . . . . . . . . . Creating threads with the thread module . . . . . . . . . . Starting and stopping threads with the threading module Thread status and information under threading . . . . . . Finding threads under threading . . . . . . . . . . . . . . . Waiting for a thread to finish . . . . . . . . . . . . . . . . . Avoiding Concurrency Issues . . . . . . . . . . . . . . . . . . . . Locking with thread . . . . . . . . . . . . . . . . . . . . . . Locking with threading . . . . . . . . . . . . . . . . . . . . Preventing Deadlock . . . . . . . . . . . . . . . . . . . . . . . . . Example: Downloading from Multiple URLs . . . . . . . . . . . . Porting Threaded Code . . . . . . . . . . . . . . . . . . . . . . . Weaving Threads Together with Queues . . . . . . . . . . . . . . Technical Note: How Simultaneous Is Simultaneous? . . . . . . For More Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 481 482 482 483 484 484 484 485 485 486 488 489 494 495 495 496 xxix 4807-7 FM.F xxx 5/24/01 8:57 AM Page xxx Python 2.1 Bible Chapter 27: Debugging, Profiling, and Optimization . . . . . . . . . 497 Debugging Python Code . . . . . . . . . . . . . Starting and stopping the debugger . . . Examining the state of things . . . . . . . Setting breakpoints . . . . . . . . . . . . Running . . . . . . . . . . . . . . . . . . . Aliases . . . . . . . . . . . . . . . . . . . . Debugging tips . . . . . . . . . . . . . . . Working with docstrings . . . . . . . . . . . . . Automating Tests . . . . . . . . . . . . . . . . . Synching docstrings with code . . . . . . Unit testing . . . . . . . . . . . . . . . . . Finding Bottlenecks . . . . . . . . . . . . . . . . Profiling code . . . . . . . . . . . . . . . . Using Profile objects . . . . . . . . . . . . Calibrating the profiler . . . . . . . . . . Customizing statistics . . . . . . . . . . . Common Optimization Tricks . . . . . . . . . . Sorting . . . . . . . . . . . . . . . . . . . . Looping . . . . . . . . . . . . . . . . . . . I/O . . . . . . . . . . . . . . . . . . . . . . Strings . . . . . . . . . . . . . . . . . . . . Threads . . . . . . . . . . . . . . . . . . . Taking out the Trash — the Garbage Collector Reference counts and Python code . . . Reference counts and C/C++ code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497 497 498 499 500 500 500 501 502 502 503 505 505 506 507 507 509 509 510 510 511 511 512 512 513 Chapter 28: Security and Encryption . . . . . . . . . . . . . . . . . . . 515 Checking Passwords . . . . . . . . . . Running in a Restricted Environment The rexec sandbox . . . . . . . . Using a class fortress . . . . . . Creating Message Fingerprints . . . . MD5 . . . . . . . . . . . . . . . . SHA . . . . . . . . . . . . . . . . . Other uses . . . . . . . . . . . . . Using 1940s-Era Encryption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 515 516 517 520 521 522 522 523 523 Chapter 29: Writing Extension Modules . . . . . . . . . . . . . . . . . 527 Extending and Embedding Overview . Writing a Simple Extension Module . . Building and Linking . . . . . . . . . . Converting Python Data to C . . . . . Unpacking normal arguments . Using special format characters Unpacking keyword arguments . Unpacking zero arguments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527 528 531 532 532 535 537 538 4807-7 FM.F 5/24/01 8:57 AM Page xxxi Contents Converting C Data to Python . . . . . . Creating simple Python objects . Creating complex Python objects Embedding the Interpreter . . . . . . . A simple example . . . . . . . . . . Shutting down . . . . . . . . . . . Other setup functions . . . . . . . System information functions . . Running Python Code from C . . . . . . Using Extension Tools . . . . . . . . . . SWIG . . . . . . . . . . . . . . . . . CXX . . . . . . . . . . . . . . . . . . Extension classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 538 539 540 541 541 541 542 542 543 546 546 549 550 Chapter 30: Embedding the Python Interpreter . . . . . . . . . . . . 553 Tracking Reference Counts . . . . . . . . . . . . Types of reference ownership . . . . . . . Reference conventions . . . . . . . . . . . Common pitfalls . . . . . . . . . . . . . . . Using the Abstract and Concrete Object Layers Object layers . . . . . . . . . . . . . . . . . Working with generic objects . . . . . . . . Working with Number Objects . . . . . . . . . . Any numerical type . . . . . . . . . . . . . Integers . . . . . . . . . . . . . . . . . . . . Longs . . . . . . . . . . . . . . . . . . . . . Floating-point numbers . . . . . . . . . . . Complex numbers . . . . . . . . . . . . . . Working with Sequence Objects . . . . . . . . . Any sequence type . . . . . . . . . . . . . . Strings . . . . . . . . . . . . . . . . . . . . . Lists . . . . . . . . . . . . . . . . . . . . . . Tuples . . . . . . . . . . . . . . . . . . . . . Buffers . . . . . . . . . . . . . . . . . . . . . Unicode strings . . . . . . . . . . . . . . . . Working with Mapping Objects . . . . . . . . . . Functions for any mapping type . . . . . . Dictionaries . . . . . . . . . . . . . . . . . . Using Other Object Types . . . . . . . . . . . . . Type . . . . . . . . . . . . . . . . . . . . . . None . . . . . . . . . . . . . . . . . . . . . . File . . . . . . . . . . . . . . . . . . . . . . . Module . . . . . . . . . . . . . . . . . . . . . CObjects . . . . . . . . . . . . . . . . . . . . Creating Threads and Sub-Interpreters . . . . . Threads . . . . . . . . . . . . . . . . . . . . Sub-interpreters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553 553 554 555 555 556 556 558 558 560 560 561 561 561 562 563 564 565 566 567 569 569 570 571 571 571 571 572 574 574 575 576 xxxi 4807-7 FM.F xxxii 5/24/01 8:57 AM Page xxxii Python 2.1 Bible Handling Errors and Exceptions . Checking for errors . . . . . Signaling error conditions . . Creating custom exceptions Raising warnings . . . . . . . Managing Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 576 577 577 578 578 579 Chapter 31: Number Crunching . . . . . . . . . . . . . . . . . . . . . . 581 Using Math Routines . . . . . . . . . . . . . . . . . . . . . . . . . . . Rounding and fractional parts . . . . . . . . . . . . . . . . . . General math routines . . . . . . . . . . . . . . . . . . . . . . . Logarithms and exponentiation . . . . . . . . . . . . . . . . . Trigonometric functions . . . . . . . . . . . . . . . . . . . . . . Computing with Complex Numbers . . . . . . . . . . . . . . . . . . Generating Random Numbers . . . . . . . . . . . . . . . . . . . . . . Random numbers . . . . . . . . . . . . . . . . . . . . . . . . . Example: shuffling a deck . . . . . . . . . . . . . . . . . . . . . Random distributions . . . . . . . . . . . . . . . . . . . . . . . Example: plotting distributions using Monte Carlo sampling Using Arbitrary-Precision Numbers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581 581 582 582 582 583 583 583 585 585 586 587 Chapter 32: Using NumPy . . . . . . . . . . . . . . . . . . . . . . . . . 589 Introducing Numeric Python . . . . . . . . Installing NumPy . . . . . . . . . . . . Some quick definitions . . . . . . . . Meet the array . . . . . . . . . . . . . Accessing and Slicing Arrays . . . . . . . . Contiguous arrays . . . . . . . . . . . Converting arrays to lists and strings Calling Universal Functions . . . . . . . . . Ufunc destinations . . . . . . . . . . . Example: editing an audio stream . . Repeating ufuncs . . . . . . . . . . . . Creating Arrays . . . . . . . . . . . . . . . . Array creation functions . . . . . . . Seeding arrays with functions . . . . Using Element Types . . . . . . . . . . . . . Reshaping and Resizing Arrays . . . . . . . Using Other Array Functions . . . . . . . . sort(array,[axis=-1]) . . . . . . . . . . where(condition,X,Y) . . . . . . . . . swapaxes(array,axis1,axis2) . . . . . Matrix operations . . . . . . . . . . . Array Example: Analyzing Price Trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 589 589 590 590 590 592 592 593 594 594 595 597 597 598 600 600 601 601 602 602 602 603 4807-7 FM.F 5/24/01 8:57 AM Page xxxiii Contents Chapter 33: Parsing and Interpreting Python Code . . . . . . . . . . 605 Examining Tracebacks . . . . . . . . . . . . . . . . . Printing a traceback — print_exc and friends Extracting and formatting exceptions . . . . . Example: reporting exceptions in a GUI . . . . Eating arbitrary exceptions is bad for you . . Introspection . . . . . . . . . . . . . . . . . . . . . . Review: basic introspection . . . . . . . . . . . Browsing classes . . . . . . . . . . . . . . . . . Browsing function information . . . . . . . . . Checking Indentation . . . . . . . . . . . . . . . . . . Tokenizing Python Code . . . . . . . . . . . . . . . . Example: Syntax-Highlighting Printer . . . . . . . . Inspecting Python Parse Trees . . . . . . . . . . . . Creating an AST . . . . . . . . . . . . . . . . . . ASTs and sequences . . . . . . . . . . . . . . . Using ASTs . . . . . . . . . . . . . . . . . . . . Low-Level Object Creation . . . . . . . . . . . . . . . Disassembling Python Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part VI: Deploying Python Applications . . . . . . . . . . . . . . . . . . 605 605 606 607 607 608 608 609 609 611 611 612 613 613 614 614 614 615 617 Chapter 34: Creating Worldwide Applications . . . . . . . . . . . . . 619 Internationalization and Localization . . . . . Preparing Applications for Multiple Languages An NLS example . . . . . . . . . . . . . . What it all means . . . . . . . . . . . . . . Formatting Locale-Specific Output . . . . . . . Changing the locale . . . . . . . . . . . . Locale-specific formatting . . . . . . . . . Properties of locales . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 619 620 620 623 624 624 625 626 Chapter 35: Customizing Import Behavior . . . . . . . . . . . . . . . 629 Understanding Module Importing . . . . . Finding and Loading Modules with imp . . Importing Encrypted Modules . . . . . . . Retrieving Modules from a Remote Source Subclassing Importer . . . . . . . . . Creating the remote Importer . . . . Testing the remote Importer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629 631 633 636 636 637 640 xxxiii 4807-7 FM.F xxxiv 5/24/01 8:57 AM Page xxxiv Python 2.1 Bible Chapter 36: Distributing Modules and Applications . . . . . . . . . 643 Understanding distutils . . . . . . . . . . Creating a simple distribution . . . Installing the simple distribution . . Other distutils Features . . . . . . . . . . Distributing packages . . . . . . . . Including other files . . . . . . . . . Customizing setup . . . . . . . . . . Distributing Extension Modules . . . . . . Creating Source and Binary Distributions Source distributions . . . . . . . . . Binary distributions . . . . . . . . . Installers . . . . . . . . . . . . . . . . Building Standalone Executables . . . . . py2exe . . . . . . . . . . . . . . . . . Freeze . . . . . . . . . . . . . . . . . Other tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part VII: Platform-Specific Support . . . . . . . . . . . . . . . . 643 644 645 647 647 648 650 650 651 652 653 653 655 655 656 657 659 Chapter 37: Windows . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661 Using win32all . . . . . . . . . . . . . . . . . . . . . . . . . Data types . . . . . . . . . . . . . . . . . . . . . . . . Error handling . . . . . . . . . . . . . . . . . . . . . Finding what you need . . . . . . . . . . . . . . . . . Example: Using Some Windows APIs . . . . . . . . . . . . Accessing the Windows Registry . . . . . . . . . . . . . . Accessing the registry with win32all . . . . . . . . . Example: setting the Internet Explorer home page Creating, deleting, and navigating keys . . . . . . . Example: recursive deletion of a key . . . . . . . . Other registry functions . . . . . . . . . . . . . . . . Accessing the registry with _winreg . . . . . . . . . Using msvcrt Goodies . . . . . . . . . . . . . . . . . . . . Console I/O . . . . . . . . . . . . . . . . . . . . . . . Other functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661 661 662 662 662 664 664 666 666 667 668 668 669 669 670 Chapter 38: UNIX-Compatible Modules . . . . . . . . . . . . . . . . . 671 Checking UNIX Passwords and Groups . . . . Accessing the System Logger . . . . . . . . . . Calling Shared Library Functions . . . . . . . . Providing Identifier and Keyword Completion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671 673 675 675 4807-7 FM.F 5/24/01 8:57 AM Page xxxv Contents Retrieving File System and Resource Information File system information . . . . . . . . . . . . Resource usage . . . . . . . . . . . . . . . . . Resource limits . . . . . . . . . . . . . . . . . Controlling File Descriptors . . . . . . . . . . . . . Handling Terminals and Pseudo-Terminals . . . . Interfacing with Sun’s NIS “Yellow Pages” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 677 678 678 679 680 681 682 Appendix A: Online Resources . . . . . . . . . . . . . . . . . . . . . . 685 Appendix B: Python Development Environments . . . . . . . . . . . 689 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 701 xxxv 4807-7 FM.F 5/24/01 8:57 AM Page xxxvi 4807-7 PO1.F 5/24/01 8:57 AM Page 1 P The Python Language A R T I ✦ ✦ ✦ ✦ Chapter 1 Python in an Hour Chapter 2 Identifiers, Variables, and Numeric Types Chapter 3 Expressions and Strings Chapter 4 Advanced Data Types Chapter 5 Control Flow Chapter 6 Program Organization Chapter 7 Object-Oriented Python Chapter 8 Input and Output ✦ ✦ ✦ ✦ 4807-7 PO1.F 5/24/01 8:57 AM Page 2 4807-7 ch01.F 5/24/01 8:57 AM Page 3 1 CHAPTER Python in an Hour ✦ ✦ ✦ ✦ In This Chapter P Jumping in: Starting the Python interpreter As you read, please fire up the Python interpreter, and try out some of the examples. Feel free to experiment, tinker, and wander away from the rest of the tour group. Everything in this chapter is repeated, in greater detail, in later chapters, so don’t worry too much about absorbing everything at once. Try some things out, get your feet wet, and have fun! Defining a function ython is a rich and powerful language, but also one that is easy to learn. This chapter gives an overview of Python’s syntax, its useful data-types, and its unique features. Jumping In: Starting the Python Interpreter The first thing to do, if you haven’t already, is to install Python. You can download Python from www.python.org. As of this writing, the latest versions of Python are 2.0 (stable) and 2.1 (still in beta). You can start the Python interpreter from the command line. Change to the directory where the interpreter lives, or add the directory to your path. Then type: python On UNIX, Python typically lives in /usr/local/bin; on Windows, Python probably lives in c:\python20. On Windows, you can also bring the interpreter up from Start ➪ Programs ➪ Python 2.0 ➪ Python (command line). Experimenting with variables and expressions Running a Python program Looping and control Lists and tuples Dictionaries Reading and writing files Loading and using modules Creating a class ✦ ✦ ✦ ✦ 4807-7 ch01.F 4 5/24/01 8:57 AM Page 4 Part I ✦ The Python Language Once you start the interpreter, Python displays something like this: Python 2.0 (#8, Oct 16 2000, 17:27:58) [MSC 32 bit (Intel)] on win32 Type “copyright”, “credits” or “license” for more information. >>> The interpreter displays the >>> prompt to show that it’s ready for you to type in some Python. And so, in the grand tradition of programming books everywhere, we proceed to the “Hello world” example: >>> print “Hello world!” Hello world! To exit the interpreter, type the end-of-file character (Ctrl-Z on Windows, or Ctrl-D on Linux) and press Enter. Note You may prefer to interact with the interpreter in IDLE, the standard Python IDE. IDLE features syntax coloring, a class browser, and other handy features. See Appendix B for tips on starting and using IDLE. Experimenting with Variables and Expressions Python’s syntax for variables and expressions is close to what you would see in C or Java, so you can skim this section if it starts looking familiar. However, you should take note of Python’s loose typing (see below). Pocket calculator Python understands the standard arithmetic operators, including +, -, / (division), and * (multiplication). The Python interpreter makes a handy calculator: >>> 8/2 4 >>> 5+4*6 29 Note that the second example evaluates 29 (and not 54); the interpreter multiplies 4 by 6 before adding 5. Python uses operator precedence rules to decide what to do first. You can control order explicitly by using parentheses: >>> (5+4)*6 54 In practice, it’s often easiest to use parentheses (even when they aren’t required) to make code more readable. 4807-7 ch01.F 5/24/01 8:57 AM Page 5 Chapter 1 ✦ Python in an Hour Variables You can use variables to hold values over time. For example, this code computes how long it takes to watch every episode of Monty Python’s Flying Circus (including the two German episodes of Monty Python’s Fliegende Zirkus): >>> NumberOfEpisodes=47 >>> EpisodeLength=0.5 >>> PythonMarathonLength=(NumberOfEpisodes*EpisodeLength) >>> PythonMarathonLength 23.5 A variable is always a reference to a value. Variables do not have types, but objects do. (Python is loosely typed; the same variable may refer to an integer value in the morning and a string value in the afternoon.) Python does not require variable declarations. However, you cannot access a variable until you have assigned it a value. If you try to access an undefined variable, the interpreter will complain (the wording of the error may be different in your version of Python): >>> print Scrumptious Traceback (most recent call last): File “<stdin>”, line 1, in ? NameError: There is no variable named ‘Scrumptious’ This example raised an exception. In Python, most errors are represented by exception objects that the surrounding code can handle. Chapter 5 describes Python’s exception-handling abilities. Note Python is case-sensitive. This means that names that are capitalized differently refer to different variables: >>> FavoriteColor=”blue” >>> favoritecolor=”yellow” >>> print FavoriteColor,favoritecolor blue yellow Defining a Function Assume you and some friends go out to dinner and decide to split the bill evenly. How much should each person pay? Here is a function that calculates each person’s share: >>> def SplitBill(Bill,NumberOfPeople): ... # The hash character (#) starts a comment. Python ... # ignores everything from # to the end of the line. ... TotalWithTip = Bill * (1.15) # Add a 15% tip. 5 4807-7 ch01.F 6 5/24/01 8:57 AM Page 6 Part I ✦ The Python Language ... return (TotalWithTip / NumberOfPeople) ... >>> SplitBill(23.35,3) 8.9508333333333336 The statement def FunctionName (parameter,...): starts a function definition. I indented the following four lines to indicate that they are a control block — a sequence of statements grouped by a common level of indentation. Together, they make up the body of the function definition. Python statements with the same level of indentation are grouped together. In this example, Python knows the function definition ends when it sees a non-indented line. Grouping statements by indentation-level is common practice in most programming languages; in Python it is actually part of the syntax. Normally, one indentation level equals four spaces, and eight spaces equals one tab. Running a Python Program A text file consisting of Python code is called a program, or a script, or a module. There is little distinction between the three terms — generally a script is smaller than a program, and a file designed to be imported (rather than executed directly) is called a module. Normally, you name Python code files with a .py extension. To run a program named spam.py, type the following at a command prompt: python spam.py In Windows, you can run a program by double-clicking it. (If the file association for the .py extension is not set up at installation time, you can configure it by rightclicking the script, choosing “Open With...” and then choosing python.exe.) In UNIX, you can run a script directly by using the “pound-bang hack.” Add this line at the top of the Python script (replacing the path with the path to env if it’s different on your system): #!/usr/bin/python Then make the file executable (by running chmod +x <filename>), and you can run it directly. Looping and Control Listing 1-1 illustrates Python’s looping and conditional statements. It prints out all the prime numbers less than 500. 4807-7 ch01.F 5/24/01 8:57 AM Page 7 Chapter 1 ✦ Python in an Hour Listing 1-1: PrimeFinder.py print 1 # Loop over the numbers from 2 to 499: for PrimeTest in range(2,500): # Assume PrimeTest prime until proven otherwise: IsPrime = 1 # 0 is false, nonzero is true # Loop over the numbers from 2 to (PrimeTest-1): for TestFactor in range(2,PrimeTest): # a % b equals the remainder of a/b: if (PrimeTest % TestFactor == 0): # PrimeTest divides TestFactor (remainder is 0). IsPrime=0 break # Jump out of the innermost for-loop. if (IsPrime): print PrimeTest Integer division The modulo operator, %, returns the remainder when the first number is divided by the second. (For instance, 8 % 5 is equal to 3.) If PrimeTest is zero modulo TestFactor, then this remainder is zero, so TestFactor is one of PrimeTest’s divisors. In Python, dividing one integer by another returns another integer — the quotient, rounded down: >>> 8/3 # I want an integer, not the “right answer.” 2 So, here is a sneaky replacement to line 7 of PrimeFinder.py. If TestFactor does not divide PrimeTest evenly, then the quotient is rounded off, and so the comparison will fail: if ((PrimeTest/TestFactor)*TestFactor == PrimeTest) Python uses the float class for floating-point (decimal) numbers. The float function transforms a value into a float: >>> 8.0/3.0 2.6666666666666665 >>> float(8)/float(3) # Give me the “real” quotient. 2.6666666666666665 7 4807-7 ch01.F 8 5/24/01 8:57 AM Page 8 Part I ✦ The Python Language Looping The for statement sets up a loop — a block of code that is executed many times. The function range(startnum,endnum) provides a list of integers starting with startnum and ending just before endnum. In the example, PrimeTest takes on each value in the range in order, and the outer loop executes once for each value of PrimeTest. The inner loop iterates over the “possible factors” of PrimeTest, starting at 2 and continuing until (PrimeTest-1). Branching with if-statements The statement if expression: begins a control block that executes only if expression is true. You can enclose the expression in parentheses. As far as Python is concerned, the number 0 is false, and any other number is true. Note that in a condition, we use the == operator to test for equality. The = operator is used only for assignments, and assignments are forbidden within a condition. (Here Python differs from C/C++, which allows assignments inside an if-condition, even though they are usually a horrible mistake.) In an if statement, an else-clause executes when the condition is not true. For example: if (MyNumber % 2 == 0): print “MyNumber is even!” else: print “MyNumber is odd!” Breaking and continuing The break statement jumps out of a loop. It exits the innermost loop in the current context. In Listing 1-1, the break statement exits the inner TestFactor loop, and continues on line 11. The continue statement jumps to the next iteration of a loop. Loops can also be set up using the while statement. The syntax while (expression) sets up a control block that executes as long as expression is true. For example: # print out powers of 2 less than 2000 X=2 while (X<2000): print X X=X*2 4807-7 ch01.F 5/24/01 8:57 AM Page 9 Chapter 1 ✦ Python in an Hour Lists and Tuples A list is an ordered collection of zero or more elements. An element of a list can be any sort of object. You can write lists as a comma-separated collection of values enclosed in square brackets. For example: FibonacciList=[1,1,2,3,5,8] FishList=[1,2,”Fish”] # Lists can contain various types. AnotherList=[1,2,FishList] # Lists can include other lists. YetAnotherList=[1,2,3,] # Trailing commas are ok. RevengeOfTheList= # The empty list Tuples A tuple is similar to a list. The difference is that a tuple is immutable — it cannot be modified. You enclose tuples in parentheses instead of brackets. For example: FirstTuple=(“spam”,”spam”,”bacon”,”spam”) SecondTuple=() # The empty tuple LonelyTuple=(5,) # Trailing comma is *required*, since (5) is # just a number-in-parens, not a tuple. Slicing and dicing Lists are ordered, so each list element has an index. You can access an element with the syntax listname[index]. Note that index numbering begins with zero: >>> FoodList=[“Spam”,”Egg”,”Sausage”] >>> FoodList[0] ‘Spam’ >>> FoodList[2] ‘Sausage’ >>> FoodList[2]=”Spam” # Modifying list elements in place >>> FoodList [‘Spam’, ‘Egg’, ‘Spam’] Sometimes it’s easier to count from the end of the list backwards. You can access the last item of a list with listname[-1], the second-to-last item with listname[-2], and so on. You can access a sublist of a list via the syntax listname[start:end]. The sublist contains the original list elements, starting with index start, up to (but not including) index end. Both start and end are optional; omitting them makes Python go all the way to the beginning (or end) of the list. For example: >>>WordList=[“And”,”now”,”for”,”something”,”completely”, “different”] >>> WordList[0:2] # From index 0 to 2 (not including 2) [‘And’, ‘now’] 9 4807-7 ch01.F 10 5/24/01 8:57 AM Page 10 Part I ✦ The Python Language >>> WordList[2:5] [‘for’, ‘something’, ‘completely’] >>> WordList[:-1] # All except the last [‘And’, ‘now’, ‘for’, ‘something’, ‘completely’] Substrings Lists, tuples, and strings are all sequence types. Sequence types all support indexed access. So, taking a substring in Python is easy: >>> Word=”pig” >>> PigLatinWord=Word[1:]+Word[0]+”ay” >>> PigLatinWord ‘igpay’ Immutable types Tuples and strings are immutable types. Modifying them in place is not allowed: FirstTuple[0]=”Egg” # Object does not support item assignment. You can switch between tuples and lists using the tuple and list functions. So, although you cannot edit a tuple directly, you can create a new-and-improved tuple: >>> FoodTuple=(“Spam”,”Egg”,”Sausage”) >>> FoodList=list(FoodTuple) >>> FoodList [‘Spam’, ‘Egg’, ‘Sausage’] >>> FoodList[2]=”Spam” >>> NewFoodTuple=tuple(FoodList) >>> NewFoodTuple (‘Spam’, ‘Egg’, ‘Spam’) Dictionaries A dictionary is a Python object that cross-references keys to values. A key is an immutable object, such as a string. A value can be any object. A dictionary has a canonical string representation: a comma-separated list of key-value pairs, enclosed in curly braces: {key:value, key:value}. For example: >>> PhoneDict={“bob”:”555-1212”,”fred”:”555-3345”} >>> EmptyDict={} # Initialize a new dictionary. >>> PhoneDict[“bob”] # Find bob’s phone number. ‘555-1212’ >>> PhoneDict[“cindy”]=”867-5309” # Add an entry. >>> print “Phone list:”,PhoneDict Phone list: {‘fred’: ‘555-3345’, ‘bob’: ‘555-1212’, ‘cindy’: ‘867-5309’} 4807-7 ch01.F 5/24/01 8:57 AM Page 11 Chapter 1 ✦ Python in an Hour Looking up a value raises an exception if the dictionary holds no value for the key. The function dictionary.get(key,defaultValue) performs a “safe get”; it looks up the value corresponding to key, but if there is no such entry, returns defaultValue. >>> PhoneDict[“luke”] # May raise an exception. Traceback (most recent call last): File “<stdin>”, line 1, in ? KeyError: luke >>> PhoneDict.get(“joe”,”unknown”) ‘unknown’ Often a good default value is the built-in value None. The value None represents nothing (it is a little Zen-like). The value None is similar to NULL in C (or null in Java). It evaluates to false. >>> DialAJoe=PhoneDict.get(“joe”,None) >>> print DialAJoe None Reading and Writing Files To create a file object, use the function open(filename,mode). The mode argument is a string explaining what you intend to do with the file — typical values are “w” to write and “r” to read. Once you have a file object, you can read( ) from it or write( ) to it, then close( ) it. This example creates a simple file on disk: >>> fred = open(“hello”,”w”) >>> fred.write(“Hello world!”) >>> fred.close() >>> barney = open(“hello”,”r”) >>> FileText = barney.read() >>> barney.close() >>> print FileText Hello world! Sample Program: Word Frequencies Different authors use different words. Patterns of word use form a kind of “author fingerprint” that is sometimes used as a test of a document’s authenticity. Listing 1-2 counts occurrences of a word in a body of text, and illustrates some more Python power in the process. (Don’t be intimidated by all the comments — it’s actually only 26 lines of code.) 11 4807-7 ch01.F 12 5/24/01 8:57 AM Page 12 Part I ✦ The Python Language Listing 1-2: WordCount.py # Import the string module, so we can call Python’s standard # string-related functions. import string def CountWords(Text): “Count how many times each word occurs in Text.” # A string immediately after a def statement is a # “docstring” - a comment intended for documentation. WordCount={} # We will build up (and return) a dictionary whose keys # are the words, and whose values are the corresponding # number of occurrences. CurrentWord=”” # To make the job cleaner, add a period at the end of the # text; that way, we are guaranteed to be finished with # the current word when we run out of letters: Text=Text+”.” # We assume that ‘ and - don’t break words, but any other # nonalphabetic character does. This assumption isn’t # entirely accurate, but it’s close enough for us. # string.letters is a string of all alphabetic characters. PiecesOfWords = string.letters + “‘-” # Iterate over each character in the text. The # function len () returns the length of a sequence, # such as a string: for CharacterIndex in range(0,len(Text)): CurrentCharacter=Text[CharacterIndex] # The find() method of a string finds # the starting index of the first occurrence of a # substring within a string, or returns –1 # if it doesn’t find the substring. The next # line of code tests to see whether CurrentCharacter # is part of a word: if (PiecesOfWords.find(CurrentCharacter)!=-1): # Append this letter to the current word. CurrentWord=CurrentWord+CurrentCharacter else: # This character is not a letter. if (CurrentWord!=””): # We just finished off a word. # Convert to lowercase, so “The” and “the” # fall in the same bucket. CurrentWord = string.lower(CurrentWord) # Now increment this word’s count. CurrentCount=WordCount.get(CurrentWord,0) WordCount[CurrentWord]=CurrentCount+1 4807-7 ch01.F 5/24/01 8:57 AM Page 13 Chapter 1 ✦ Python in an Hour # Start a new word. CurrentWord=”” return (WordCount) if (__name__==”__main__”): # Read the text from the file song.txt. TextFile=open(“poem.txt”,”r”) Text=TextFile.read() TextFile.close() # Count the words in the text. WordCount=CountWords(Text) # Alphabetize the word list, and print them all out. SortedWords=WordCount.keys() SortedWords.sort() for Word in SortedWords: print Word,WordCount[Word] Listing 1-3: poem.txt Shall I compare thee to a summer’s day? Thou art more lovely and more temperate: Rough winds do shake the darling buds of May, And summer’s lease hath all too short a date: Sometime too hot the eye of heaven shines And often is his gold complexion dimmed; And every fair from fair sometimes declines, By chance or nature’s changing course untrimmed; But thy eternal summer shall not fade, Nor lose possession of that fair thou ow’st: Nor shall Death brag thou wander’st in his shade, When in eternal lines to time thou grow’st: So long as men can breathe, or eyes can see, So long lives this, and this gives life to thee. Listing 1-4: WordCount output all 1 and 5 art 1 as 1 brag 1 [. . .omitted for brevity. . .] too 2 untrimmed 1 wander’st 1 when 1 winds 1 13 4807-7 ch01.F 14 5/24/01 8:57 AM Page 14 Part I ✦ The Python Language Loading and Using Modules Python comes with a collection of libraries to do all manner of useful things. To use the functions, classes, and variables in another Python module, you must first import that module with the statement import modulename. (Note: No parentheses.) After importing a module, you can access any of its members using the syntax moduleName.itemName. For instance, this line (from the preceding example) calls the function lower in the module string to convert a string to lowercase. CurrentWord = string.lower(CurrentWord) When you import a module, any code at module level (that is, code that isn’t part of a function or class definition) executes. To set aside code to execute only when someone runs your script from the command line, you can enclose it in an if (__name__==”__main__”) block, as in Listing 1-2 above. As an alternative to “import foo,” you can use the syntax from foo import itemName to import a function or variable all the way into the current namespace. For example, after you include the line from math import sqrt in a Python script, you can call the square-root function sqrt directly, instead of calling math.sqrt. You can even bring in everything from a module with from foo import *. However, although this technique does save typing, it can become confusing — especially if you import functions with the same name from several different modules! Note Python does not enforce “privacy” in modules; you can call any of a module’s functions. It is generally a good idea to be polite and only call those you are supposed to. Creating a Class Python is an object-oriented language. In fact, every piece of Python data is an object. Working with objects in Python is easy, as you will soon see. Some quick object jargon A class is a mechanism for tying together data and behavior. An instance of a particular class is called an object. Class instances have certain methods (functions) and attributes (data values). In Python, all data items behave like objects, even though a few base types (like integers) are not actual instances of a class. You can derive a class from a parent class; this relationship is called inheritance. Instances of the child (derived) class have the same attributes and methods of the parent class. The child class may add new methods and attributes, and override methods of the parent. A class may be derived from more than one parent class; this relationship is called multiple inheritance. 4807-7 ch01.F 5/24/01 8:57 AM Page 15 Chapter 1 ✦ Python in an Hour Object-oriented programming (OOP) is a mindset that may take some getting used to. When inheritance becomes natural, and you start talking about your data in anthropomorphic terms, you will know that your journey to the OO side is complete. See the References section for some resources that explain object-oriented programming in detail. Object orientation, Python style You define a new class with the syntax class ClassName. The control block following the class statement is the class declaration; it generally consists of several method definitions. You define a child class (using inheritance) via the syntax class ClassName(ParentClass). You create an object via the syntax NewObject = ClassName(). When you create an object, Python calls its constructor, if any. In Python, a constructor is a member function with the name __init__. A constructor may require extra parameters to create an object. If so, you provide them when creating the object: NewObject = ClassName(param1,param2,...). Every object method takes, as its first parameter, the argument self, which is a reference to the object. (Python self is similar to this in C++/Java, but self is always explicit.) You do not explicitly declare attributes in Python. An object’s attributes are not part of the local namespace — in other words, to access an object’s attribute foo in one of its methods, you must type self.foo. Keep off the grass — Accessing class members Attributes and methods are all “public” — they are visible and available outside the object. However, to preserve encapsulation, many classes have some attributes or methods you should not access directly. The motivation for this is that an object should be something of a “black box” — code outside the object should only care what it does, not how it does it. This helps keep code easy-to-maintain, especially in big programs. Example: the point class Listing 1-5 defines a class representing a point in the plane (or on a computer screen): 15 4807-7 ch01.F 16 5/24/01 8:57 AM Page 16 Part I ✦ The Python Language Listing 1-5: Point.py import math # The next statement starts our class declaration; the # function declarations inside the indented control block are # the class’s methods. class Point: # The method __init__ is the class’s constructor. It # executes when you create an instance of the class. # When __init__ takes extra parameters (as it does here), # you must supply parameter values in order to create an # instance of the class. Writing an __init__ method is # optional. def __init__(self,X,Y): # X and Y are the attributes of this class. You do not # have to declare attributes. I like to initialize # all my attributes in the constructor, to ensure that # the attributes will be available when I need them. self.X=X self.Y=Y def DistanceToPoint(self, OtherPoint): “Returns the distance from this point to another” SumOfSquares = ((self.X-OtherPoint.X)**2) +\ ((self.Y-OtherPoint.Y)**2) return math.sqrt(SumOfSquares) def IsInsideCircle(self, Center, Radius): “””Return 1 if this point is inside the circle, 0 otherwise””” if (self.DistanceToPoint(Center)<Radius): return 1 else: return 0 # This code tests the point class. PointA=Point(3,5) # Create a point with coordinates (3,5) PointB=Point(-4,-4) # How far is it from point A to point B? print “A to B:”,PointA.DistanceToPoint(PointB) # What if I go backwards? print “B to A:”,PointB.DistanceToPoint(PointA) # Who lives inside the circle of radius 5 centered at (3,3)? CircleCenter=Point(3,3) print “A in circle:”,PointA.IsInsideCircle(CircleCenter,5) print “B in circle:”,PointB.IsInsideCircle(CircleCenter,5) 4807-7 ch01.F 5/24/01 8:57 AM Page 17 Chapter 1 ✦ Python in an Hour Recommended Reading If you are new to computer programming, you may find this tutorial useful: http://www.honors.montana.edu/~jjc/easytut/easytut/. To learn all about the language on one (large!) page, see the Python Quick Reference at http://starship.python.net/quick-ref1_52.html. If you like to learn by tinkering with finished programs, you can download a wide variety of source code at the Vaults of Parnassus: http://www.vex.net/ parnassus/. Summary This wraps up our quick tour of Python. We hope you enjoyed the trip. You now know most of Python’s notable features. In this chapter, you: ✦ Ran the Python interpreter for easy interaction. ✦ Grouped statements by indentation level. ✦ Wrote functions to count words in a body of text. ✦ Created a handy Point class. The next chapter digs a little deeper and introduces all of Python’s standard types and operators. ✦ ✦ ✦ 17 4807-7 ch01.F 5/24/01 8:57 AM Page 18 4807-7 ch02.F 5/24/01 8:57 AM Page 19 2 CHAPTER Identifiers, Variables, and Numeric Types O ✦ ✦ ✦ In This Chapter Identifiers and operators Numeric types ne of the simplest forms of data on which your programs operate is numbers. This chapter introduces the numeric data types in Python, such as integers and floating point numbers, and shows you how to use them together in simple operations like assignment to variables. As with Chapter 1, you’ll find it helpful to have a Python interpreter up and running as you read this and the following chapters. Playing around with the examples in each section will pique your curiosity and help keep Python’s features firmly rooted in your brain. Identifiers and Operators Variable names and other identifiers in Python are similar to those in many other languages: they start with a letter (A–Z or a–z) or an underscore (“_”) and are followed by any number of letters, numbers, and underscores. Their length is limited only by your eagerness to type, and they are case-sensitive (that is, spam and Spam are different identifiers). Regardless of length, choose identifiers that are meaningful. (Having said that, I’ll break that rule for the sake of conciseness in many of the examples in this chapter.) The following are some examples of valid and invalid identifiers: wordCount y_axis errorField2 _logFile _2 good idea ✦ # Technically valid, but not a Assigning values to variables ✦ ✦ ✦ ✦ 4807-7 ch02.F 20 5/24/01 8:57 AM Page 20 Part I ✦ The Python Language # Invalid, starts with a number # Invalid due to apostrophe character 7Index won’t_work Note Python considers these forms to have special meaning: _name — Not imported by “from x import *” (see Chapter 6) __name__ — System name (see Chapter 6) __name — Private class member (see Chapter 7) When you’re running the Python interpreter in interactive mode, a single underscore character (_) is a special identifier that holds the result of the last expression evaluated. This is especially handy when you’re using Python as a desktop calculator: >>> “Hello” ‘Hello’ >>> _ ‘Hello’ >>> 5 + 2 7 >>> _ * 2 14 >>> _ + 5 19 >>> Reserved words Although it would make for some interesting source code, you can’t use the following words as identifiers because they are reserved words in the Python language: and assert break class continue def del elif else except exec finally for from global if import in is lambda not or pass print raise return try while Operators Python has the following operators, each of which we’ll discuss in context with the applicable data types they operate on: + != < % << & <= * <> ** == / > ^ >= | >> ~ 4807-7 ch02.F 5/24/01 8:57 AM Page 21 Chapter 2 ✦ Identifiers, Variables, and Numeric Types Numeric Types Python has four built-in numeric data types: integers, long integers, floating point numbers, and imaginary numbers. Integers Integers are whole numbers in the range of -2147483648 to 2147483647 (that is, they are signed, 32-bit numbers). Tip For convenience, the sys module has a maxint member that holds the maximum positive value of an integer variable: >>> import sys >>> sys.maxint 2147483647 In addition to writing integers in the default decimal (base 10) notation, you can also write integer literals in hexadecimal (base 16) and octal (base 8) notation by preceding the number with a 0x or 0, respectively: >>> 300 300 >>> 0x12c 300 >>> 0454 300 # 300 in decimal # 300 in hex # 300 in octal Keep in mind that for decimal numbers, valid digits are 0 through 9. For hexadecimal, it’s 0 through 9 and A through F, and for octal it’s 0 through 7. If you’re not familiar with hexadecimal and octal numbering systems, or if you are but they don’t thrill you, just nod your head and keep moving. Long integers Long integers are similar to integers, except that the maximum and minimum values of long integers are restricted only by how much memory you have (yes, you really can have long integers with thousands of digits). To differentiate between the two types of integers, you append an “L” to the end of long integers: >>> 200L 200L # A long integer literal with a value of 200 >>> 11223344 * 55667788 # Too big for normal integers... Traceback (innermost last): File “<interactive input>”, line 1, in ? OverflowError: integer multiplication >>> 11223344L * 55667788L 624778734443072L # ...but works with long integers 21 4807-7 ch02.F 22 5/24/01 8:57 AM Page 22 Part I ✦ The Python Language Tip The “L” on long integers can be uppercase or lowercase, but do yourself a favor and always use the uppercase version. The lowercase “L” and the one digit look too similar, especially if you are tired, behind schedule on a project, or both. Floating point numbers Floating point numbers let you express fractional numeric values such as 3.14159. You can also include an optional exponent. If you include neither an exponent nor a decimal point, Python interprets the number as an integer, so to express “the floating point number two hundred,” write it as 200.0 and not just 200. Here are a few examples of floating point numbers: 200.05 9.80665 .1 20005e-2 6.0221367E23 Note Occasionally you may notice what appear to be rounding errors in how Python displays floating point numbers: >>> 0.3 0.29999999999999999 Don’t worry; this display is not indicating a bug, but is just a friendly reminder that your digital computer just approximates real world numbers. See “Formatting strings” in Chapter 3 to learn about printing numbers in a less ugly format. The valid values for floating point numbers and the accuracy with which Python uses them is implementation-dependent, although it is at least 64-bit, doubleprecision math and is often IEEE 754 compliant. Imaginary numbers Unlike many other languages, Python has language-level support for imaginary numbers, making it trivial to use them in your programs. You form an imaginary number by appending a “j” to a decimal number (integer or floating point): 3j 2.5e-3j When you add a real and an imaginary number together, Python recognizes the result as a complex number and handles it accordingly: >>> 2 + 5j (2+5j) >>> 2 * (2 + 5j) (4+10j) 4807-7 ch02.F 5/24/01 8:57 AM Page 23 Chapter 2 ✦ Identifiers, Variables, and Numeric Types Manipulating numeric types You can use most of Python’s operators when working with numeric data types. Numeric operators Table 2-1 lists operators and how they behave with numeric types. Table 2-1 Operations on Numeric Types Operator Description Example Input Example Output + Plus +2 2 - Minus -2 2 -(-2) 2 ~5 6 5+7 12 5 + 7.0 12.0 5–2 3 5 – 2.0 3.0 Unary Operations ~ Inversion 1 Binary Operations + - Addition Subtraction * Multiplication 2.5 * 2 5.0 / Division 5/2 2 % Modulo (remainder) 5 / 2.0 0 3 5|2 7 11 | 3 OR ^ 5&2 11 5^2 7 11 ^ 3 8 2 AND | 1.466... 11 & 3 & 25 1.2 ** 2.1 Binary Bitwise Operations 0.0 5 ** 2 Power 1 7.5 % 2.5 ** 2.5 5%2 XOR (exclusive-or) Continued 23 4807-7 ch02.F 24 5/24/01 8:57 AM Page 24 Part I ✦ The Python Language Table 2-1 (continued) Operator Description Example Input Example Output Shifting Operations2 << Left bit-shift 5 << 2 20 >> Right bit-shift 50 >> 3 6 1 Unary bitwise inversion of a number x is defined as –(x+1). 2 Numbers used in binary bitwise and shifting operations must be integers or long integers. It is important to notice what happens when you mix standard numeric types (adding an integer and a floating point number, for example). If needed, Python first coerces (converts) either of the numbers according to these rules (stopping as soon as a rule is satisfied): 1. If one of the numbers is a complex number, convert the other to a complex number too. 2. If one of the numbers is a floating point number, convert the other to floating point. 3. If one of the numbers is a long integer, convert the other to a long integer. 4. No previous rule applies, so both are integers, and Python leaves them unchanged. Other functions Python has a few other built-in functions for working with numeric types, as described in the following sections. Absolute value — abs The abs(x) function takes the absolute value of any integer, long integer, or floating point number: >>> abs(-5.0) 5.0 >>> abs(-20L) 20L When applied to a complex number, this function returns the magnitude of the number, which is the distance from that point to the origin in the complex plane. Python calculates the magnitude just like the length of a line in two dimensions: for a complex number (a + bj), the magnitude is the square root of a squared plus b squared: >>> abs(5 - 2j) 5.3851648071345037 4807-7 ch02.F 5/24/01 8:57 AM Page 25 Chapter 2 ✦ Identifiers, Variables, and Numeric Types Convert two numbers to a common type — coerce(x, y) The coerce function applies the previously explained numeric conversion rules to two numbers and returns them to you as a tuple (we cover tuples in detail in the next chapter): >>> coerce(5,2L) (5L, 2L) >>> coerce(5.5,2L) (5.5, 2.0) >>> coerce(5.5,5 + 2j) ((5.5+0j), (5+2j)) Quotient and remainder — divmod(a, b) This function performs long division on two numbers and returns the quotient and the remainder: >>> divmod(5,2) (2, 1) >>> divmod(5.5,2) (2.0, 1.5) Power — pow(x, y [, z]) The pow function is similar to the power (**) operator in Table 2-1: >>> pow(5,2) 25 >>> pow(1.2,2.1) 1.4664951016517147 As usual, Python coerces the two numbers to a common type if needed. If the resulting type can’t express the correct result, Python yells at you: >>> pow(2.0,-1) # The coerced type is a floating point. 0.5 >>> pow(2,-1) # The coerced type is an integer. Traceback (innermost last): File “<interactive input>”, line 1, in ? ValueError: integer to the negative power An optional third argument to pow specifies the modulo operation to perform on the result: >>> pow(2,5) 32 >>> pow(2,5,10) 2 >>> (2 **5) % 10 2 25 4807-7 ch02.F 26 5/24/01 8:57 AM Page 26 Part I ✦ The Python Language The result is the same as using the power and modulo operators, but Python arrives at the result more efficiently. (Speedy power-and-modulo is useful in some types of cryptography.) Round — round(x [, n]) This function rounds a floating point number x to the nearest whole number. Optionally, you can tell it to round to n digits after the decimal point: >>> round(5.567) 6.0 >>> round(5.567,2) 5.57 CrossReference Chapter 31, “Number Crunching,” covers several Python modules that deal with math and numerical data types. Assigning Values to Variables With basic numeric types out of the way, we can take a break before moving on to other data types, and talk about variables and assignment statements. Python creates variables the first time you use them (you never need to explicitly declare them beforehand), and automatically cleans up the data they reference when they are no longer needed. Refer back to “Identifiers and Operators” at the beginning of this chapter for the rules regarding valid variable names. Simple assignment statements The simplest form of assignment statements in Python are of the form variable = value: >>> >>> >>> 5 >>> 10 >>> 15 >>> 0 CrossReference a=5 b = 10 a b a+b a>b “Understanding References” in Chapter 4 goes into more depth about how and when Python destroys unneeded data, and “Taking Out the Trash” in Chapter 26 covers the Python garbage collector. 4807-7 ch02.F 5/24/01 8:57 AM Page 27 Chapter 2 ✦ Identifiers, Variables, and Numeric Types A Python variable doesn’t actually contain a piece of data but merely references a piece of data. The details and importance of this are covered in Chapter 4, but for now it’s just important to note that the type of data that a variable refers to can change at any time: >>> a = 10 >>> a 10 >>> a = 5.0 + 2j >>> a (5+2j) # First it refers to an integer. # Now it refers to a complex number. Multiple assignment Python provides a great shorthand method of assigning values to multiple variables at the same time: >>> >>> 5.5 >>> 2 >>> 10 a,b,c = 5.5,2,10 a b c You can also use multiple assignment to swap any number of variables. Continuing the previous example: >>> >>> 10 >>> 5.5 >>> 2 CrossReference a,b,c = c,a,b a b c Multiple assignment is really tuple packing and unpacking, covered in Chapter 4. Augmented assignment Another shorthand feature is augmented assignment, which enables you to combine an assignment and a binary operation into a single statement: >>> a = 10 >>> a += 5 >>> a 15 27 4807-7 ch02.F 28 5/24/01 8:57 AM Page 28 Part I ✦ The Python Language New Feature Augmented assignment was introduced in Python 2.0. Python provides these augmented assignment operators: += >>= -= <<= *= &= /= |= %= ^= **= The statement a += 5 is nearly identical to the longer form of a = a + 5 with two exceptions (neither of which you need to worry about too often, but are worth knowing): 1. In augmented assignment, Python evaluates a only once instead of the two times in the longhand version. 2. When possible, augmented assignment modifies the original object instead of creating a new object. In the longhand example above, Python evaluates the expression a + 5, creates a place in memory to hold the result, and then reassigns a to reference the new data. With augmented assignment, however, Python places the result in the original object. Summary Python has several built-in data types and many features to help you work with them. In this chapter you: ✦ Learned the rules for valid Python variable names and other identifiers. ✦ Created variables using integer, floating point, and other numerical data. ✦ Used augmented assignment statements to combine basic operations such as addition with assignment. In the next chapter you discover how to use expressions to compare data and you learn how character strings work in Python. ✦ ✦ ✦ 4807-7 ch03.F 5/24/01 8:57 AM Page 29 3 CHAPTER Expressions and Strings ✦ ✦ ✦ ✦ In This Chapter C haracter strings can hold messages for users to read (a la “Hello, world!”), but in Python they can also hold a sequence of binary data. This chapter covers how you use strings in your programs, and how you can convert between strings, numbers, and other Python data types. Before you leave this chapter, you’ll also have a solid grasp of expressions and how your programs can use them to make decisions and compare data. Expressions Expressions are the core building blocks of decision making in Python and other programming languages, and Python evaluates each expression to see if it is true or false. The most basic form of a Python expression is any value: if the value is nonzero, it is considered to be “true,” and if it equals 0, it is considered to be “false.” CrossReference Chapter 4 goes on to explain that Python also considers any nonempty and non-None objects to be true. More common, however, is the comparison of two or more values with some sort of operator: >>> 12 > 5 # This expression is true. 1 >>> 2 < 1 # This expression is false. 0 Comparing numeric types Python supplies a standard set of operators for comparing numerical data types. Table 3-1 lists these comparison operators with examples. Expressions Strings Converting between simple types ✦ ✦ ✦ ✦ 4807-7 ch03.F 30 5/24/01 8:57 AM Page 30 Part I ✦ The Python Language Table 3-1 Comparison Operators Operator Description Sample Input Sample Output < Less than 10 < 5 0 > Greater than 10 > 5 1 <= Less than or equal 3 <= 5 1 3 <= 3 1 >= Greater than or equal 3 >= 5 0 == Equality 3 == 3 1 3 == 5 0 3 != 5 1 != * Inequality * Python also supports an outdated inequality operator: <>. It may not be supported in the future. Before comparing two numbers, Python applies the usual coercion rules if necessary. A comparison between two complex numbers involves only the real part of each number if they are different. Only if the real parts of both are the same does the comparison depend on the imaginary part: >>> 3 + 10j < 2 + 1000j 0 >>> 3 + 10j < 3 + 1000j 1 Python doesn’t restrict you to just two operands in a comparison; for example, you can use the common a < b < c notation common in mathematics: >>> a,b,c = 10,20,30 >>> a < b < c # True because 10 < 20 and 20 < 30 Note that a < b < c is the same as comparing a < b and then comparing b < c, except that b is evaluated only once (besides being nifty, this could really make a difference if evaluating b required a lot of processing time). Expressions like a < b > c are legal but discouraged, because to the casual observer (for example, you, late at night, searching for a bug in your code) they appear to imply a comparison or relationship between a and c, which is not really the case. Python has three additional functions that you can use when comparing data: 4807-7 ch03.F 5/24/01 8:57 AM Page 31 Chapter 3 ✦ Expressions and Strings min (x[, y,z,...]) The min function takes two or more arguments of any type and returns the smallest: >>> min(10,20.5,5,100L) 5 max (x[, y,z,...]) Similarly, max chooses the largest of the arguments passed in: >>> max(10,20.5,5,100L) 100L Both min and max can accept a sequence as an argument (See Chapter 4 for information on lists and tuples.): >>> Ages=[42,37,26] >>> min(Ages) 26 cmp (x,y) The comparison function takes two arguments and returns a negative number, 0, or a positive number if the first argument is less than, equal to, or greater than the second: >>> cmp(2,5) -1 >>> cmp(5,5.0) 0 >>> cmp(5,2) 1 Do not rely on the values being strictly 1, -1, or 0, especially when calling cmp with other data types (for example, strings). Compound expressions A compound expression combines simple expressions using the Boolean operators and, or, and not. Python treats Boolean operators slightly differently than many other languages do. and When evaluating the expression a and b, Python evaluates a to see if it is false, and if so, the entire expression takes on the value of a. If a is true, Python evaluates b and the entire expression takes on the value of b. There are two important points here. First, the expression does not evaluate to just true or false (0 or 1): 31 4807-7 ch03.F 32 5/24/01 8:57 AM Page 32 Part I ✦ The Python Language >>> >>> 20 >>> >>> 0 a,b = 10,20 a and b # a is true, so evaluate b a,b = 0,5 a and b Second, if a (the first expression) evaluates to false, then Python never bothers to evaluate b (the second expression): >>> 0 and 2/0 0 # Doesn’t cause division by zero error or With the expression a or b, Python evaluates a to see if it is true, and if so, the entire expression takes on the value of a. When a is false, the expression takes on the value of b: >>> >>> 10 >>> >>> 5 a,b = 10,20 a or b a,b = 0,5 a or b Similar to the and operator, the expression takes on the value of either a or b instead of just 0 or 1, and Python evaluates b only if a is false. not Finally, not inverts the “truthfulness” of an expression: if the expression evaluates to true, not returns false, and vice versa: >>> not 5 0 >>> not 0 1 >>> not (0 > 2) 1 Unlike the and and or operators, not always returns a value of 0 or 1. Complex expressions You can form arbitrarily complex expressions by grouping any number of expressions together using parentheses and Boolean operators. For example, if you just can’t seem to remember if a number is one of the first few prime numbers, this expression will bail you out: 4807-7 ch03.F 5/24/01 8:58 AM Page 33 Chapter 3 ✦ Expressions and Strings >>> >>> 1 >>> >>> 1 >>> >>> 0 i=5 (i == 2) or (i % 2 != 0 and 0 < i < 9) i=2 (i == 2) or (i % 2 != 0 and 0 < i < 9) i=4 (i == 2) or (i % 2 != 0 and 0 < i < 9) If the number is 2, the first sub-expression (i == 2) evaluates to true and Python stops processing the expression and returns 1 for true. Otherwise, two remaining conditions must be met for the expression to evaluate to true. The number must not be evenly divisible by 2, and it must be between 0 and 9 (hey, I said the first few primes, remember?). Parentheses let you explicitly control the order of what gets evaluated first. Without parentheses, the order of evaluation may be unclear and different than what you expect (and a great source of bugs): >>> 4 or 1 * 2 4 A well-placed pair of parentheses clears up any ambiguity: >>> (4 or 1) * 2 8 Operator precedence Python uses the ordering in Table 3-2 to guide the evaluation of complex expressions. Expressions using operators higher up in the table get evaluated before those towards the bottom of the table. Operators on the same line of the table have equal priority or precedence. Python evaluates operators with the same precedence from left to right. Table 3-2 Operator Precedence (from lowest to highest) Operators Description x String conversion {key:datum, ...} Dictionary [x,y,...] List (x,y,...) Tuple Continued 33 4807-7 ch03.F 34 5/24/01 8:58 AM Page 34 Part I ✦ The Python Language Table 3-2 (continued) Operators f(x,y,...) Function call x[j:k] Slice x[j] Subscription x.attribute Attribute reference ~x Bitwise negation (inversion) +x, -x Plus, minus ** Power *, /, % Multiply, divide, modulo +, - Add, subtract <<, >> Shifting & Bitwise AND ^ Bitwise XOR | Bitwise OR <, <=, ==, !=, >=, > Comparisons is, is not Identity in, not in Membership not x Boolean NOT and Boolean AND or Boolean OR lambda CrossReference Description Lambda expression See Chapters 4 through 7 for more information on operators and data types such as lists and tuples that we have not yet covered. Strings A string is Python’s data type for holding not only text but also “non-printable” or binary data. If you’ve done much work with strings in languages like C or C++, prepare to be liberated from mundane memory management tasks as well as a plethora of bugs lying in wait. Strings in Python were not added as an afterthought or tacked on via a third party library, but are part of the core language itself, and it shows! 4807-7 ch03.F 5/24/01 8:58 AM Page 35 Chapter 3 ✦ Expressions and Strings String literals A string literal is a sequence of characters enclosed by a matching pair of single or double quotes: “Do you like green eggs and ham?” ‘Amu vian najbaron’ “Tuesday’ # Illegal: quotes do not match. Which of the two you use is more of a personal preference (in some nerdy way I find single-quoted strings more sexy and “cool”), but sometimes the text of the string makes one or the other more convenient: ‘Quoth the Raven, _Nevermore._ ‘ _Monty Python’s Flying Circus_ _Enter your age (I’ll know if you’re lying, so don’t): _ Python automatically joins two or more string literals separated only by whitespace: >>> “one” ‘two’ “three” ‘onetwothree’ A single backslash character inside a string literal lets you break a string across multiple lines: >>> ‘Rubber baby \ ... buggy bumpers’ ‘Rubber baby buggy bumpers’ If your string of text covers several lines and you want Python to preserve the exact formatting you used when typing it in, use triple-quoted strings (the string begins with three single or double quotes and ends with three more of the same type of quote). An example: >>> s = “”””Knock knock.” ... “Who’s there?” ... “Knock knock.” ... “Who’s there?” ... “Knock knock.” ... “Who’s there?” ... “Philip Glass.” ... “”” >>> print s “Knock knock.” “Who’s there?” “Knock knock.” “Who’s there?” “Knock knock.” “Who’s there?” “Philip Glass.” 35 4807-7 ch03.F 36 5/24/01 8:58 AM Page 36 Part I ✦ The Python Language String length Regardless of the quoting method you use, string literals can be of any length. You can use the len(x) function to retrieve the length of a string: >>> len(‘Pokey’) 5 >>> s = ‘Data:\x00\x01’ >>> len(s) 7 Escape sequences You can also use escape sequences to include quotes or other characters inside a string (see Table 3-3): >>> print “\”Never!\” shouted Skeptopotamus.” “Never!” shouted Skeptopotamus. Table 3-3 Escape Sequences Sequence Description \n Newline (ASCII LF) \’ Single quote \” Double quote \\ Backslash \t Tab (ASCII TAB) \b Backspace (ASCII BS) \r Carriage return (ASCII CR) \xhh Character with ASCII value hh in hex \ooo Character with ASCII value ooo in octal \f Form feed (ASCII FF)* \a Bell (ASCII BEL) \v Vertical tab (ASCII VT) * Not all output devices support all ASCII codes. You won’t use \v very often, for example. Table 3-3 lists the valid escape sequences. If you try to use an invalid escape sequence, Python leaves both the backslash and the character after it in the string: >>> print ‘Time \z for foosball!’ Time \z for foosball! 4807-7 ch03.F 5/24/01 8:58 AM Page 37 Chapter 3 ✦ Expressions and Strings As shown in Table 3-3, you can specify the characters of a string using their ASCII value: >>> ‘\x50\x79\x74\x68\x6f\x6e’ ‘Python’ CrossReference See “Converting Between Simple Types” later in this chapter for more on the ASCII codes for characters. The values can be in the range of 0 to 255 (the values that a single byte can have). Remember: a string in Python doesn’t have to be printable text. A string could hold the raw data of an image file, a binary message received over a network, or anything else. Raw strings One final way to specify string literals is with raw strings, in which backslashes can still be used as escape characters, but Python leaves them in the string. You flag a string as a raw string with an r prefix. For example, on Windows systems the path separator character is a backslash, so to use it in a string you’d normally have to type ‘\\’ (the escape sequence for the backslash). Alternatively, you could use a raw string: >>> s = r”c:\games\half-life\hl.exe” >>> s ‘c:\\games\\half-life\\hl.exe’ >>> print s c:\games\half-life\hl.exe CrossReference The os.path module provides easy, cross-platform path manipulation. See Chapter 10 for details. Manipulating strings You can use the plus and multiply operators to build strings. The plus operator concatenates strings together: >>> a = ‘ha ‘ >>> a + a + a ‘ha ha ha ‘ The multiply operator repeats a string: >>> ‘=’ * 10 ‘==========’ 37 4807-7 ch03.F 38 5/24/01 8:58 AM Page 38 Part I ✦ The Python Language Note that operator precedence rules apply, as always: >>> ‘Wh’ + ‘e’ * 10 +’!’ ‘Wheeeeeeeeee!’ Augmented assignment works as well: >>> >>> >>> ‘Ah >>> >>> ‘Ah a = ‘Ah’ a += ‘ Hah! ‘ a Hah! ‘ a *= 2 a Hah! Ah Hah! ‘ Accessing individual characters and substrings Because strings are sequences of characters, you can use on them the same operators that are common to all of Python’s sequence types, among them, subscription and slice. CrossReference See Chapter 4 for a discussion of Python sequence types. Subscription lets you use an index number to retrieve a single character from a Python string, with 0 being the first character: >>> s = ‘Python’ >>> s[1] ‘y’ Additionally, you can reference characters from the end of the string using negative numbers. An index of -1 means the last character, -2 the next to last, and so on: >>> ‘Hello’[-1] ‘o’ >>> ‘Hello’[-5] ‘H’ Python strings are immutable, which means you can’t directly change them or individual characters (you can, of course, assign the same variable to a new string): >>> s = ‘Bad’ >>> s[2] = ‘c’ # Can’t modify the string value Traceback (innermost last): File “<interactive input>”, line 1, in ? TypeError: object doesn’t support item assignment >>> s = ‘Good’ # Can reassign the variable 4807-7 ch03.F 5/24/01 8:58 AM Page 39 Chapter 3 ✦ Expressions and Strings Strings Are Objects Python strings are actually objects with many built-in methods: >>> s = ‘Dyn-o-mite!’ >>> s.upper() ‘DYN-O-MITE!’ >>> ‘ text ‘.strip() ‘text’ Refer to Chapter 9 for a discussion of all the String methods and how to use them. Slicing is similar to subscription except that with it you can retrieve entire substrings instead of single characters. The operator takes two arguments for the lower and upper bounds of the slice: >>> ‘Monty’[2:4] ‘nt’ It’s important to understand that the bounds are not referring to character indices (as with subscription), but really refer to the spots between characters: Monty |||||| 012345 So the slice of 2:4 is like telling Python, “Give me everything from the right of 2 and to the left of 4,” which is the substring “nt”. The lower and upper bounds of a slice are optional. If omitted, Python sticks in the beginning or ending bound of the string for you: >>> s = ‘Monty’ >>> s[:2] ‘Mo’ >>> s[2:] ‘nty’ >>> s[:] ‘Monty’ Don’t forget: Python doesn’t care if you use negative numbers as bounds for the offset from the end of the string. Continuing the previous example: >>> s[1:-1] ‘ont’ >>> s[-3:-1] ‘nt’ 39 4807-7 ch03.F 40 5/24/01 8:58 AM Page 40 Part I ✦ The Python Language You can also access each character via tuple unpacking. This feature isn’t used as often because you have to use exactly the same number of variables as characters in the string: >>> a,b,c = ‘YES’ >>> print a, b, c YES Python does not have a separate ‘character’ data type; a character is just a string of length 1. Note Formatting strings The modulo operator (%) has special behavior when used with strings. You can use it like the C printf function for formatting data: >>> “It’s %d past %d, %s!” % (7,9,”Fred”) “It’s 7 past 9, Fred!” Python scans the string for conversion specifiers and replaces them with values from the list you supply. Table 3-4 lists the different characters you can use in a conversion and what they do; those in bold are more commonly useful. Table 3-4 String Formatting Characters Character Description d or I Decimal (base 10) integer f Floating point number s String or any object c Single character u Unsigned decimal integer X or x Hexadecimal integer (upper or lower case) o Octal integer e or E Floating point number in exponential form g or G Like %f unless exponent < -4 or greater than the precision. If so, acts like %e or %E r repr() version of the object* % Use %% to print the percentage character. * %s prints the str( ) version, %r prints the repr( ) version. See “Converting Between Simple Types” in this chapter. 4807-7 ch03.F 5/24/01 8:58 AM Page 41 Chapter 3 ✦ Expressions and Strings Here are a few more examples: >>> ‘%x %X’ % (57005,48879) ‘dead BEEF’ >>> pi = 3.14159 >>> ‘%f %E %G’ % (pi,pi,pi) ‘3.141590 3.141590E+000 3.14159’ >>> print ‘%s %r’ % (‘Hello’,’Hello’) Hello ‘Hello’ Beyond these features, Python has several other options, some of which are holdovers from C. Between the % character and the conversion character you choose, you can have any combination of the following (in this order): Key name Instead of a tuple, you can provide a dictionary of values to use (dictionaries are covered in Chapter 4). Place the key names (enclosed in parentheses) between the percent sign and the type code in the format string. This one is best explained with an example (although fans of Mad-Libs will be at home): >>> d = {‘name’:’Sam’, ‘num’:32, ‘amt’:10.12} >>> ‘%(name)s is %(num)d years old. %(name)s has $%(amt).2f’ % d ‘Sam is 32 years old. Sam has$10.12’ - or 0 A minus indicates that numbers should be left justified, and a 0 tells Python to pad the number with leading zeros. (This won’t have much effect unless used with the minimum field modifier, explained below.) + A plus indicates that the number should always display its sign, even if the number is positive: >>> ‘%+d %+d’ % (5,-5) ‘+5 -5’ Minimum field width number A number indicates the minimum field this value should take up. If printing the value takes up less space, Python adds padding (either spaces or zeros, see above) to make up the difference: >>> ‘%5d’ % 2 # Don’t need () if there’s only one value ‘ 2’ >>> ‘%-5d, %05d’ % (2,2) ‘2 , 00002’ 41 4807-7 ch03.F 42 5/24/01 8:58 AM Page 42 Part I ✦ The Python Language Additional precision-ish number This final number is a period character followed by a number. For a string, the number is the maximum number of characters to print. For a floating-point number, it’s the number of digits to print after the decimal point, and for integers it’s the minimum number of digits to print. Got all that? >>> ‘%.3s’ % ‘Python’ ‘Pyt’ >>> ‘%05.3f’ % 3.5 ‘3.500’ >>> ‘%-8.5d’ % 10 ‘00010 ‘ Last but not least, you can use an asterisk in place of any number in a width field. If you supply an asterisk, you also provide a list of values (instead of a single number). Python looks in the list of values for that width value: >>> ‘%*.*f’ % (6,3,1.41421356) ‘ 1.414’ Comparing strings String comparison works much the same way numeric comparison does by using the standard comparison operators (<, <=, !=, ==, >=, >). The comparison is lexicographic (‘A’ < ‘B’) and case-sensitive: >>> ‘Fortran’ > ‘Pascal’ 0 >>> ‘Perl’ < ‘Python’ 1 For a string in an expression, Python evaluates any nonempty string to true, and an empty string to false: >>> ‘OK’ and 5 5 >>> not ‘fun’ 0 >>> not ‘’ 1 This behavior provides a useful idiom for using a default value if a string is empty. For example, suppose that the variable s in the following example came from user input instead of you supplying the value. If the user chose something, name holds its value; otherwise name holds the default value of ‘index.html’. >>> s = ‘’; name = s or ‘index.html’ >>> name ‘index.html’ 4807-7 ch03.F 5/24/01 8:58 AM Page 43 Chapter 3 ✦ Expressions and Strings >>> s = ‘page.html’; name = s or ‘index.html’ >>> name ‘page.html’ You can use the min, max, and cmp functions on strings: >>> min(‘abstract’) # Find the least character in the string. ‘a’ >>> max(‘i’,’love’,’spam’) # Find the greatest string. ‘spam’ >>> cmp(‘Vader’,’Maul’) # Vader is greater. 9 Strings (and other sequence types) also have the in (and not in) operator, which tests if a character is a member of a string: >>> ‘u’ in ‘there?’ 0 >>> ‘i’ not in ‘teamwork’ # Cheesy 1 CrossReference Chapter 9 covers advanced string searching and matching with regular expressions. Unicode string literals Many computer languages limit characters in a string to values in the range of 0 to 255 because they store each one as a single byte, making nearly impossible the support of non-ASCII characters used by so many other languages besides plain old English. Unicode characters are 16-bit values (0 to 65535) and can therefore handle just about any character set imaginable. Full support for Unicode strings was a new addition in Python 2.0. New Feature You can specify a Unicode literal string by prefixing a string with a u: >>> u’Rang’ u’Rang’ CrossReference See Chapter 9 for more on using Unicode strings. Converting Between Simple Types Python provides many functions for converting between numerical and string data types in addition to the string formatting feature in the previous section. 43 4807-7 ch03.F 44 5/24/01 8:58 AM Page 44 Part I ✦ The Python Language Converting to numerical types The int, long, float, complex, and ord functions convert data to numerical types. int (x[, radix]) This function uses a string and an optional base to convert a number or string to an integer: >>> int(‘15’) 15 >>> int(‘15’,16) # In hexadecimal, sixteen is written “10” 21 The string it converts from must be a valid integer (trying to convert the string 3.5 would fail). Alternatively, the int function can convert other numbers to integers: >>> int(3.5) 3 >>> int(10L) 10 The int function drops the fractional part of a number. To find the “closest” integer, use the round function (below). long (x[, radix]) The long function can convert a string or another number to a long integer (you can also include a base): >>> long(‘125’) 125L >>> long(17.6) 17L >>> long(‘1E’,16) 30L float (x) You should be seeing a pattern by now: >>> float(12.1) 12.1 >>> float(10L) 10.0 >>> int(float(“3.5”)) # int(“3.5”) is illegal. 3 The exception is with complex numbers; use the abs function to “convert” a complex number to a floating-point number. 4807-7 ch03.F 5/24/01 8:58 AM Page 45 Chapter 3 ✦ Expressions and Strings round (num[, digits]) This function rounds a floating point number to a number having the specified number of fractional digits. If you omit the digits argument, the result is a whole number: >>> round(123.5678,3) 123.568 >>> round(123.5678) 124.0 >>> round(123.4) 123.0 complex (real[, imaginary]) The complex function can convert a string or number to a complex number, and it also takes an optional imaginary part to use if none is supplied: >>> complex(‘2+5j’) (2+5j) >>> complex(‘2’) (2+0j) >>> complex(6L,3) (6+3j) ord (ch) This function takes a single character (a string of length 1) as its argument and returns the ASCII or Unicode value for that character: >>> ord(u’a’) 97 >>> ord(‘b’) 98 Converting to strings Going the other direction, the following functions take numbers and make them into strings. chr (x) and unichr (x) Inverses of the ord function, these functions take a number representing an ASCII or Unicode value and convert it to a character: >>> chr(98) ‘b’ 45 4807-7 ch03.F 46 5/24/01 8:58 AM Page 46 Part I ✦ The Python Language oct (x) and hex (x) These two functions take numbers and convert them to octal and hexadecimal string representations: >>> oct(123) ‘0173’ >>> hex(123) ‘0x7b’ str (obj) The str function takes any object and returns a printable string version of that object: >>> str(5) ‘5’ >>> str(5.5) ‘5.5’ >>> str(3+2j) ‘(3+2j)’ Python calls this function when you use the print statement. repr (obj) The repr function is similar to str except that it tries to return a string version of the object that is valid Python syntax. For simple data types, the outputs of str and repr are often identical. (See Chapter 9 for details.) A popular shorthand for this function is to surround the object to convert in back ticks (above the Tab key on most PC keyboards): >>> a = 5 >>> ‘Give me ‘ + a # Can’t add a string and an integer! Traceback (innermost last): File “<interactive input>”, line 1, in ? TypeError: cannot add type “int” to string >>> ‘Give me ‘ + a # Convert to a string on-the-fly. ‘Give me 5’ New Feature As of Python 2.1, str and repr display newlines and other escape sequences the same way you type them (instead of displaying their ASCII code): >>> ‘Hello\nWorld’ ‘Hello\nWorld’ When you use the Python interpreter interactively, Python calls repr to display objects. You can have it use a different function by setting the value of sys. displayhook: 4807-7 ch03.F 5/24/01 8:58 AM Page 47 Chapter 3 ✦ Expressions and Strings >>> 5.3 5.2999999999999998 # The standard representation is ugly. >>> def printstr(s): ... print str(s) >>> import sys >>> sys.displayhook = printstr >>> 5.3 5.3 # A more human-friendly format New Feature The sys.displayhook feature is new in Python 2.1. Summary Python has a complete set of operators for building expressions as complex as you need. Python’s built-in string data type offers powerful but convenient control over text and binary strings, freeing you from many maintenance tasks you’d be stuck with in other programming languages. In this chapter you: ✦ Built string literals and formatted data in strings. ✦ Used Python’s operators to modify and compare data. ✦ Learned to convert between various data types and strings. In the next chapter you’ll unleash the power of Python’s other built-in data types including lists, tuples, and dictionaries. ✦ ✦ ✦ 47 4807-7 ch03.F 5/24/01 8:58 AM Page 48 4807-7 ch04.F 5/24/01 8:58 AM Page 49 4 CHAPTER Advanced Data Types ✦ ✦ ✦ ✦ In This Chapter T he simple data types in the last few chapters are common to many programming languages, although often not so easily managed and out-of-the-box powerful. The data types in this chapter, however, set Python apart from languages such as C, C++, or even Java, because they are built-in, intuitive and easy to use, and incredibly powerful. Grouping Data with Sequences Strings, lists, and tuples are Python’s built-in sequence data types. Each sequence type represents an ordered set of data elements. Unlike strings, where each piece of data is a single character, the elements that make up a list or a tuple can be anything, including other lists, tuples, strings, and so on. Though much of this section applies to strings, the focus here is on lists and tuples. Grouping data with sequences Working with sequences Using additional list object features Mapping information with dictionaries Understanding references Copying complex objects Identifying data types CrossReference Go directly to Chapter 3 to learn more about strings. Do not pass Go. The main difference between lists and tuples is one of mutability: you can change, add, or remove items of a list, but you cannot change a tuple. Beyond this, though, you will find a conceptual difference on where you apply each. Youd use a list as an array to hold the lines of text from a file, for example, and a tuple to represent a 3-D point in space (x,y,z). Put another way, lists are great for dealing with many items that you’d process similarly, while a tuple often represents different parts of a single item. (Don’t worry — when you go to use either in a program it becomes pretty obvious which one you need.) Working with array objects ✦ ✦ ✦ ✦ 4807-7 ch04.F 50 5/24/01 8:58 AM Page 50 Part I ✦ The Python Language Creating lists Creating a list is straightforward because you don’t need to specify a particular data type or length. You can surround any piece of data in square brackets to create a list containing that data: >>> x = # An empty list >>> y = [‘Strawberry’,’Peach’] >>> z = [10,’Howdy’,y] # Mixed types and a list within a list >>> z [10, ‘Howdy’, [‘Strawberry’, ‘Peach’]] You can call the list(seq) function to convert from one sequence type to a list: >>> list((5,10)) # A tuple [5, 10] >>> list(“The World”) [‘T’, ‘h’, ‘e’, ‘ ‘, ‘W’, ‘o’, ‘r’, ‘l’, ‘d’] If you call list on an object that is already a list, you get a copy of the original list back. CrossReference See “Copying Complex Objects” in this chapter for more on copying objects. Ranges You use the range([lower,] stop[, step]) function to generate a list whose members are some ordered progression of integers. Instead of idling away your time typing in the numbers from 0 to 10, you can do the same with a call to range: >>> range(10) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] # 10 items, starting at 0 You can also call the function with start and stop indices, and even a step to tell it how quickly to jump to the next item: >>> range(6,12) [6, 7, 8, 9, 10, 11] # Stops just before the stop index. >>> range (2,20,3) [2, 5, 8, 11, 14, 17] >>> range (20,2,-3) # Going down! [20, 17, 14, 11, 8, 5] You most commonly use the range function in looping (which we cover in the next chapter): >>> for i in range(10): ... print i, 0123456789 4807-7 ch04.F 5/24/01 8:58 AM Page 51 Chapter 4 ✦ Advanced Data Types The xrange ([lower,] stop[, step]) function is similar to range except that instead of creating a list, it returns an xrange object that behaves like a list but doesn’t calculate each list value until needed. This feature has the potential to save memory if the range is very large or to improve performance if you aren’t likely to iterate through every single member of the equivalent list. List comprehensions One final way to create a list is through list comprehensions, which are great if you want to operate on each item in a list and store the result in a new list, or if you want to create a list that contains only items that meet certain criteria. For example, to generate a list containing x2 for the numbers 1 through 10: >>> [x*x for x in range(1,11)] [1, 4, 9, 16, 25, 36, 49, 64, 81, 100] New Feature List comprehensions are new in Python 2.0. Python uses the range(1,11) to generate a list containing the numbers 1 through 10. Then, for each number in that list, it evaluates the expression x*x and adds the result to the output list. You can add an if to the list comprehension so that items get added to the new list only if they pass some test. For example, to generate the same list as above while weeding out odd numbers: >>> [x*x for x in range(10) if x % 2 == 0] [0, 4, 16, 36, 64] But wait, there’s more! You can list more than one for statement and Python evaluates each in order, processing the rest of the list comprehension each time: >>> [a+b for a in ‘ABC’ for b in ‘123’] [‘A1’, ‘A2’, ‘A3’, ‘B1’, ‘B2’, ‘B3’, ‘C1’, ‘C2’, ‘C3’] Python loops through each character of ‘ABC’ and for each one goes through the entire loop of each character in ‘123’. See where this is going? You can have as many for statements as you want, and each one can have an if statement (but if you think you need five or six then you might want to break them into separate statements for sanity’s sake): >>> [a+b+c for a in “HI” for b in “JOE” if b != ‘E’ ... for c in ‘123’ if c!= ‘2’] [‘HJ1’, ‘HJ3’, ‘HO1’, ‘HO3’, ‘IJ1’, ‘IJ3’, ‘IO1’, ‘IO3’] 51 4807-7 ch04.F 52 5/24/01 8:58 AM Page 52 Part I ✦ The Python Language Finally, the expression that Python evaluates to generate each item in the new list doesn’t have to be a simple data type such as an integer. You can also have it be lists, tuples, and so forth: >>> [(x,ord(x)) for x in ‘Ouch’] [(‘O’, 79), (‘u’, 117), (‘c’, 99), (‘h’, 104)] Creating tuples Creating a tuple is similar to creating a list, except that you use parentheses instead of square brackets: >>> x = () # Any empty tuple >>> y = 22407,’Fredericksburg’ # ()’s are optional >>> z = (‘Mrs. White’,’Ballroom’,’Candlestick’) Parentheses can also enclose any expression, so Python has a special syntax to designate a tuple with only one item. To create a tuple containing the string ‘lonely’: >>> x = (‘lonely’,) Use the tuple(seq) function to convert one of the other sequence types to a tuple: >>> tuple(‘tuple’) (‘t’, ‘u’, ‘p’, ‘l’, ‘e’) >>> tuple([1,2,3]) (1, 2, 3) Working with Sequences Now that you have your list or tuple, what do you do with it? This section shows you the operators and functions you can use to work on sequence data. Joining and repeating with arithmetic operators Of the arithmetic operators, Python defines addition and multiplication for working with sequences. As with strings, the addition operator concatenates sequences and the multiplication operator repeats them: >>> [1,2] + [5] + [‘EGBDF’] [1, 2, 5, ‘EGBDF’] >>> (‘FACEG’,) + (17,88) (‘FACEG’, 17, 88) >>> (1,3+4j) * 2 (1, (3+4j), 1, (3+4j)) 4807-7 ch04.F 5/24/01 8:58 AM Page 53 Chapter 4 ✦ Advanced Data Types The augmented assignment version of these operators works as well (although for strings and tuples Python doesn’t perform the operation in place but instead creates a new object): >>> z = [‘bow’,’arrow’] >>> z *= 2 >>> z [‘bow’, ‘arrow’, ‘bow’, ‘arrow’] >>> q = (1,2) >>> q += (3,4) >>> q (1, 2, 3, 4) Comparing and membership testing You can use the normal comparison (<, <=, >=, >) and equality (!=, ==) operators with sequence objects: >>> [‘five’,’two’] != [5,2] 1 >>> (0.5,2) < (0.5,1) 0 Python checks the corresponding element of each sequence until it can make a determination. When the items in two sequence objects are equal except that one has more items than the other, the longer is considered greater: >>> [1,2,3] > [1,2] 1 You can use the in operator to test if something is in a list or tuple, and not in to test if it is not: >>> trouble = (‘Dan’,’Joe’,’Bob’) >>> ‘Bob’ in trouble 1 >>> ‘Dave’ not in trouble 1 Accessing parts of sequences When you need to retrieve data from a sequence object, you have several alternatives. Subscription When you want to access a single element of a sequence object, you use the subscript or index of the element you want to reference, with the first element having an index of zero (For some reason I get strange looks when I say, “Back to square zero!”): 53 4807-7 ch04.F 54 5/24/01 8:58 AM Page 54 Part I ✦ The Python Language >>> num = [‘dek’,’dudek’,’tridek’] >>> num[1] ‘dudek’ >>> num[-1] # A negative index starts from the other end. ‘tridek’ Slices Slices let you create a new sequence containing all or part of another sequence. You specify a slice in the form of [start:end] and for each element Python adds that element to the new sequence if its index i is start <= i < end. Conceptually, thinking of the slice parameters as pointing between items in a sequence is helpful. Tip >>> meses = [‘marzo’,’abril’,’mayo’,’junio’] >>> meses[1:3] [‘abril’, ‘mayo’] >>> meses[0:-2] # Parameters can count from the right, too. [‘marzo’, ‘abril’] The start and end parameters are both optional, and Python silently corrects invalid input: >>> meses[2:] [‘mayo’, ‘junio’] >>> meses[:2] [‘marzo’, ‘abril’] >>> meses[-2:5000] [‘mayo’, ‘junio’] CrossReference See “Accessing individual characters and substrings” in Chapter 3 for more examples of using slices. Unpacking Just as you can create a tuple by assigning a comma-separated list of items to a single variable, you can unpack a sequence object (not just tuples!) by doing the opposite: >>> >>> >>> 801 s = 801,435,804 x,y,z = s print x,y,z 435 804 Keep in mind that the number of variables on the left must match the length of the sequence you’re unpacking on the right. Note Multiple assignment (in Chapter 3) is really just a special case of tuple packing and unpacking: you pack the objects into a single tuple and then unpack them into the same number of original variables. 4807-7 ch04.F 5/24/01 8:58 AM Page 55 Chapter 4 ✦ Advanced Data Types Iterating with for...in A common task is to loop over all the elements of a list or tuple and operate on each one. One of the easiest ways to do this is with a for...in statement: >>> for op in [‘sin’,’cos’,’tan’]: ... print op sin cos tan Using sequence utility functions Python provides a rich complement of sequence processing functions. len (x), min (x[, y,z,...]), and max (x[, y,z,...]) These three aren’t really specific to sequences, but they’re quite useful nonetheless: >>> >>> 5 >>> -5 >>> 18 data = [0.5, 12, 18, 2, -5] len(data) # Count of items in the sequence min(data) # The minimum item in the sequence max(data) # The maximum item in the sequence filter (function, list) When you call filter it applies a function to each item in a sequence, and returns all items for which the function returns true, thus filtering out all items for which the function returns false. In the following example I create a tiny function, nukeBad, that returns false if the string passed in contains the word ‘bad’. Combining filter with nukeBad eliminates all those ‘bad’ words: >>> def nukeBad(s): ... return s.find(‘bad’) == -1 >>> s = [‘bad’,’good’,’Sinbad’,’bade’,’welcome’] >>> filter(nukeBad,s) [‘good’, ‘welcome’] If you pass in None for the function argument, filter removes any 0 or empty items from the list: >>> stuff = [12,0,’Hey’,,’’,[1,2]] >>> filter(None,stuff) [12, ‘Hey’, [1, 2]] The filter function returns the same sequence type as the one you passed in. The example below removes any number characters from a string and returns a new string: 55 4807-7 ch04.F 56 5/24/01 8:58 AM Page 56 Part I ✦ The Python Language >>> filter(lambda d:not d.isdigit(),”P6yth12on”) ‘Python’ CrossReference See Chapter 6 for more information on lambda expressions. map (function, list[, list, ...]) The map function takes a function and a sequence and returns to you the result of applying the function to each item in the original sequence. Regardless of the type of sequence you pass in, map always returns a list: >>> import string >>> s = [‘chile’,’canada’,’mexico’] >>> map(string.capitalize,s) [‘Chile’, ‘Canada’, ‘Mexico’] You can pass in several multiple lists, too, as long as the function you supply takes the same number of arguments as the number of lists you pass in: >>> import operator >>> s = [2,3,4,5]; t = [5,6,7,8] >>> map(operator.mul,s,t) # s[j] * t[j] [10, 18, 28, 40] CrossReference Chapter 7 covers the operator class, which contains function versions of the standard operators so you can pass them into functions like map. If the lists you use are of different lengths, map uses empty (None) items to make up the difference. Also, if you pass in None instead of a function, map combines the corresponding elements from each sequence and returns them as tuples (compare this to the behavior of the zip function, later in this section): >>> a = [1,2,3]; b = [4,5,6]; c = [7,8,9] >>> map(None,a,b,c) [(1, 4, 7), (2, 5, 8), (3, 6, 9)] reduce (function, seq[, init]) This function takes the first two items in the sequence you pass in, passes them to the function you supply, takes the result and the next item in the list, passes them to the function, and so on until it has processed all the items: >>> import operator >>> reduce(operator.mul,[2,3,4,5]) 120 # 120 = ((2*3)*4)*5 An optional third parameter is an initializer reduce uses in the very first calculation, or when the list is empty. The following example starts with the string “-” and adds each character of a word to the beginning and end of the string (because strings are sequences, reduce calls the function once for each letter in the string): 4807-7 ch04.F 5/24/01 8:58 AM Page 57 Chapter 4 ✦ Advanced Data Types >>> reduce(lambda x,y: y+x+y, “Hello”, “-”) ‘olleH-Hello’ zip (seq[, seq, ...]) The zip function combines corresponding items from two or more sequences and returns them as a list of tuples, stopping after it has processed all the items in the shortest sequence: >>> zip([1,1,2,3,5],[8,13,21]) [(1, 8), (1, 13), (2, 21)] You may find the zip function convenient when you want to iterate over several lists in parallel: >>> names = [‘Joe’,’Fred’,’Sam’] >>> exts = [116,120,100] >>> ages = [26,34,28] >>> for name,ext,age in zip(names,exts,ages): ... print ‘%s (extension %d) is %d’ % (name,ext,age) Joe (extension 116) is 26 Fred (extension 120) is 34 Sam (extension 100) is 28 Passing in just one sequence to zip returns each item as a 1-tuple: >>> zip((1,2,3,4)) [(1,), (2,), (3,), (4,)] New Feature The zip function was introduced in Python 2.0. Using Additional List Object Features List objects have several methods that further facilitate their use, and because they are mutable they support a few extra operations. Additional operations You can replace the value of any item with an assignment statement: >>> todo = [‘dishes’,’garbage’,’sweep’,’mow lawn’,’dust’] >>> todo[1] = ‘boogie’ >>> todo [‘dishes’, ‘boogie’, ‘sweep’, ‘mow lawn’, ‘dust’] What gets replaced in the list doesn’t need to be limited to a single item. You can choose to replace an entire slice with a new list: 57 4807-7 ch04.F 58 5/24/01 8:58 AM Page 58 Part I ✦ The Python Language >>> todo[1:3] = [‘nap’] # Replace from 1 to before 3 >>> todo [‘dishes’, ‘nap’, ‘mow lawn’, ‘dust’] >>> todo[2:] = [‘eat’,’drink’,’be merry’] >>> todo [‘dishes’, ‘nap’, ‘eat’, ‘drink’, ‘be merry’] And finally, you can delete items or slices using del: >>> del >>> z [‘nap’, >>> del >>> z [‘nap’, z[0] ‘eat’, ‘drink’, ‘be merry’] z[1:3] ‘be merry’] List object methods The following methods are available on all list objects. append (obj) and extend (obj) The append method adds an item to the end of a list like the += operator (Python modifies the original list in place) except that the item you pass to append is not a list. The extend method assumes the argument you pass it is a list: >>> z = [‘Nevada’,’Virginia’] >>> z.append(‘Utah’) >>> z [‘Nevada’, ‘Virginia’, ‘Utah’] >>> z.extend([‘North Carolina’,’Georgia’]) >>> z [‘Nevada’, ‘Virginia’, ‘Utah’, ‘North Carolina’, ‘Georgia’] index (obj) This method returns the index of the first matching item in the list, if present, and raises the ValueError exception if not. Continuing the previous example: >>> 1 >>> ... NOT CrossReference x.index(12) try: print x.index(‘Farmer’) except ValueError: print ‘NOT ON LIST!’ ON LIST! See the next chapter for information on try...exception blocks. count (obj) You use the count method to find out how many items in the list match the one you pass in: 4807-7 ch04.F 5/24/01 8:58 AM Page 59 Chapter 4 ✦ Advanced Data Types >>> x = [15,12,’Foo’,16,12] >>> x.count(12) 2 CrossReference String objects also have count and index methods. See Chapter 9 for details. insert (j, obj) Use the insert method to add a new item anywhere in the list. Pass in the index of the item you want the new one to come before and the item to insert: >>> months = [‘March’,’May’,’June’] >>> months.insert(1,’April’) >>> months [‘March’, ‘April’, ‘May’, ‘June’] Notice that insert is pretty forgiving if you pass in a bogus index: >>> months.insert(-1,’February’) # Item added at start >>> months.insert(5000,’July’) # Item added at end >>> months [‘February’, ‘March’, ‘April’, ‘May’, ‘June’, ‘July’] remove (obj) This function locates the first occurrence of an item in the list and removes it, if present, and yells at you if not: >>> months.remove(‘March’) >>> months [‘February’, ‘February’, ‘April’, ‘May’, ‘June’, ‘July’] >>> months.remove(‘August’) Traceback (innermost last): File “<interactive input>”, line 1, in ? ValueError: list.remove(x): x not in list pop([j]) If you specify an index, pop removes the item from that place in the list and returns it. Without an index, the pop function removes and returns the last item from the list: >>> saludos = [‘Hasta!’,’Ciao’,’Nos vemos’] >>> saludos.pop(1) ‘Ciao’ >>> saludos [‘Hasta!’, ‘Nos vemos’] >>> saludos.pop() ‘Nos vemos’ 59 4807-7 ch04.F 60 5/24/01 8:58 AM Page 60 Part I ✦ The Python Language Calling pop on an empty list causes it to raise IndexError. reverse( ) As named, the reverse function reverses the order of the list: >>> names = [‘Jacob’,’Hannah’,’Rachael’,’Jennie’] >>> names.reverse() >>> names [‘Jennie’, ‘Rachael’, ‘Hannah’, ‘Jacob’] sort([func]) This function orders the items in a list. Continuing the previous example: >>> names.sort() >>> names [‘Hannah’, ‘Jacob’, ‘Jennie’, ‘Rachael’] Additionally, you can provide your own comparison function to use during the sort. This function accepts two arguments and returns a negative number, 0, or a positive number if the first argument is less than, equal to, or greater than the second. For example, to order a list by length of each item: >>> names.sort(lambda a,b:len(a)-len(b)) # Ch 5 covers lambdas. >>> names [‘Jacob’, ‘Hannah’, ‘Jennie’, ‘Rachael’] Tip If you want to add and remove items to a sorted list, use the bisect module. When you insert an item using the insort(list, item) function, it uses a bisection algorithm to inexpensively find the correct place to insert the item so that the resulting list remains sorted. The bisect(list, item) function in the same module finds the correct insertion point without actually adding the item to the list. Mapping Information with Dictionaries A dictionary contains a set of mappings between unique keys and their values; they are Python’s only built-in mapping data type. The examples in this section use the following dictionary that maps login user names and passwords to Web site names (who can ever keep track of them all?): >>> logins = {‘yahoo’:(‘john’,’jyahooohn’), ... ‘hotmail’:(‘jrf5’,’18thStreet’)} >>> logins[‘hotmail’] # What’s my name/password for hotmail? (‘jrf5’, ‘18thStreet’) 4807-7 ch04.F 5/24/01 8:58 AM Page 61 Chapter 4 ✦ Advanced Data Types Creating and adding to dictionaries You create a dictionary by listing zero or more key-value pairs within curly braces. The keys used in a dictionary must be unique and immutable, so strings, numbers, and tuples with immutable items in them can all be used as keys. The values in the key-value pair can be anything, even other dictionaries if you want. Adding or replacing mappings is easy: >>> logins[‘slashdot’] = (‘juan’,’lemmein’) Accessing and updating dictionary mappings If you try to use a key that doesn’t exist in the dictionary, Python barks out a KeyError exception. When you don’t want to worry about handling the exception, you can instead use the get (key[, obj]) method, which returns None if the mapping doesn’t exist, and even lets you specify a default value for such cases: >>> logins[‘sourceforge’,’No such login’] Traceback (innermost last): File “<interactive input>”, line 1, in ? KeyError: (‘sourceforge’, ‘No such login’) >>> logins.get(‘sourceforge’) == None 1 >>> logins.get(‘sourceforge’,’No such login’) ‘No such login’ The setdefault(key[, obj]) method works like get with the default parameter, except that if the key-value pair doesn’t exist, Python adds it to the dictionary: >>> logins.setdefault(‘slashdot’,(‘jimmy’,’punk’)) (‘juan’, ‘lemmein’) # Existing item returned >>> logins.setdefault(‘justwhispers’,(‘jimmy’,’punk’)) (‘jimmy’, ‘punk’) # New item returned AND added to dictionary If you just want to know if a dictionary has a particular key-value pair (or if you want to check before requesting it), you can use the has_key(key) method: >>> logins.has_key(‘yahoo’) 1 The del statement removes an item from a dictionary: >>> del logins[‘yahoo’] >>> logins.has_key(‘yahoo’) 0 61 4807-7 ch04.F 62 5/24/01 8:58 AM Page 62 Part I ✦ The Python Language “Hashability” The more precise requirement of a dictionary key is that it must be hashable. An object’s hash value is a semi-unique, internally generated number that can be used for quick comparisons. Consider comparing two strings, for example. To see if the strings are equal, you would have to compare each character until one differed. If you already had the hash value for each string, however, you could just compare the two and be done. Python uses hash values in dictionary lookups for the same reason: so that dictionary lookups will not be too costly. You can retrieve the hash value of any hashable object by using the hash (obj) function: >>> hash(‘hash’) -1671425852 >>> hash(10) 10 >>> hash(10.0) # Numbers of different types have the same hash. 10 >>> hash((1,2,3)) -821448277 The hash function raises the TypeError exception on unhashable objects (lists, for example). You can use the update (dict) method to add the items from one dictionary to another: >>> z = {} >>> z[‘slashdot’] = (‘fred’,’fred’) >>> z.update (logins) >>> z {‘justwhispers’: (‘jimmy’, ‘punk’), ‘slashdot’: (‘juan’, ‘lemmein’), # Duplicate key overwritten ‘hotmail’: (‘jrf5’, ‘18thStreet’)} Additional dictionary operations Here are a few other functions and methods of dictionaries that are straightforward and useful: >>> len(logins) # How many items? 3 >>> logins.keys() # List the keys of the mappings [‘justwhispers’, ‘slashdot’, ‘hotmail’] >>> logins.values() # List the other half of the mappings [(‘jimmy’, ‘punk’), (‘juan’, ‘lemmein’), (‘jrf5’, ‘18thStreet’)] >>> logins.items() # Both pieces together as tuples 4807-7 ch04.F 5/24/01 8:58 AM Page 63 Chapter 4 ✦ Advanced Data Types [(‘justwhispers’, (‘jimmy’, ‘punk’)), (‘slashdot’, (‘juan’, ‘lemmein’)), (‘hotmail’, (‘jrf5’, ‘18thStreet’))] >>> logins.clear() # Delete everything >>> logins {} You can destructively iterate through a dictionary by calling its popitem() method, which removes a random key and its value from the dictionary: >>> d = {‘one’:1, ‘two’:2, ‘three’:3} >>> try: ... while 1: ... print d.popitem() ... except KeyError: # Raises KeyError when empty ... pass (‘one’, 1) (‘three’, 3) (‘two’, 2) popitem is new in Python 2.1. New Feature Dictionary objects also provide a copy() method that creates a shallow copy of the dictionary: >>> >>> >>> {3: CrossReference a = {1:’one’, 2:’two’, 3:’three’} b = a.copy() b ‘three’, 2: ‘two’, 1: ‘one’} See “Copying Complex Objects” later in this chapter for a comparison of shallow and deep copies. Understanding References Python stores any piece of data in an object, and variables are merely references to an object; they are names for a particular spot in the computer’s memory. All objects have a unique identity number, a type, and a value. Object identity Because the object, and not the variable, has the data type (for example, integer), a variable can reference a list at one moment and a floating-point number the next. An object’s type can never change, but for lists and other mutable types its value can change. 63 4807-7 ch04.F 64 5/24/01 8:58 AM Page 64 Part I ✦ The Python Language Python provides the id(obj) function to retrieve an object’s identity (which, in the current implementation, is just the object’s address in memory): >>> shoppingList = [‘candy’,’cookies’,’ice cream’] >>> id(shoppingList) 17611492 >>> id(5) 3114676 The is operator compares the identities of two objects to see if they are the same: >>> >>> 1 >>> >>> 1 >>> 1 junkFood = shoppingList # Both reference the same object junkFood is shoppingList yummyStuff = [‘candy’,’cookies’,’ice cream’] junkFood is not yummyStuff # Different identity, but... junkFood == yummyStuff # ...same value Because variables just reference objects, a change in a mutable object’s value is visible to all variables referencing that object: >>> >>> >>> >>> [1, >>> >>> >>> 6 >>> >>> 6 a = [1,2,3,4] b=a a[2] = 5 b 2, 5, 4] a=6 b=a # Reference the same object for now. b a = a + 1 # Python creates a new object to hold (a+1) b # so b still references the original object. Counting references Each object also contains a reference count that tells how many variables are currently referencing that object. When you assign a variable to an object or when you make an object a member of a list or other container, the reference count goes up. When you destroy, reassign, or remove an object from a container the reference count goes down. If the reference count reaches zero (no variables reference this object), Python’s garbage collector destroys the object and reclaims the memory it was using. The sys.getrefcount(obj) function returns the reference count for the given object. 4807-7 ch04.F 5/24/01 8:58 AM Page 65 Chapter 4 ✦ Advanced Data Types CrossReference See Chapter 26 for more on Python’s garbage collector. New Feature As of version 2.0, Python now also collects objects with only circular references. For example, a = ; b = a.append(b); b.append(a) a = 5; b = 10 # Reassign both variables to different objects. The two list objects still have a reference count of 1 because each is a member of the other’s list. Python now recognizes such cases and reclaims the memory used by the list objects. Keep in mind that the del statement deletes a variable and not an object, although if the variable you delete was the last to reference an object then Python may end up deleting the object too: >>> >>> >>> >>> [1, CrossReference a = [1,2,3] b = a # List object has 2 references now del a # Back to 1 reference b 2, 3] You can also create weak references to objects, or references that do not affect an object’s reference count. See Chapter 7 for more information. Copying Complex Objects Assigning a variable to a list object creates a reference to the list, but what if you want to create a copy of the list? Python enables you to make two different types of copies, depending on what you need to do. Shallow copies A shallow copy of a list or other container object makes a copy of the object itself but creates references to the objects contained by the list. An easy way to make a shallow copy of a sequence is by requesting a slice of the entire object: >>> >>> >>> 0 >>> 1 faceCards = [‘A’,’K’,’Q’,’J’] myHand = faceCards[:] # Create a copy, not a reference myHand is faceCards myHand == faceCards 65 4807-7 ch04.F 66 5/24/01 8:58 AM Page 66 Part I ✦ The Python Language You can also use the copy(obj) function of the copy module: >>> >>> >>> (0, import copy highCards = copy.copy(faceCards) highCards is faceCards, highCards == faceCards 1) Deep copies A deep copy makes a copy of the container object and recursively makes copies of all the children objects. For example, consider the case when a list contains a list. A shallow copy of the parent list would contain a reference to the child list, not a separate copy. As a result, changes to the inner list would be visible from both copies of the parent list: >>> myAccount = [1000, [‘Checking’,’Savings’]] >>> yourAccount = myAccount[:] >>> myAccount[1].remove(‘Savings’) # Modify the child list. >>> myAccount [1000, [‘Checking’]] # Different parent objects share a >>> yourAccount # reference to the same child list. [1000, [‘Checking’]] Now look at the same example by using the deepcopy(obj) function in the copy module: >>> myAccount = [1000, [‘Checking’,’Savings’]] >>> yourAccount = copy.deepcopy(myAccount) >>> myAccount[1].remove(‘Savings’) >>> myAccount [1000, [‘Checking’]] # deepcopy copied the child list too. >>> yourAccount [1000, [‘Checking’, ‘Savings’]] The deepcopy function tracks which objects it copied so that if an object directly or indirectly references itself, deepcopy makes only one copy of that object. Not all objects can be copied safely. For example, copying a socket that has an open connection to a remote computer won’t work because part of the object’s internal state (the open connection) is outside the realms of Python. File objects are another example of forbidden copy territory, and Python lets you know: f = open(‘foo’,’wt’) >>> copy.deepcopy(f) Traceback (innermost last): File “<interactive input>”, line 1, in ? File “D:\Python20\lib\copy.py”, line 147, in deepcopy raise error, \ Error: un-deep-copyable object of type <type ‘file’> 4807-7 ch04.F 5/24/01 8:58 AM Page 67 Chapter 4 ✦ Advanced Data Types CrossReference Chapter 7 shows you how to override standard behaviors on classes you create. By defining your own __getstate__ and __setstate__ methods you can control how your objects respond to shallow and deep copy operations. Identifying Data Types You can check the data type of any object at runtime, enabling your programs to correctly handle different types of data (for example, think of the int function that works when you pass it an integer, a float, a string, and so on). You can retrieve the type of any object by passing the object to the type(obj) function: >>> type(5) <type ‘int’> >>> type(‘She sells seashells’) <type ‘string’> >>> type(operator) <type ‘module’> The types module contains the type objects for Python’s built-in data types. The following example creates a function that prints a list of words in uppercase. To make it more convenient to use, the function accepts either a single string or a list of strings: >>> import types >>> def upEm(words): ... if type(words) != types.ListType: # Not a list so ... words = [words] # make it a list. ... for word in words: ... print word.upper() >>> upEm(‘horse’) HORSE >>> upEm([‘horse’,’cow’,’sheep’]) HORSE COW SHEEP The following list shows a few of the more common types you’ll use. BuiltinFunctionType FunctionType MethodType BuiltinMethodType InstanceType ModuleType ClassType 67 4807-7 ch04.F 68 5/24/01 8:58 AM Page 68 Part I ✦ The Python Language IntType NoneType DictType LambdaType StringType FileType ListType TupleType FloatType LongType Classes and instances of classes have the types ClassType and InstanceType, respectively. Python provides the isinstance(obj) and issubclass(obj) functions to test if an object is an instance or a subclass of a particular type: >>> 1 >>> ... ... >>> >>> 1 CrossReference isinstance(5.1,types.FloatType) class Foo: pass a = Foo() isinstance(a,Foo) Chapter 7 covers creating and using classes and objects. Working with Array Objects While lists are flexible in that they let you store any type of data in them, that flexibility comes at a cost of more memory and a little less performance. In most cases, this isn’t an issue, but in cases where you want to exchange a little flexibility for performance or low level access, you can use the array module to create an array object. Creating arrays An array object is similar to a list except that it can hold only certain types of simple data and only one type at any given time. When you create an array object, you specify which type of data it will hold: >>> import array >>> z = array.array (‘B’) # Create an array of bytes >>> z.append(5) 4807-7 ch04.F 5/24/01 8:58 AM Page 69 Chapter 4 ✦ Advanced Data Types >>> z[0] 5 >>> q = array.array(‘i’,[5,10,-12,13]) # Optional initializer >>> q array(‘i’, [5, 10, -12, 13]) Table 4-1 lists the type code you use to create each type of array. You can retrieve the size of items and the type code of an array object using its itemsize and typecode members. Table 4-1 Array Type Codes Code Equivalent C Type Minimum Size in Bytes* c char 1 b (B) byte (unsigned byte) 1 h (H) short (unsigned short) 2 i (I) int (unsigned int) 2 l (L) long (unsigned long) 4 f float 4 d double 8 * Actual size may be greater, depending on the implementation. Converting between types Array objects have built-in support for converting to and from lists and strings, and for reading and writing with files. The following examples all deal with an array object of two-byte short integers initially containing the numbers 10, 1000, and 500: >>> z = array.array(‘h’,[10,1000,500]) >>> z.itemsize 2 Lists The tolist() method converts the array to an ordinary list: >>> z.tolist() [10, 1000, 500] 69 4807-7 ch04.F 70 5/24/01 8:58 AM Page 70 Part I ✦ The Python Language The fromlist(list) method appends items from a normal list to the end of the array: >>> z.fromlist([2,4]) >>> z array(‘h’, [10, 1000, 500, 2, 4]) If any item in the list to add is of an incorrect type, fromlist adds none of the items to the array object. Strings You can convert an array to a sequence of bytes using the tostring() method: >>> z.tostring() ‘ \n\x00\xe8\x03\xf4\x01\x02\x00\x04\x00’ >>> len(z.tostring()) 6 # 3 items, 2 bytes each The fromstring(str) method goes in the other direction, taking a string of bytes and converting them to values for the array: >>> z.fromstring(‘\x10\x00\x00\x02’) # x10 = 16, x0200 = 512 >>> z array(‘h’, [10, 1000, 500, 2, 4, 16, 512]) Files The tofile(file) method converts the array to a sequence of bytes (just like tostring) and writes the resulting bytes to a file you pass in: >>> >>> >>> >>> z = array.array(‘h’,[10,1000,500]) f = open(‘myarray’,’wb’) # Chapter 8 covers files. z.tofile(f) f.close() The fromfile(file, count) method reads the specified number of items in from a file object and appends them to the array. Continuing the previous example: >>> z.fromfile(open(‘myarray’,’rb’),3) # Read 3 items. >>> z array(‘h’, [10, 1000, 500, 10, 1000, 500]) If the file ends before reading in the number of items you requested, fromfile raises the EOFError exception, but still adds as many valid items as it could to the array. CrossReference The marshal, pickle, and struct modules all provide additional — and often better — methods for converting to and from sequences of bytes for use in files and network messages. See Chapter 12 for more. 4807-7 ch04.F 5/24/01 8:58 AM Page 71 Chapter 4 ✦ Advanced Data Types Array methods and operations Array objects support many of the same functions and methods of lists: len, append, extend, count, index, insert, pop, remove, and reverse. You can access individual members with subscription, and you can use slicing to return a smaller portion of the array (although it returns another array object and not a list). The buffer_info() method returns some low-level information about the current array. The returned tuple contains the memory address of the buffer and the length in bytes of the buffer. This information is valid until you destroy the array or it changes length. You can use the byteswap() method to change the byte order of each item in the array, which is useful for converting between big-endian and little-endian data: >>> z = array.array(‘I’,[1,2,3]) >>> z.byteswap() >>> z array(‘I’, [16777216L, 33554432L, 50331648L]) CrossReference See Chapter 12 for information on cross-platform byte ordering. CrossReference NumPy (Numeric Python) is a Python extension that you can also use to create arrays, but it has much better support for using the resulting arrays in calculations. See Chapter 31 for more information on NumPy. Summary Python provides several powerful and easy-to-use data types that simplify working with different types of data. In this chapter you: ✦ Learned the differences between Python’s sequence types. ✦ Organized data with lists, sequences, and dictionaries. ✦ Created shallow and deep copies of complex objects. ✦ Used an object’s type to handle it appropriately. ✦ Built array objects to hold homogenous data. The next chapter shows you how to expand your programs to include loops and decisions and how to catch errors with exceptions. ✦ ✦ ✦ 71 4807-7 ch04.F 5/24/01 8:58 AM Page 72 4807-7 ch05.F 5/24/01 8:58 AM Page 73 5 CHAPTER Control Flow A program is more than simply a list of actions. A program can perform an action several times (with for- and whileloops), handle various cases (with if-statements), and cope with problems along the way (with exceptions). This chapter explains how to control the flow of execution in Python. A simple Game of Life program illustrates these techniques in practice. ✦ ✦ ✦ ✦ In This Chapter Making decisions with if-statements Using for-loops Using while-loops Making Decisions with If-Statements The if-statement evaluates a conditional expression. If the expression is true, the program executes the if-block. For example: if (CustomerAge>55): print “You get a senior citizen’s discount!” An if-statement may have an else-block. If the expression is false, the else-block (if any) executes. This code block prints one greeting for Bob, and another for everyone else: if (UserName==”Bob”): print “Greetings, O supreme commander!” else: print “Hello, humble peasant.” An if-statement may have one or more elif-blocks (“elif” is shorter to type than “else if” and has the same effect). When Python encounters such a statement, it evaluates the ifexpression, then the first elif-expression, and so on, until one of the expressions evaluates to true. Then, Python executes the corresponding block of code. When Python executes an if-statement, it executes no more than one block of code. (If there is an else-block, then exactly one block of code gets executed.) Throwing and catching exceptions Debugging with assertions Example: Game of Life ✦ ✦ ✦ ✦ 4807-7 ch05.F 74 5/24/01 8:58 AM Page 74 Part I ✦ The Python Language Listing 5-1 is a sample script that uses an if-statement (shown in both italics and bold) in a simple number-guessing game. Listing 5-1: NumberGuess.py import random import sys # This line chooses a random integer >=1 and <=100. # (See Chapter 15 for a proper explanation.) SecretNumber=random.randint(1,100) print “I’m thinking of a number between 1 and 100.” # Loop forever (at least until the user hits Ctrl-Break). while (1): print “Guess my number.” # The following line reads a line of input from # the command-line and converts it to an integer. NumberGuess=int(sys.stdin.readline()) if (NumberGuess==SecretNumber): print “Correct! Choosing a new number...” SecretNumber=random.randint(1,100) elif (NumberGuess > SecretNumber): print “Lower.” else: print “Higher.” You can use many elif clauses; the usual way to write Python code that handles five different cases is with an if-elif-elif-elif-else statement. (Veterans of C and Java, take note: Python does not have a switch statement.) Note Python stops checking if-expressions as soon as it finds a true one. If you write an if-statement to handle several different cases, consider putting the most common and/or cheapest-to-check cases first in order to make your program faster. Using For-Loops For-loops let your program do something several times. In addition, you can iterate over elements of a sequence with a for-loop. Anatomy of a for-loop A simple for statement has the following syntax: 4807-7 ch05.F 5/24/01 8:58 AM Page 75 Chapter 5 ✦ Control Flow for <variable> in <sequence>: (loop body) The statement (or block) following the for statement forms the body of the loop. Python executes the body once for each element of the sequence. The loop variable takes on each element’s value, in order, from first to last. For instance: for Word in [“serious”,”silly”,”slinky”]: print “The minister’s cat is a “+Word+” cat.” The body of a loop can be a single statement on the same line as the for-statement: for Name in [“Tom”,”Dick”,”Harry”]: print Name Some people (myself included) usually stick with the first style, because all-on-one-line loops can lead to long and tricky lines of code. Python can loop over any sequence type — even a string. If the sequence is empty, the loop body never executes. Looping example: encoding strings Listing 5-2 uses for-loops to convert strings to a list of hexadecimal values, and back again. The encoded strings look somewhat similar to the “decoder rings” popular on old children’s radio programs. Listing 5-2: DecoderRing.py import string def Encode(MessageString): EncodedList= # Iterate over each character in the string for Char in MessageString: EncodedList.append(“%x” % ord(Char)) return EncodedList def Decode(SecretMessage): DecodedList= # Iterate over each element in the list for HexValue in SecretMessage: # The following line converts HexValue from # a hex-string to an integer, then finds the ASCII # symbol for that integer, and finally adds that # character to the list. # Don’t try this at home! :) DecodedList.append(chr(int(HexValue,16))) Continued 75 4807-7 ch05.F 76 5/24/01 8:58 AM Page 76 Part I ✦ The Python Language Listing 5-2 (continued) # Join these strings together, with no separator. return string.join(DecodedList,””) if (__name__==”__main__”): SecretMessage=Encode(“Remember to drink your Ovaltine!”) print SecretMessage print Decode(SecretMessage) Listing 5-3: DecoderRing.py output [‘52’, ‘65’, ‘6d’, ‘65’, ‘6d’, ‘62’, ‘65’, ‘72’, ‘20’, ‘74’, ‘6f’, ‘20’, ‘64’, ‘72’, ‘69’, ‘6e’, ‘6b’, ‘20’, ‘79’, ‘6f’, ‘75’, ‘72’, ‘20’, ‘4f’, ‘76’, ‘61’, ‘6c’, ‘74’, ‘69’, ‘6e’, ‘65’, ‘21’] Remember to drink your Ovaltine! Ranges and xranges Many loops do something a fixed number of times. To iterate over a range of numbers, use range. For example: # print 10 numbers (from 0 to 9) for X in range(10): print X The function range returns a list of numbers that you can use anywhere (not just in a loop). The syntax is: range(start[,end[,step]]). The numbers in the range begin with start, increment by step each time, and stop just before end. Both start and step are optional; by default, a range starts at 0 and increments by 1. For example: >>> range(10,0,-1) # Countdown! [10, 9, 8, 7, 6, 5, 4, 3, 2, 1] >>> range(5,10) [5, 6, 7, 8, 9] Code that does something once for each element of a sequence sometimes loops over range(len(SequenceVariable)). This range contains the index of each element in the sequence. For example, this code prints the days of the week: DaysOfWeek=[“Monday”, “Tuesday”, “Wednesday”, “Thursday”, “Friday”, “Saturday”, “Sunday”] for X in range(len(DaysOfWeek)): print “Day”,X,”is”,DaysOfWeek[X] 4807-7 ch05.F 5/24/01 8:58 AM Page 77 Chapter 5 ✦ Control Flow An xrange is an object that represents a range of numbers. You can loop over an xrange instead of the list returned by range. The only real difference is that creating a large range involves creating a memory-hogging list, while creating an xrange of any size is cheap. Try checking your system’s free memory while running these interpreter commands: >>> MemoryHog=range(1000000) # There goes lots of RAM! >>> BigXRange=xrange(1000000) # Only uses a little memory. To see the contents of an xrange in convenient list form, use the tolist method: >>> SmallXRange=xrange(10,110,10) >>> SmallXRange.tolist() [10, 20, 30, 40, 50, 60, 70, 80, 90, 100] Breaking, continuing, and else-clauses Python’s continue statement jumps to the next iteration of a loop. The break statement jumps out of a loop entirely. These statements apply only to the innermost loop; if you are in a loop-within-a-loop-within-a-loop, break jumps out of only the innermost loop. You can follow the body of a for-loop with an else-clause. The code in the else-clause executes after the loop finishes iterating, unless the program exits the loop due to a break statement. (If you have no break statement in the loop, the else-clause always executes, so you really have no need to put the code in an else-clause.) Listing 5-4 illustrates break, continue, and an else-clause: Listing 5-4: ClosestPoint.py import math def FindClosestPointAboveXAxis(PointList,TargetPoint): “”” Given a list of points and a target point, this function returns the list’s closest point, and its distance from the target. It ignores all points with a negative y-coordinate. We represent points in the plane (or on screen) as a two-valued tuple of the form (x-coordinate,y-coordinate). “”” ClosestPoint=None # Initialize. ClosestDistance=None # Iterate over each point in the list. for Point in PointList: # Throw out any point below the X axis. if (Point[1]<0): # Skip to the next point in the list. continue # Compute the distance from this point to the target. Continued 77 4807-7 ch05.F 78 5/24/01 8:58 AM Page 78 Part I ✦ The Python Language Listing 5-4 (continued) # The following two lines are one statement; # indentation for clarity is optional. DistToPoint=math.sqrt((TargetPoint[0]-Point[0])**2 + (TargetPoint[1]-Point[1])**2) if (ClosestDistance == None or DistToPoint < ClosestDistance): ClosestPoint=Point ClosestDistance = DistanceToPoint if (DistanceToPoint==0): print “Point found in list” # Exit the loop entirely, since no point will # be closer than this break else: # This clause executes unless we hit the break above. print “Point not found in list” return (ClosestPoint, ClosestDistance) Here is the function in action: >>> SomePoints=[(-1,-1),(4,5),(-5,7),(23,-2),(5,2)] >>> ClosestPoint.FindClosestPointAboveXAxis(SomePoints,(1,1)) Point not found in list ((5, 2), 4.1231056256176606) >>> ClosestPoint.FindClosestPointAboveXAxis(SomePoints,(-1,-1)) Point not found in list ((5, 2), 6.7082039324993694) >>> ClosestPoint.FindClosestPointAboveXAxis(SomePoints,(4,5)) Point found in list ((4, 5), 0.0) Changing horses in midstream Modifying the sequence that you are in the process of looping over is not recommended — Python won’t get confused, but any mere mortals reading your program will. The loop variable keeps iterating over its reference sequence, even if you change a sequence variable. For example, this loop prints the numbers from 0 to 99; changing the value that MyRange points to does not affect control flow: MyRange=range(100) for X in MyRange: print X MyRange = range(30) # No change in looping behavior! 4807-7 ch05.F 5/24/01 8:58 AM Page 79 Chapter 5 ✦ Control Flow However, changing the reference sequence does affect the loop. After executing for the nth element in a sequence, the loop proceeds to the (n+1)th element, even if the sequence changes in the process. For example, this loop prints even numbers from 0 to 98: MyRange=range(100) for X in MyRange: print X del MyRange[0] # Changing the loop-sequence in place Modifying the loop variable inside a for-loop is also inadvisable. It does not change looping behavior; Python will continue the next iteration of the loop as usual. Using While-Loops If you could crossbreed an if-statement and a for-loop, you would get a whilestatement, Python’s other looping construct. A while-statement has the form: while (<expression>): <block of code> When Python encounters a while-statement, it evaluates the expression, and if the expression is true, it executes the corresponding block of code. Python keeps executing the block of code until the expression is no longer true. For example, this code counts down from 10 to 1: X=10 while (X>0): print X X -= 1 Within a while-loop, you can use the continue statement to jump to the next iteration, or the break statement to jump out of the loop entirely. A while-loop can also have an else-block. Code in the else-block executes immediately after the last iteration, unless a break statement exits the loop. These statements work similarly for for-loops and while-loops. See the section on for-loops, above, for examples of break, continue, and else. Throwing and Catching Exceptions Imagine a Python program innocently going about its business, when suddenly . . . [dramatic, scary music] something goes wrong. 79 4807-7 ch05.F 80 5/24/01 8:58 AM Page 80 Part I ✦ The Python Language In general, when a function or method encounters a situation that it can’t cope with, it raises an exception. An exception is a Python object that represents an error. Passing the buck: propagating exceptions When a function raises an exception, the function must either handle the exception immediately or terminate. If the function doesn’t handle the exception, the caller may handle it. If not, the caller also terminates immediately as well. The exception propagates up the call-stack until someone handles the error. If nobody catches the exception, the whole program terminates. In general, functions that return a value should return None to indicate a “reasonable” failure, and only raise an exception for “unreasonable” problems. Just what is reasonable is open to debate, so it is generally a good idea to clearly document the exceptions your code raises, and to handle common exceptions raised by the code you call. Handling an exception If you have some “suspicious” code that may raise an exception, you can defend your program by placing the suspicious code in a try: block. After the try: block, include an except statement, followed by a block of code which handles the problem (as elegantly as possible). For example, the guess-the-number program from earlier in this chapter crashes if you try to feed it something other than an integer. The error looks something like this: Traceback (most recent call last): File “C:\Python20\NumberGuess.py”, line 7, in ? NumberGuess=int(sys.stdin.readline()) ValueError: invalid literal for int(): whoops! Listing 5-5 shows a new-and-improved script that handles the exception. The call to sys.stdin.readline() is now in a try: block: Listing 5-5: NumberGuess2.py import random import sys # This line chooses a random integer >=1 and <=100. # (See Chapter 15 for a proper explanation.) SecretNumber=random.randint(1,100) 4807-7 ch05.F 5/24/01 8:58 AM Page 81 Chapter 5 ✦ Control Flow print “I’m thinking of a number between 1 and 100.” # Loop forever (at least until the user hits Ctrl-Break). while (1): print “Guess my number.” # The following line reads a line of input from # the command line and converts it to an integer. try: NumberGuess=int(sys.stdin.readline()) except ValueError: print “Please type a whole number.” continue if (NumberGuess==SecretNumber): print “Correct! Choosing a new number...” SecretNumber=random.randint(1,100) elif (NumberGuess > SecretNumber): print “Lower.” else: print “Higher.” More on exceptions An exception can have an argument, which is a value that gives additional information about the problem. The contents (and even the type) of the argument vary by exception. You capture an exception’s argument by supplying a variable in the except clause: except ExceptionType,ArgumentVariable You can supply several except clauses to handle various types of exceptions. In this case, exceptions are handled by the first applicable except clause. You can also provide a generic except clause, which handles any exception. If you do this, I highly recommend that you do something with the exception. Code that silently “swallows” exceptions may mask important bugs, like a NameError. Here is some cookie-cutter code I use for quick-and-dirty error handling: try: DoDangerousStuff() except: # The show must go on! # Print the exception and the stack trace, and continue. (ErrorType,ErrorValue,ErrorTB)=sys.exc_info() print sys.exc_info() traceback.print_exc(ErrorTB) After the except clause(s), you can include an else-clause. The code in the else-block executes if the code in the try: block does not raise an exception. The else-block is a good place for code that does not need the try: block’s protection. Python raises an IOError exception if you try to open a file that doesn’t exist. Here is a snippet of code that handles a missing file without crashing. (This code grabs the exception argument — a tuple consisting of an error number and error string — but doesn’t do anything interesting with it.) 81 4807-7 ch05.F 82 5/24/01 8:58 AM Page 82 Part I ✦ The Python Language try: OptionsFile=open(“SecretOptions.txt”) except IOError, (ErrorNumber,ErrorString): # Assume our default option values are all OK. # We need a statement here, but we have nothing # to do, so we pass. pass else: # This executes if we opened it without an IOError. ParseOptionsFile(OptionsFile) Defining and raising exceptions You can raise exceptions with the statement raise exceptionType,argument. ExceptionType is the type of exception (for example, NameError). Argument is a value for the exception argument. Argument is optional; if not supplied, the exception argument is None. An exception can be a string, a class, or an object. Most of the exceptions that the Python core raises are classes, with an argument that is an instance of the class. Defining new exceptions is quite easy, as this contrived example demonstrates: def CalculateElfHitPoints(Level): if Level<1: raise “Invalid elf level!”,Level # (The code below won’t execute if we raise # the exception.) HitPoints=0 for DieRoll in range(Level): HitPoints += random.randint(1,6) Note In order to catch an exception, an “except” clause must refer to the same exception thrown. Python compares string exceptions by reference identity (is, not ==). So, if you have code to raise “BigProblem” and an except-clause for “BigProblem,” the except clause may not catch the exception. (The strings are equivalent, but may not point to the same spot in memory.) To handle exceptions properly, use a named constant string, or a class. (See Listing 5-6 for an example.) Cleaning up with finally An alternative mechanism for coping with failure is the finally block. The finally block is a place to put any code that must execute, whether the try-block raised an exception or not. You can provide except clause(s), or a finally clause, but not both. For example, multithreaded programs often use a lock to prevent threads from stomping on each other’s data. If a thread acquires a lock and crashes without releasing it, the other threads may be kept waiting forever — an unpleasant situation called deadlock. This example is a perfect job for the finally clause: 4807-7 ch05.F 5/24/01 8:58 AM Page 83 Chapter 5 ✦ Control Flow try: DataLock.acquire() # ... do things with the data ... finally: # This code *must* execute. The fate of the # free world hangs in the balance! DataLock.release() Debugging with Assertions An assertion is a sanity-check that you can turn on (for maximum paranoia) or turn off (to speed things up). Using an assertion can help make code self-documenting; raising an AssertionError implies that a problem is due to programmer error and not normal problems. Programmers often place assertions at the start of a function to check for valid input, and after a function call to check for valid output. Assertions in Python You can add assertions to your code with the syntax assert <Expression>. When it encounters an assert statement, Python evaluates the accompanying expression, which is hopefully true. If the expression is false, Python raises an AssertionError. You can include an assertion argument, via the syntax assert Expression,ArgumentExpression. If the assertion fails, Python uses ArgumentExpression as the argument for the AssertionError. For example, here is a function that converts a temperature from degrees Kelvin to degrees Fahrenheit. Since zero degrees Kelvin is as cold as it gets, the function bails out if it sees a negative temperature: >>> def KelvinToFahrenheit(Temperature): ... assert (Temperature >= 0),”Colder than absolute zero!” ... return ((Temperature-273)*1.8)+32 >>> KelvinToFahrenheit(273) 32.0 >>> int(KelvinToFahrenheit(505.78)) 451 >>> KelvinToFahrenheit(-5) Traceback (innermost last): File “<pyshell#186>”, line 1, in ? KelvinToFahrenheit(-5) File “<pyshell#178>”, line 2, in KelvinToFahrenheit assert (Temperature >= 0),”Colder than absolute zero!” AssertionError: Colder than absolute zero! 83 4807-7 ch05.F 84 5/24/01 8:58 AM Page 84 Part I ✦ The Python Language Toggling assertions Normally, assertions are active. They are toggled by the internal variable __debug__. Turning on optimization (by running python with the -O command-line argument) turns assertions off. (Direct access to __debug__ is also possible, but not recommended.) In assert statements, avoid using expressions with side effects. If the assertion expression affects the data, then the “release” and “debug” versions of your scripts may behave differently, leaving you with twice as much debugging to do. Tip Example: Game of Life Listing 5-6 simulates John Conway’s Game of Life, a simple, cellular automata. The game is played on a grid. Each cell of the grid can be “alive” or “dead.” Each “generation,” cells live or die based on the state of their eight neighboring cells. Cells with three living neighbors come to life. Live cells with two living neighbors stay alive. All other cells die (or stay dead). CrossReference This example introduces a class to represent the playing field. For further information on classes, see Chapter 7. Listing 5-6: LifeGame.py # We arbitrarily set the field size to 10x10. Naming the size # in upper-case implies that we shouldn’t change its value. FIELD_SIZE=10 # Create two strings for use as exceptions. We raise and catch # these variables, instead of raw strings (which would be ==# equivalent, but possibly not is-equivalent). STEADY_STATE=”Steady state” EVERYONE_DEAD=”Everyone dead” class PlayField: # Constructor. When creating a PlayField, initialize the # grid to be all dead: def __init__(self): self.LifeGrid={} for Y in range(FIELD_SIZE): for X in range(FIELD_SIZE): self.LifeGrid[(X,Y)]=0 def SetAlive(self,X,Y): self.LifeGrid[(X,Y)]=1 def SetDead(self,X,Y): self.LifeGrid[(X,Y)]=0 def PrintGrid(self,Number): print “Generation”,Number 4807-7 ch05.F 5/24/01 8:58 AM Page 85 Chapter 5 ✦ Control Flow for Y in range(FIELD_SIZE): for X in range(FIELD_SIZE): # Trailing comma means don’t print newline: print self.LifeGrid[(X,Y)], # Print newline at end of row: print def GetLiveNeighbors(self,X,Y): # The playing field is a “donut world”, where the # edge cells join to the opposite edge. LeftColumn=X-1 if (LeftColumn<0): LeftColumn=FIELD_SIZE-1 RightColumn=(X+1) % FIELD_SIZE UpRow=Y-1 if (UpRow<0): UpRow=FIELD_SIZE-1 DownRow=(Y+1) % FIELD_SIZE LiveCount=(self.LifeGrid[(LeftColumn,UpRow)]+ self.LifeGrid[(X,UpRow)]+ self.LifeGrid[(RightColumn,UpRow)]+ self.LifeGrid[(LeftColumn,Y)]+ self.LifeGrid[(RightColumn,Y)]+ self.LifeGrid[(LeftColumn,DownRow)]+ self.LifeGrid[(X,DownRow)]+ self.LifeGrid[(RightColumn,DownRow)]) return (LiveCount) def RunGeneration(self): NewGrid={} AllDeadFlag=1 for Y in range(FIELD_SIZE): for X in range(FIELD_SIZE): CurrentState=self.LifeGrid[(X,Y)] LiveCount=self.GetLiveNeighbors(X,Y) if ((LiveCount==2 and CurrentState) or (LiveCount==3)): NewGrid[(X,Y)]=1 AllDeadFlag=0 else: NewGrid[(X,Y)]=0 if (AllDeadFlag): raise EVERYONE_DEAD if self.LifeGrid==NewGrid: raise STEADY_STATE self.LifeGrid,OldGrid=NewGrid,self.LifeGrid def ShowManyGenerations(self,GenerationCount): try: for Cycle in range(GenerationCount): self.PrintGrid(Cycle) self.RunGeneration() except EVERYONE_DEAD: print “The population is now dead.” except STEADY_STATE: print “The population is no longer changing.” if (__name__==”__main__”): # This first grid quickly settles into a pattern # that does not change. Continued 85 4807-7 ch05.F 86 5/24/01 8:58 AM Page 86 Part I ✦ The Python Language Listing 5-6 (continued) BoringGrid=PlayField() BoringGrid.SetAlive(2,2) BoringGrid.SetAlive(2,3) BoringGrid.SetAlive(2,4) BoringGrid.SetAlive(3,2) BoringGrid.ShowManyGenerations(50) # This grid contains a “glider” – a pattern of live # cells which moves diagonally across the grid. GliderGrid=PlayField() GliderGrid.SetAlive(0,0) GliderGrid.SetAlive(1,0) GliderGrid.SetAlive(2,0) GliderGrid.SetAlive(2,1) GliderGrid.SetAlive(1,2) GliderGrid.ShowManyGenerations(50) Summary Python has several tools for controlling the flow of execution. In this chapter you: ✦ Made decisions with if-statements. ✦ Set up repeating tasks with for-loops and while-loops. ✦ Built code that copes with problems by handling exceptions. ✦ Learned to add test scaffolding with assertions. In the next chapter you’ll learn how to organize all your Python code into functions, modules, and packages. ✦ ✦ ✦ 4807-7 ch06.F 5/24/01 8:58 AM Page 87 6 CHAPTER Program Organization ✦ ✦ ✦ ✦ In This Chapter P ython lets you break code down into reusable functions and classes, then reassemble those components into modules and packages. The larger the project, the more useful this organization becomes. This chapter explains function definition syntax, module and package structure, and Python’s rules for visibility and scope. Defining Functions Here is a sample function definition: def ReverseString(Forwards): “””Convert a string to a list of characters, reverse the list, and join the list back into a string “”” CharacterList=list(Forwards) CharacterList.reverse() return string.join(CharacterList,””); The statement def FunctionName([parameters,...]) begins the function. Calling the function executes the code within the following indented block. A string following the def statement is a docstring. A docstring is a comment intended as documentation. Development environments like IDLE display a function’s docstrings to show how to call the function. Also, tools like HappyDoc can extract docstrings from code to produce documentation. So, a docstring is a good place to describe a function’s behavior, parameter requirements, and the like. Modules can also have a docstring — a string preceding any executable code is taken to be the module’s description. Defining functions Grouping code with modules Importing modules Locating modules Understanding scope rules Grouping modules into packages Compiling and running programmatically ✦ ✦ ✦ ✦ 4807-7 ch06.F 88 5/24/01 8:58 AM Page 88 Part I ✦ The Python Language The statement return [expression] exits a function, optionally passing back an expression to the caller. A return statement with no arguments is the same as return None. A function also exits (returning None) when the last statement finishes, and execution “runs off the end of” the function code block. Pass by object reference A Python variable is a reference to an object. Python passes function parameters using call-by-value. If you change what a parameter refers to within a function, the change does not affect the function’s caller. For example: >>> ... ... >>> >>> >>> [1, def StupidFunction(InputList): InputList=[“I”,”Like”,”Cheese”] MyList=[1,2,3] StupidFunction(MyList) print MyList # MyList is unchanged! 2, 3] The parameter InputList is local to the function StupidFunction. Changing InputList within the function does not affect MyList. The function accomplishes nothing. However, a function can change the object that a parameter refers to. For example, this function removes duplicate elements from a list: def RemoveDuplicates(InputList): ListIndex=-1 # We iterate over the list from right to left, deleting # all duplicates of element -1, then -2, and so on. (Because # we are removing elements of the list, using negative # indices is convenient: element -3 is still element -3 # after we delete some items preceding it.) while (-ListIndex<len(InputList)): # list.index() returns a positive index, so get the # positive equivalent of ListIndex and name it # CurrentIndex (same element, new index number). CurrentIndex=len(InputList)+ListIndex CurrentElement=InputList[ListIndex] # Keep removing duplicate elements as long as # an element precedes the current one. while (InputList.index(CurrentElement)<CurrentIndex): InputList.remove(CurrentElement) CurrentIndex=CurrentIndex-1 ListIndex=ListIndex-1 All about parameters A function parameter can have a default value. If a parameter has a default value, you do not need to supply a value to call the function. 4807-7 ch06.F 5/24/01 8:58 AM Page 89 Chapter 6 ✦ Program Organization When you call a function, you can supply its parameters by name. It is legal to name some parameters and not others — but after supplying the name for one parameter, you must name any other parameters you pass. For example, this function simulates the rolling of dice. By default, it rolls ordinary 6-sided dice, one at a time: >>> import whrandom >>> def RollDice(Dice=1,Sides=6): ... Total=0 ... for Die in range(Dice): ... Total += whrandom.randint(1,Sides) ... return Total ... >>> RollDice() 5 >>> RollDice(2) # Come on, snake-eyes! 8 >>> RollDice(2,4) # Roll two four-sided dice. 5 >>> RollDice(Sides=20) # Named parameter 17 >>> # After naming one parameter, you must name the rest: >>> RollDice(Sides=5,4) SyntaxError: non-keyword arg after keyword arg A function evaluates its argument defaults only once. We recommend avoiding dynamic (or mutable) default values. For example, if you do not pass a value to this function, it will always print the time that you first called it: def PrintTime(TimeStamp=time.time()): # time.time() is the current time in milliseconds, # time.localtime() puts the time into the # canonical tuple-form, and time.asctime() converts # the time-tuple to a cute string format. # The function’s default argument, TimeStamp, does # not change between calls! print time.asctime(time.localtime(TimeStamp)) This improved version of the function prints the current time if another time is not provided: def PrintTime(TimeStamp=None): if (TimeStamp==None): TimeStamp=time.time() print time.asctime(time.localtime(TimeStamp)) Arbitrary arguments A function can accept an arbitrary sequence of parameters. The function collects these parameters into one tuple. This logging function shows the internal object IDs of a sequence of arguments: 89 4807-7 ch06.F 90 5/24/01 8:58 AM Page 90 Part I ✦ The Python Language def LogObjectIDs(LogString, *args): print LogString for arg in args: print id(arg) A function can also accept an arbitrary collection of named parameters. The function collects these named parameters into one dictionary. This version of the logging function lets you give names to the objects passed in: def LogObjectIDs(LogString, **kwargs): print LogString for (ParamName,ParamValue) in kwargs.items(): print “Object:”,ParamName,”ID:”,id(ParamValue) To make a truly omnivorous function, you can take a dictionary of arbitrary named parameters and a tuple of unnamed parameters. Apply: passing arguments from a tuple The function apply(InvokeFunction,ArgumentSequence) calls the function InvokeFunction, passing the elements of ArgumentSequence as arguments. The usefulness of apply is that it breaks arguments out of a tuple cleanly, for any length of tuple. For example, assume you have a function SetColor(Red,Green,Blue), and a tuple representing a color: >>> print MyColor (255, 0, 255) >>> SetColor(MyColor[0],MyColor[1],MyColor[2]) # Kludgy! >>> apply(SetColor,MyColor) # Same as above, but cleaner. A bit of functional programming Python can define new functions on the fly, giving you some of the functional flexibility of languages like Lisp and Scheme. You define an anonymous function with the lambda keyword. The syntax is lambda [parameters,...]: <expression>. For example, here is an anonymous function that filters list entries: >>> SomeNumbers=[5,10,15,3,18,2] >>> filter(lambda x:x>10, SomeNumbers) [15, 18] This code uses anonymous functions to test for primes: 4807-7 ch06.F 5/24/01 8:58 AM Page 91 Chapter 6 ✦ Program Organization def FindPrimes(EndNumber): NumList = range(2,EndNumber) Index=0 while (Index<len(NumList)): NumList=filter(lambda y,x=NumList[Index]: (y<=x or y%x!=0), NumList) Index += 1 print NumList Lambda functions can be helpful for event handling in programs with a GUI. For example, here is some code to add a button to a Tkinter frame. def AddCosmeticButton(ButtonFrame,ButtonLabel): Button(ButtonFrame,text=ButtonLabel,command = lambda =ButtonLabel:LogUnimplemented(l)).pack() Clicking the button causes it to call LogUnimplemented with the button label as an argument. Presumably, LogUnimplemented makes note of the fact that somebody is clicking a button that does nothing. Note An anonymous function cannot be a direct call to print because lambda requires an expression. Note Lambda functions have their own local namespace and cannot access variables other than those in their parameter list and those in the global namespace. Grouping Code with Modules A module is a file consisting of Python code. A module can define functions, classes, and variables. A module can also include runnable code. A stand-alone module is often called a script or program. You can use whichever word you like, because Python makes no distinction between them. Grouping related code into a module makes the code easier to understand and use. When writing a program, split off code into separate modules whenever a file starts becoming too large or performing too many different functions. Laying out a module The usual order for module elements is: ✦ Docstring and/or general comments (revision log or copyright information, and so on) ✦ Import statements (see below for more information on importing modules) 91 4807-7 ch06.F 92 5/24/01 8:58 AM Page 92 Part I ✦ The Python Language ✦ Definitions of module-level variables (“constants”) ✦ Definitions of classes and functions ✦ Main function, if any This organization is not required, but it works well and is widely used. Note People often store frequently used values in ALL_CAPS_VARIABLES to make later code easier to maintain, or simply more readable. For example, the standard library ftplib includes this definition: FTP_PORT = 21 # The standard FTP server control port Such a variable is “constant by convention” — Python does not forbid modifications, but callers should not change its value. Taking inventory of a module The function dir(module) returns a list of the variables, functions, and classes defined in module. With no arguments, dir returns a list of all currently defined names. dir(__builtin__) returns a list of all built-in names. For example: >>> dir() # Just after starting Python [‘__builtins__’, ‘__doc__’, ‘__name__’] >>> import sys >>> dir() [‘__builtins__’, ‘__doc__’, ‘__name__’, ‘sys’] You can pass any object (or class) to dir to get a list of class members. Importing Modules To use a module, you must first import it. Then, you can access the names in the module using dotted notation. For example: >>> string.digits # Invalid, because I haven’t imported string Traceback (most recent call last): File “<stdin>”, line 1, in ? NameError: There is no variable named ‘string’ >>> import string # Note: No parentheses around module name. >>> string.digits ‘0123456789’ Another option is to import names from the module into the current namespace, using the syntax from ModuleName import Name, Name2,.... For example: >>> from string import digits >>> digits # Without a dot ‘0123456789’ 4807-7 ch06.F 5/24/01 8:58 AM Page 93 Chapter 6 ✦ Program Organization >>> string.digits # I don’t know about the module, only digits. Traceback (most recent call last): File “<stdin>”, line 1, in ? NameError: There is no variable named ‘string’ To bring every name from a module into the current namespace, use a blanket import: from module import *. Importing modules this way can make for confusing code, especially if two modules have functions with the same name. But it can also save a lot of typing. The import statements for a script should appear at the beginning of the file. (This arrangement is not required, but importing halfway though a script is confusing.) What else happens upon import? Within a module, the special string variable __name__ is the name of the module. When you execute a stand-alone module, its __name__ is always __main__. This provides a handy way to set aside code that runs when you invoke a module, but not when you import it. Some modules use this code as a test driver. (See Listing 6-1.) Listing 6-1: Alpha.py import string def Alphabetize(Str): “Alphabetize the letters in a string” CharList=list(Str) CharList.sort() return (string.join(CharList,””)) if (__name__==”__main__”): # This code runs when we execute the script, not when # we import it. X=string.upper(“BritneySpears”) Y=string.upper(“Presbyterians”) # Strange but true! print (Alphabetize(X)==Alphabetize(Y)) else: # This code runs when we import (not run) the module. print “Imported module Alpha” Reimporting modules Once Python has imported a module once, it doesn’t import it again for subsequent import statements. You can force Python to “reimport” a module with a call to reload(LoadedModule). This procedure is useful for debugging — you can edit a 93 4807-7 ch06.F 94 5/24/01 8:58 AM Page 94 Part I ✦ The Python Language module on disk, then reload it without having to restart an interactive interpreter session. Exotic imports A module can override standard import behavior by implementing the function __import__ (name[, globals[, locals[, fromlist]]]). Because a module is a class, defining __import__ in a module amounts to overriding the default version of __import__. Caution We don’t recommend overriding __import__ as it is a very low-level operation for such a high-level language! See the libraries imp, ihooks, and rexec for examples of overridden import behavior. Locating Modules When you import a module, the Python interpreter searches for the module in the current directory. If the module isn’t found, Python then searches each directory in the PythonPath. If all else fails, Python checks the default path. On Windows, the default path consists of c:\python20\lib\ and some subdirectories; on UNIX, this default path is normally /usr/local/lib/python/. (The code for Python’s standard libraries is installed into the default path. Some modules, such as sys, are built into the Python interpreter, and have no corresponding .py files.) Python stores a list of directories that it searches for modules in the variable sys.path. Python path The PythonPath is an environment variable, consisting of a list of directories. Here is a typical PythonPath from a Windows system: set PYTHONPATH=c:\python20\lib;c:\python20\lib\proj1;c:\python20\lib\bob And here is a typical PythonPath from a UNIX system: set PYTHONPATH=/home/stanner/python;/usr/bin/python/lib I generally use a scratch folder to hold modules I am working on; other files I put in the lib directory (or, if they are part of a package, in subdirectories). I find that setting the PythonPath explicitly is most useful for switching between different versions of a module. 4807-7 ch06.F 5/24/01 8:58 AM Page 95 Chapter 6 ✦ Program Organization Compiled files You can compile a Python program into system-independent bytecodes. The interpreter stores the compiled version of a module in a corresponding file with a .pyc extension. This precompiled file runs at the same speed, but loads faster because Python need not parse the source code. Files compiled with the optimization flag on are named with a .pyo extension, and behave like .pyc files. When you import a module foo, Python looks for a compiled version of foo. Python looks for a file named foo.pyc that is as new as foo.py. If so, Python loads foo. pyc instead of re-parsing foo.py. If not, Python parses foo.py, and writes out the compiled version to foo.pyc. Note When you run a script from the command line, Python does not create (or look for) a precompiled version. To save some parsing time, you can invoke a short “stub” script that imports the main module. Or, you can compile the main script by hand (by importing it, by calling py_compile.compile(ScriptFileName), or by calling compileall.compile_dir(ScriptDirectoryName)), then invoke the .pyc file directly. However, be sure to precompile the script again when you change it! Understanding Scope Rules Variables are names (identifiers) that map to objects. A namespace is a dictionary of variable names (keys) and their corresponding objects (values). A Python statement can access variables in a local namespace and in the global namespace. If (heaven forfend!) a local and a global variable have the same name, the local variable shadows the global variable. Each function has its own local namespace. Class methods follow the same scoping rule as ordinary functions. Python accesses object attributes via the self argument; attributes are not brought separately into the namespace. At the module level, or in an interactive session, the local namespace is the same as the global namespace. For purposes of an eval, exec, execfile, or input statement, the local namespace is the same as the caller’s. Is it local or global? Python makes educated guesses on whether variables are local or global. It assumes that any variable assigned a value in a function is local. Therefore, in order to assign a value to a global variable within a function, you must first use the global statement. The statement global VarName tells Python that VarName is a global variable. Python stops searching the local namespace for the variable. 95 4807-7 ch06.F 96 5/24/01 8:58 AM Page 96 Part I ✦ The Python Language For example, Listing 6-2 defines a variable NumberOfMonkeys in the global namespace. Within the function AddMonkey, we assign NumberOfMonkeys a value — therefore, Python assumes NumberOfMonkeys is a local variable. However, we access the value of the local variable NumberOfMonkeys before setting it, so an UnboundLocalError is the result. Uncommenting the global statement fixes the problem. Listing 6-2: Monkeys.py NumberOfMonkeys = 11 def AddMonkey(): # Uncomment the following line to fix the code: #global NumberOfMonkeys NumberOfMonkeys = NumberOfMonkeys + 1 print NumberOfMonkeys AddMonkey() print NumberOfMonkeys Listing namespace contents The built-in functions locals and globals return local and global namespace contents in dictionary form. These operations are handy for debugging. Grouping Modules into Packages You can group related modules into a package. Packages can also contain subpackages, and sub-subpackages, and so on. You access modules inside a package using dotted notation — for example, seti.log.FlushLogFile() calls the function FlushLogFile in the module log in the package seti. Python locates packages by looking for a directory containing a file named __init__.py. The directory can be a subdirectory of any directory in sys.path. The directory name is the package name. The script __init__.py runs when the package is imported. It can be an empty file, but should probably at least contain a docstring. It may also define the special variable __all__, which governs the behavior of a blanket import of the form from PackageName import *. If defined, __all__ is a list of names of modules to bring into 4807-7 ch06.F 5/24/01 8:58 AM Page 97 Chapter 6 ✦ Program Organization the current namespace. If the script __init__.py does not define __all__, then a blanket-import brings into the current namespace only the names defined and modules imported in __init__.py. CrossReference See Chapter 36 for information on how to install new modules and packages, and how to distribute your own code. Compiling and Running Programmatically The exec statement can run an arbitrary chunk of Python code. The syntax is exec ExecuteObject [in GlobalDict[, LocalDict]]. ExecuteObject is a string, file object, or code object containing Python code. GlobalDict and LocalDict are dictionaries used for the global and local namespaces, respectively. Both GlobalDict and LocalDict are optional. If you omit LocalDict, it defaults to GlobalDict. If you omit both, the code runs using the current namespaces. The eval function evaluates a Python expression. The syntax is eval (ExpressionObject[,GlobalDict[,LocalDict]]). ExpressionObject is a string or a code object; GlobalDict and LocalDict have the same semantics as for exec. The execfile function has the same syntax as exec, except that it takes a file name instead of an execute object. These functions raise an exception if they encounter a syntax error. The compile function transforms a code string into a runnable code object. Python passes the code object to exec or eval. The syntax is compile(CodeString,FileName,Kind). CodeString is a string of Python code. FileName is a string describing the code’s origin; if Python read the code from a file, FileName should be the name of that file. Kind is a string describing the code: ✦ “exec” — one or more executable statements ✦ “eval” — a single expression ✦ “single” — a single statement, which is printed upon evaluation if not None Note Multiline expressions should have two trailing newlines in order for Python to pass them to compile or exec. (This requirement is a quirk of Python that may be fixed in a later version.) 97 4807-7 ch06.F 98 5/24/01 8:58 AM Page 98 Part I ✦ The Python Language Summary Program organization helps make code reusable, as well as more easily comprehended. In this chapter you: ✦ Defined functions with variable argument lists. ✦ Organized code into modules and packages. ✦ Compiled and ran Python code on-the-fly. In the next chapter you’ll harness the power of object-oriented programming in Python. ✦ ✦ ✦ 4807-7 ch07.F 5/24/01 8:58 AM Page 99 7 CHAPTER Object-Oriented Python ✦ ✦ ✦ ✦ In This Chapter P ython has been an object-oriented language from day one. Because of this, creating and using classes and objects are downright easy. This chapter helps you become an expert in using Python’s object-oriented programming support. Overview of Object-Oriented Python If you don’t have any previous experience with object-oriented (OO) programming, you may want to consult an introductory course on it or at least a tutorial of some sort so that you have a grasp of the basic concepts. Python’s object-oriented programming support is very straightforward and easy: you create classes (which are something akin to blueprints), and you use them to create instance objects (which are like the usable and finished versions of what the blueprints represent). An instance object (or just “object,” for short) can have any number of attributes, which include data members (variables belonging to that object) and methods (functions belonging to that object that operate on that object’s data). You can create a new class by deriving it from one or more other classes. The new child class, or subclass, inherits the attributes of its parent classes, but it may override any of the parent’s attributes as well as add additional attributes of its own. Overview of objectoriented Python Creating classes and instance objects Deriving new classes from other classes Hiding private data Identifying class membership Overloading standard behaviors Using weak references ✦ ✦ ✦ ✦ 4807-7 ch07.F 100 5/24/01 8:58 AM Page 100 Part I ✦ The Python Language Creating Classes and Instance Objects Below is a sample class and an example of its use: >>> class Wallet: “Where does my money go?” walletCnt = 0 def __init__(self,balance=0): self.balance = balance Wallet.walletCnt += 1 def getPaid(self,amnt): self.balance += amnt self.displayBalance() def spend(self,amnt): self.balance -= amnt self.displayBalance() def displayBalance(self): print ‘New balance: $%.2f’ % self.balance The class statement creates a new class definition (which is itself also an object) called Wallet. The class has a documentation string (which you can access via Wallet.__doc__), a count of all the wallets in existence, and three methods. You declare methods like normal functions with the exception that the first argument to each method is self, the conventional Python name for the instance of the object (it has the same role as the this object in Java or the this pointer in C++). Python adds the self argument to the list for you; you don’t need to include it when you call the methods. The first method is a special constructor or initialization method that Python calls when you create a new instance of this class. Note that it accepts an initial balance as an optional parameter. The other two methods operate on the wallet’s current balance. Note All methods must operate on an instance of the object (if you’re coming from C++, there are no “static methods”). Objects can have two types of data members: walletCnt, which is outside of any method of the class, is a class variable, which means that all instances of the class share it. Changing its value in one instance (or in the class definition itself) changes it everywhere, so any wallet can use walletCnt to see how many wallets you’ve created: >>> myWallet = Wallet(); yourWallet = Wallet() >>> print myWallet.walletCnt, yourWallet.walletCnt 2,2 4807-7 ch07.F 5/24/01 8:58 AM Page 101 Chapter 7 ✦ Object-Oriented Python The other type of data member is an instance variable, which is one defined inside a method and belongs only to the current instance of the object. The balance member of Wallet is an instance variable. So that you’re never confused as to what belongs to an object, you must use the self parameter to refer to its attributes whether they are methods or data members. Creating instance objects To create an instance of a class, you “call” the class and pass in whatever arguments its __init__ method accepts, and you access the object’s attributes using the dot operator: >>> w = Wallet(50.00) >>> w.getPaid(100.00) New balance$150.00 >>> w.spend(25.0) New balance $125.00 >>> w.balance 125.0 An instance of a class uses a dictionary (named __dict__) to hold the attributes and values specific to that instance. Thus object.attribute is the same as object.__dict__[‘attribute’]. Additionally, each object and class has a few other special members: >>> Wallet.__name__ # Class name ‘Wallet’ >>> Wallet.__module__ # Module in which class was defined ‘__main__’ >>> w.__class__ # Class definition for this object <class __main__.Wallet at 010C1CFC> >>> w.__doc__ # Doc string ‘Where does my money go?’ More on accessing attributes You can add, remove, or modify attributes of classes and objects at any time: >>> w.owner = ‘Dave’ # Add an ‘owner’ attribute. >>> w.owner = ‘Bob’ # Bob stole my wallet. >>> del w.owner # Remove the ‘owner’ attribute. Modifying a class definition affects all instances of that class: >>> Wallet.color = ‘blue’ # Add a class variable. >>> w.color ‘blue’ 101 4807-7 ch07.F 102 5/24/01 8:58 AM Page 102 Part I ✦ The Python Language Note that when an instance modifies a class variable without naming the class, it’s really only creating a new instance attribute and modifying it: >>> w.color = ‘red’ # You might think you’re changing the >>> Wallet.color # class variable, but you’re not! ‘blue’ Because you can modify a class instance at any time, a class is a great way to mimic a more flexible version of a C struct: Tip class myStruct: pass z = myStruct() z.whatever = ‘howdy’ Instead of using the normal statements to access attributes, you can use the getattr(obj, name[, default]), hasattr(obj,name), setattr(obj,name,value), and delattr(obj, name) functions: >>> hasattr(w,’color’) 1 >>> getattr(w,’color’) ‘red’ >>> setattr(w,’size’,10) >>> delattr(w,’color’) # Does w.color exist? # Return w.color please. # Same as ‘w.size = 10’. # Same as ‘del w.color’. As with functions, methods can also have data attributes. The method of the following class, for example, includes an HTML docstring for use with a Web browserbased class browser: >>> class SomeClass: ... def deleteFiles(self, mask): ... os.destroyFiles(mask) ... deleteFiles.htmldoc = ‘<bold>Use with care!</bold>’ >>> hasattr(SomeClass.deleteFiles,’htmldoc’) 1 >>> SomeClass.deleteFiles.htmldoc ‘<bold>Use with care!</bold>’ CrossReference You can read more about function attributes in Chapter 6. New Feature Method attributes are new in Python 2.1. Deriving New Classes from Other Classes Instead of starting from scratch, you can create a class by deriving it from a preexisting class by listing the parent class in parentheses after the new class name: 4807-7 ch07.F 5/24/01 8:58 AM Page 103 Chapter 7 ✦ Object-Oriented Python >>> class GetAwayVehicle: ... topSpeed = 200 ... def engageSmokeScreen(self): ... print ‘<Cough!>’ ... def fire(self): ... print ‘Bang!’ >>> class SuperMotorcycle(GetAwayVehicle): ... topSpeed = 250 ... def engageOilSlick(self): ... print ‘Enemies destroyed.’ ... def fire(self): ... GetAwayVehicle.fire(self) # Use method in parent. ... print ‘Kapow!’ The child class (SuperMotorcycle) inherits the attributes of its parent class (GetAwayVehicle), and you can use those attributes as if they were defined in the child class: >>> myBike = SuperMotorcycle() >>> myBike.engageSmokeScreen() <Cough!> >>> myBike.engageOilSlick() Enemies destroyed. A child class can override data members and methods from the parent. For example, the value of topSpeed in child overrides the one in the parent: >>> myBike.topSpeed 250 The fire method doesn’t just override the original version in the parent, but it also calls the parent version too: >>> myBike.fire() Bang! Kapow! Multiple inheritance When deriving a new child class, you aren’t limited to a single parent class: >>> class Glider: ... def extendWings(self): ... print ‘Wings ready!’ ... def fire(self): ... print ‘Bombs away!’ >>> class FlyingBike(Glider,SuperMotorcycle): ... pass 103 4807-7 ch07.F 104 5/24/01 8:58 AM Page 104 Part I ✦ The Python Language In this case a FlyingBike enjoys all the benefits of being both a Glider and a SuperMotorcycle (which is also a GetAwayVehicle). When searching for an attribute not defined in a child class, Python does a left-to-right, depth-first search on the base classes until it finds a match. If you fire with a FlyingBike, it drops bombs, because first and foremost, it’s a Glider: >>> betterBike = FlyingBike() >>> betterBike.fire() Bombs away! You can get a list of base classes using the __bases__ member of the class definition object: >>> for base in FlyingBike.__bases__: ... print base __main__.Glider # __main__ is the module in __main__.SuperMotorcycle # which you defined the class. Just because multiple inheritance lets you have child classes with many parents (and other strange class genealogies) doesn’t always mean it’s a good idea. If your design calls for more than a few direct parent classes, chances are you need a new design. Tip Multiple inheritance really shines with mix-ins, which are small classes that override a portion of another class to customize behavior. The SocketServer module, for example, defines a generic TCP socket server class called TCPServer that handles a single connection at a time. The module also provides several mix-ins, including ForkingMixIn and ThreadingMixIn that provide their own process_request method. This lets the TCPServer code remain simple while making it easy to create multi-threaded or multi-process socket server classes: class ThreadingServer(ThreadingMixIn, TCPServer): pass class ForkingServer(ForkingMixIn, TCPServer): pass Furthermore, you can use the same threading and forking code to create other types of servers: class ThreadingUDPServer(ThreadingMixIn, UDPServer): pass CrossReference See Chapter 15 for information on networking and socket servers. Creating a custom list class The UserList class (in the UserList module) provides a listlike base class that you can extend to suit your needs. UserList accepts a list to use as an initializer, and internally you can access the actual Python list via the data member. The following example creates an object that behaves like an ordinary list except that it also provides a method to randomly reorder the items in the list: 4807-7 ch07.F 5/24/01 8:58 AM Page 105 Chapter 7 ✦ Object-Oriented Python >>> >>> >>> ... ... ... ... ... >>> >>> [1, >>> [5, import UserList, whrandom from whrandom import randint class MangleList(UserList.UserList): def mangle(self): data = self.data count = len(data) for i in range(count): data.insert(randint(0,count-1),data.pop()) z = MangleList([1,2,3,4,5]) z.mangle() ; print z 3, 5, 4, 2] z.mangle() ; print z 4, 1, 2, 3] Creating a custom string class You can also create your own custom string behaviors using the UserString class in the UserString module. As with UserLists and lists, a UserString looks and acts a lot like a normal string object: >>> from UserString import * >>> s = UserString(‘Goal!’) >>> s.data # Access the underlying Python string. ‘Goal!’ >>> s ‘Goal!’ >>> s.upper() ‘GOAL!’ >>> s[2] ‘a’ Of course, the whole point of having the UserString class is so that you can subclass it. As an example, the UserString module also provides the MutableString class: >>> m = MutableString(‘2 + 2 is 5’) >>> m ‘2 + 2 is 5’ >>> m[9] = ‘4’ >>> m ‘2 + 2 is 4’ CrossReference MutableString does its magic by overriding (among other things) the __setitem__ method, which is a special method Python calls to handle the index-based assignment in the example above. We cover __setitem__ and other special methods in the “Overloading Standard Behaviors” section later in this chapter. 105 4807-7 ch07.F 106 5/24/01 8:58 AM Page 106 Part I ✦ The Python Language Creating a custom dictionary class And finally, Python also has the UserDict class in the UserDict module so that you can create your own subclasses of dictionaries: >>> >>> >>> {3: >>> {3: >>> 1 from UserDict import * d = UserDict({1:’one’,2:’two’,3:’three’}) d ‘three’, 2: ‘two’, 1: ‘one’} d.data ‘three’, 2: ‘two’, 1: ‘one’} d.has_key(3) The following example creates a dictionary object that, instead of raising an exception, returns None if you try to use a nonexistent key: >>> from UserDict import * >>> class NoFailDict(UserDict): ... def __getitem__(self,key): ... try: ... value = self.data[key] ... except KeyError: ... value = None ... return value >>> q = NoFailDict({‘orange’:’0xFF6432’,’yellow’:’0xFFFF00’}) >>> print q[‘orange’] 0xFF6432 >>> print q[‘blue’] None Hiding Private Data In other object-oriented languages such as C++ or Java, an object’s attributes may or may not be visible outside the class definition (you can say a member is public, private, or protected). Such conventions help keep the implementation details hidden and force you to work with objects through well-defined interfaces. Python, however, takes more of a minimalist approach and assumes you know what you’re doing when you try to access attributes of an object. Python programs usually have smaller and more straightforward implementations than their C++ or Java counterparts, so private data members aren’t as useful or necessary (although if you’re accustomed to using them you may feel a little “overexposed” for awhile). Having said that, there still may come a time when you really don’t want users of an object to have access to the implementation, or maybe you have some members in a base class that you don’t want children classes to access. For these cases, you can name attributes with a double underscore prefix, and those attributes will not be directly visible to outsiders: 4807-7 ch07.F 5/24/01 8:58 AM Page 107 Chapter 7 ✦ Object-Oriented Python >>> class FooCounter: ... __secretCount = 0 ... def foo(self): ... self.__secretCount += 1 ... print self.__secretCount >>> foo = FooCounter() >>> foo.foo() 1 >>> foo.foo() 2 >>> foo.__secretCount Traceback (innermost last): File “<interactive input>”, line 1, in ? AttributeError: ‘FooCounter’ instance has no attribute ‘__secretCount’ Python protects those members by internally changing the name to include the class name. You can be sneaky and thwart this convention (valid reasons for doing this are rare!) by referring to the attribute using its mangled name: _className__attrName: >>> foo._FooCounter__secretCount 2 Identifying Class Membership Class definitions and instance objects each have their own data type: >>> class Tree: ... pass >>> class Oak(Tree): ... pass >>> seedling = Oak() >>> type(seedling); type(Oak) <type ‘instance’> <type ‘class’> CrossReference Refer to Chapter 4 for more on identifying the data types of an object. Because the type is instance or class, all class definitions have the same type and all instance objects have the same type. If you want to see if an object is an instance of a particular class, you can use the isinstance(obj,class) function: >>> isinstance(seedling,Oak) 1 >>> isinstance(seedling,Tree) # True because an Oak is a Tree. 1 The issubclass(class,class) checks to see if one class is a descendent of another: 107 4807-7 ch07.F 108 5/24/01 8:58 AM Page 108 Part I ✦ The Python Language >>> issubclass(Oak,Tree) 1 >>> issubclass(Tree,Oak) 0 You can also retrieve the string name for a class using the __name__ member: >>> seedling.__class__.__name__ ‘Oak’ >>> seedling.__class__.__bases__[0].__name__ ‘Tree’ Tip Your programs will often be more flexible if, instead of depending on an object’s type or class, they check to see if an object has a needed attribute. This enables you and others to use your code with data types that you didn’t necessarily consider when you wrote it. For example, instead of checking to see if an object passed in is a file before you write to it, just check for a write method, and if present, use it. Later you may find it useful to call the same routine passing in some other object that also has a write method. “Using Filelike Objects” in Chapter 8 covers this theme in more detail. Overloading Standard Behaviors Suppose you’ve created a Vector class to represent two-dimensional vectors. What happens when you use the plus operator to add them? Most likely Python will yell at you. You could, however, define the __add__ method in your class to perform vector addition, and then the plus operator would behave: >>> class Vector: ... def __init__(self,a,b): ... self.a = a ... self.b = b ... def __str__(self): ... return ‘Vector(%d,%d)’ % (self.a,self.b) ... def __add__(self,other): ... return Vector(self.a+other.a,self.b+other.b) >>> v1 = Vector(2,10) >>> v2 = Vector(5,-2) >>> print v1 + v2 Vector(7,8) Not only do users now have an intuitive way to add two vectors (much better than having them call some clunky function directly), but vectors also display themselves nicely when converted to strings (thanks to the __str__ method). The operator module defines many functions for which you can overload or define new behavior when used with your classes. The following sections describe these functions and how to use them. 4807-7 ch07.F 5/24/01 8:58 AM Page 109 Chapter 7 ✦ Object-Oriented Python Note that some functions have two or even three very similar versions. For example, in the numeric operators, you can create an __add__ function, an __iadd__ function, and an __radd__ function all for addition. The first is to implement normal addition (x + y), the second for in-place addition (x += y), and the third for x + y when x does not have an __add__ method (so Python calls y.__radd(x) instead). If you don’t define in-place operator methods, Python checks for an overloaded version of the normal operator (for example, if you don’t define __iadd__, x += y causes Python to still call __add__ if defined). For simplicity, it’s best to leave the in-place operators undefined unless your class in some way benefits from special in-place processing (such as a huge matrix class that could save memory by performing addition in place). Overloading basic functionality Table 7-1 lists some generic functionality that you can override in your own classes. Table 7-1 Base Overloading Methods Method Sample Call __init__ (self[, args...]) obj = className(args) __del__ (self) del obj __call__ (self[, args...]) , callable function obj(5) __getattr__ (self, name) obj.foo __setattr__ (self, name, value) obj.foo = 5 __delattr__ (self, name) del obj.foo __repr__ (self) obj or repr(obj) __str__ (self) str(obj) __cmp__ (self, x) cmp(obj,x) __lt__(self, x) obj < x __le__(self,x) obj <= x __eq__(self,x) obj == x __ne__(self,x) obj != x __gt__(self, x) obj > x __ge__(self,x) obj >= x __hash__ (self) hash(obj) __nonzero__ (self) nonzero(obj) 109 4807-7 ch07.F 110 5/24/01 8:58 AM Page 110 Part I ✦ The Python Language Note that with the del statement, Python won’t call the __del__ method unless the object’s reference count is finally 0. Python invokes the __call__ method any time someone tries to treat an instance of your object as a function. Users can test for “callability” using the callable(obj) function, which tries to determine if the object is callable (callable may return true and be wrong, but if it returns false, the object really isn’t callable). Python calls the __getattr__ function only after a search through the instance dictionary and base classes comes up empty-handed. Your implementation should return the desired attribute or raise an AttributeError exception. If __setattr__ needs to assign a value to an instance variable, be sure to assign it to the instance dictionary instead (self.__dict__[name] = val) to prevent a recursive call to __setattr__. If your class has a __setattr__ method, Python always calls it to set member variable values, even if the instance dictionary already contains the variable being set. The hash and cmp functions are closely related: if you do not implement __cmp__, you should not implement __hash__. If you provide a __cmp__ but no __hash__, then instances of your object can’t act as dictionary keys (which is correct if your objects are mutable). Hash values are 32-bit integers, and two instances that are considered equal should also return the same hash value. The nonzero function performs truth value testing, so your implementation should return 0 or 1. If not implemented, Python looks for a __len__ implementation to use, and if not found, then all instances of your object will be considered “true.” You use the __lt__, __gt__, and other methods to implement support for rich comparisons where you have more complete control over how objects behave during different types of comparisons. If present, Python calls any of these methods before looking for a __cmp__ method. The following example prints a message each time Python calls a comparison function so you can see what happens: >>> class Simple: ... def __cmp__(self, obj): ... print ‘__cmp__’ ... return 1 ... def __lt__(self, obj): ... print ‘__lt__’ ... return 0 >>> s = Simple() >>> s < 5 __lt__ # Python uses rich comparisons first. 0 >>> s > 5 __cmp__ # Uses __cmp__ if there are no rich comparison methods. 1 4807-7 ch07.F 5/24/01 8:58 AM Page 111 Chapter 7 ✦ Object-Oriented Python Your rich comparison methods can return NotImplemented to tell Python that you don’t want to handle a particular comparison. For example, the following class implements an equality method that works on integers. If the object to which it is comparing isn’t an integer, it tells Python to figure out the comparison result on its own: >>> class MyInt: ... def __init__(self, val): ... self.val = val ... def __eq__(self, obj): ... print ‘__eq__’ ... if type(obj) != type(0): ... print ‘Skipping’ ... return NotImplemented ... return self.val == obj >>> m = MyInt(16) >>> m == 10 __eq__ 0 >>> m == ‘Hi’ __eq__ Skipping 0 Tip New Feature Although __cmp__ methods must return an integer to represent the result of the comparison, rich comparison methods can return data of any type or raise an exception if a particular comparison is invalid or meaningless. Rich comparisons are new in Python 2.1. Overloading numeric operators By overloading the numeric operators methods, your classes can correctly respond to operators like +, -, and so on. Note that Python calls the right-hand side version of operators (for example, __radd__) if the left-hand operator doesn’t have a corresponding method defined (__add__): >>> class Add: ... def __init__(self,val): ... self.val = val ... def __add__(self,obj): ... print ‘add’,obj ... return self.val + obj ... def __radd__(self,obj): ... print ‘radd’,obj ... return self.val + obj >>> a = Add(10) >>> a <__main__.Add instance at 00E5D354> >>> a + 5 # Calls a.__add__(5). 111 4807-7 ch07.F 112 5/24/01 8:58 AM Page 112 Part I ✦ The Python Language add 5 15 >>> 5 + a # Calls a.__radd__(5). radd 5 15 Table 7-2 lists the mathematic operations (and the right-hand and in-place variants) that you can overload and examples of how to invoke them. Table 7-2 Numeric Operator Methods Method Sample Call __add__ (self, obj), __radd__, __iadd__ obj + 10.5 __sub__ (self, obj), __rsub__, __isub__ obj – 16 __mul__ (self, obj), __rmul__, __imul__ obj * 5.1 __div__ (self, obj), __rdiv__, __idiv__ obj / 15 __mod__ (self, obj), __rmod__, __imod__ obj % 2 __divmod__ (self, obj), __rdivmod__ divmod(obj,3) __pow__ (self, obj[, modulo]), __rpow__(self,obj) pow(obj,3) __neg__ (self) -obj __pos__ (self) +obj __abs__ (self) abs(obj) __invert__ (self) ~obj Overloading sequence and dictionary operators If you create your own sequence or mapping data type, or if you just like those nifty bracket operators, you can overload the sequence operators with the methods listed in Table 7-3. 4807-7 ch07.F 5/24/01 8:58 AM Page 113 Chapter 7 ✦ Object-Oriented Python Table 7-3 Sequence and Dictionary Operator Methods Method Sample Call __len__ (self) len(obj) __getitem__ (self, key) obj[‘cheese’] __setitem__ (self, key, value) obj[5] = (2,5) __delitem__ (self, key) del obj[‘no’] __setslice__ (self, i, j, sequence) obj[1:7] = ‘Fellow’ __delslice__ (self, i, j) del obj[5:7] __contains__(self,obj) x in obj This class overrides the slice operator to provide an inefficient way to create a list of numbers: >>> ... ... ... ... ... >>> >>> [2, >>> [2, class DumbRange: def __getitem__(self,slice): step = slice.step if step is None: step = 1 return range(slice.start,slice.stop+1,step) d = DumbRange() d[2:5] 3, 4, 5] d[2:10:2] # Extended (step) slicing! 4, 6, 8, 10] The argument to __getitem__ is either an integer or a slice object. Slice objects have start, stop, and step attributes, so your class can support the extended slicing shown in the example. If the key passed to __getitem__ is of the wrong type, your implementation should raise the TypeError exception, and the slice methods should reject invalid indices by raising the IndexError exception. If your __getitem__ method raises IndexError on an invalid index, Python can iterate over object instances as if they were sequences. The following class behaves like a range object with a user-supplied step, but it limits itself to only 6 iterations: 113 4807-7 ch07.F 114 5/24/01 8:58 AM Page 114 Part I ✦ The Python Language >>> class Stepper: ... def __init__(self, step): ... self.step = step ... def __getitem__(self, index): ... if index > 5: ... raise IndexError ... return self.step * index >>> s = Stepper(3) >>> for i in s: ... print i 0 # Python calls __getitem__ with index=0 3 6 9 12 15 # Python stops after a __getitem__call raises an exception Overloading bitwise operators The bitwise operators let your classes support operators such as << and xor: >>> class Vector2D: ... def __init__(self,i,j): ... self.i = i ... self.j = j ... def __lshift__(self,x): ... return Vector2D(self.i << x, self.j << x) ... def __repr__(self): ... return ‘Vector2D(%s,%s)’ % (self.i,self.j) >>> v1 = Vector2D(5,2) >>> v1 << 2 Vector2D(20,8) Table 7-4 lists the methods you define to overload the bitwise operators. Table 7-4 Bitwise Operator Methods Method Sample Call __lshift__ (self, obj), __rlshift__, __ilshift__ obj << 3 __rshift__ (self, obj), __rrshift__, __irshift__ obj >> 1 __and__ (self, obj), __rand__, __iand__ obj & 17 __or__ (self, obj), __ror__, __ior__ obj | otherObj __xor__ (self, obj), __rxor__, __ixor__ obj ^ 0xFE 4807-7 ch07.F 5/24/01 8:58 AM Page 115 Chapter 7 ✦ Object-Oriented Python Overloading type conversions By overloading type conversion methods, you can convert your object to different data types as needed: >>> class Five: ... def __int__(self): ... return 5 >>> f = Five() >>> int(f) 5 Python calls these methods when you pass an object to one of the type conversion routines. Table 7-5 lists the methods, sample Python code that would invoke them, and sample output they might return. Table 7-5 Type Conversion Methods Method Sample Call Sample Output __int__(self) int(obj) 53 __long__(self) long(obj) 12L __float__(self) float(obj) 3.5 __complex__(self) complex(obj) 2 + 3j __oct__(self) oct(obj) ‘012’ __hex__(self) hex(obj) ‘0xFE’ Python calls the __coerce__(self, obj) method, if present, to coerce two numerical types into a common type before applying an arithmetic operation. Your implementation should return a 2-item tuple containing self and obj converted to a common numerical type or None if you don’t support that conversion. Using Weak References Like many other high-level languages, Python uses a form of garbage collection to automatically destroy objects that are no longer in use. Each Python object has a reference count that tracks how many references to that object exist; when the reference count is 0, then Python can safely destroy the object. While reference counting saves you quite a bit of error-prone memory management work, there can be times when you want a weak reference to an object, or a reference that doesn’t prevent Python from garbage collecting the object if no other 115 4807-7 ch07.F 116 5/24/01 8:58 AM Page 116 Part I ✦ The Python Language references exist. With the weakref module, you can create weak references to objects, and Python will garbage collect an object if its reference count is 0 or if the only references that exist are weak references. New Feature The weakref module is new in Python 2.1. Creating weak references You create a weak reference by calling ref(obj[, callback]) in the weakref module, where obj is the object to which you want a weak reference and callback is an optional function to call when Python is about to destroy the object because no strong references to it remain. The callback function takes a single argument, the weak reference object. Once you have a weak reference to an object, you can retrieve the referenced object by calling the weak reference. The following example creates a weak reference to a socket object: >>> ref = weakref.ref(a) >>> from socket import * >>> import weakref >>> s = socket(AF_INET,SOCK_STREAM) >>> ref = weakref.ref(s) >>> s <socket._socketobject instance at 007B4A94> >>> ref <weakref at 0x81195c; to ‘instance’ at 0x7b4a94> >>> ref() # Call it to access the referenced object. <socket._socketobject instance at 007B4A94> Once there are no more references to an object, calling the weak reference returns None because Python has destroyed the object. Note Most objects are not accessible through weak references. The getweakrefcount(obj) and getweakrefs(obj) functions in the weakref module return the number of weak references and a list of referents for the given object. Weak references can be useful for creating caches of objects that are expensive to create. For example, suppose you are building a distributed application that sends messages between computers using connection-based network sockets. In order to reuse the socket connections without keeping unused connections open, you decide to keep a cache of open connections: 4807-7 ch07.F 5/24/01 8:58 AM Page 117 Chapter 7 ✦ Object-Oriented Python import weakref from socket import * socketCache = {} def getSocket(addr): ‘Returns an open socket object’ if socketCache.has_key(addr): sock = socketCache[addr]() if sock: # Return the cached socket. return sock # No socket found, so create and cache a new one. sock = socket(AF_INET,SOCK_STREAM) sock.connect(addr) socketCache[addr] = weakref.ref(sock) return sock In order to send a message to a remote computer, your program calls getSocket to obtain a socket object. If a connection to the given address doesn’t already exist, getSocket creates a new one and adds a weak reference to the cache. When all strong references to a given socket are gone, Python destroys the socket object and the next request for the same connection will cause getSocket to create a new one. The mapping([dict[,weakkeys]]) function in the weakref module returns a weak dictionary (initializing it with the values from the optional dictionary dict). If weakkeys is 0 (the default), the dictionary automatically removes any entry whose value no longer has any strong references to it. If weakkeys is nonzero, the dictionary automatically removes entries whose keys no longer have strong references. Creating proxy objects Proxy objects are weak reference objects that behave like the object they reference so that you don’t have to first call the weak reference to access the underlying object. Create a proxy by calling weakref’s proxy(obj[, callback]) function. You use the proxy object as if it was the actual object it references: >>> from socket import * >>> import weakref >>> s = socket(AF_INET,SOCK_STREAM) >>> ref = weakref.proxy(s) >>> s <socket._socketobject instance at 007E4874> >>> ref # It looks like the socket object. <socket._socketobject instance at 007E4874> >>> ref.close() # The object’s methods work too. 117 4807-7 ch07.F 118 5/24/01 8:58 AM Page 118 Part I ✦ The Python Language The callback parameter has the same purpose as the ref function. After Python deletes the referenced object, using the proxy results in a weakref.ReferenceError: >>> del s >>> ref Traceback (most recent call last): File “<stdin>”, line 1, in ? Note This example assumes that Python immediately destroys the object once the last string is gone. While true of the current garbage collector implementation, future versions may be different. Summary Python fully supports object-oriented programming while requiring minimal effort from you, the programmer. In this chapter you: ✦ Created your own custom classes. ✦ Derived new classes from other classes. ✦ Extended built-in data types like strings and lists. ✦ Defined custom behaviors for operations on your classes. In the next chapter you learn to create programs that interact with the user and store and retrieve data. ✦ ✦ ✦ 4807-7 ch08.F 5/24/01 8:58 AM Page 119 8 CHAPTER Input and Output ✦ ✦ ✦ ✦ In This Chapter I n order to be useful, most programs must interact with the “outside world” in some way. This chapter introduces Python’s functions for reading and writing files, printing to the screen, and retrieving keyboard input from the user. Printing to the Screen The simplest way to produce output is using the print statement, which converts the expressions you pass it to a string and writes the result to standard output, which by default is the screen or console. You can pass in zero or more expressions, separated by commas, between which print inserts a space: Printing to the screen Accessing keyboard input Opening, closing, and positioning files Writing files Reading files Accessing standard I/O Using filelike objects >>> print ‘It is’,5+7,’past’,3 It is 12 past 3 Before printing each expression, print converts any nonstring expressions using the str function. If you don’t want the spaces between expressions, you can do the conversions yourself: >>> a = 5.1; z = (0,5,10) >>> print ‘(%0.1f + %0.1f) = \n%0.1f’ % (a,a,a*2) (5.1 + 5.1) = 10.2 >>> print ‘Move to ‘+str(z) Move to (0, 5, 10) >>> print ‘Two plus ten is ‘+2+10 #  is the same as repr. Two plus ten is 12 CrossReference Chapter 3 covers converting different data types to strings. ✦ ✦ ✦ ✦ 4807-7 ch08.F 120 5/24/01 8:58 AM Page 120 Part I ✦ The Python Language If you append a trailing comma to the end of the statement, print won’t move to the next line: >>> def addEm(x,y): ... print x, ... print ‘plus’, ... print y, ... print ‘is’, ... print x+y >>> addEm(5,2) 5 plus 2 is 7 Python uses the softspace attribute of stdout (stdout is in the sys module) to track whether it needs to output a space before the next item to be printed. You can use this feature to manually shut off the space that would normally appear due to using a comma: >>> import sys >>> def joinEm(a,b): ... print a, ... sys.stdout.softspace = 0 ... print b ... >>> joinEm(‘Thanks’,’giving’) Thanksgiving An extended form of the print statement lets you redirect output to a file instead of standard output: >>> print >> sys.stderr File not found New Feature ,”File not found” The extended form of print was introduced in Python 2.0. Any filelike object will do, as you will see in the “Using Filelike Objects” section later in this chapter. Accessing Keyboard Input Going the other direction, Python provides two built-in functions to retrieve a line of text from standard input, which by default comes from the user’s keyboard. The examples in this section use italics for text you enter in response to the prompts. raw_input The raw_input([prompt]) function reads one line from standard input and returns it as a string (removing the trailing newline): 4807-7 ch08.F 5/24/01 8:58 AM Page 121 Chapter 8 ✦ Input and Output >>> s = raw_input() Uncle Gomez >>> print s Uncle Gomez You can also specify a prompt for raw_input to use while waiting for user input: >>> s = raw_input(‘Command: ‘) Command: launch missiles >>> print ‘Ignoring command to’,s Ignoring command to launch missiles If raw_input encounters the end of file, it raises the EOFError exception. input The input([prompt]) function is equivalent to raw_input, except that it assumes the input is a valid Python expression and returns the evaluated result to you: >>> input(‘Enter some Python: ‘) Enter some Python: [x*5 for x in range(2,10,2)] [10, 20, 30, 40] Note that input isn’t at all error-proof. If the expression passed in is bogus, input raises the appropriate exception, so be wary when using this function in your programs. CrossReference Chapter 38 covers the readline module for UNIX systems. If enabled, this module adds command history tracking and completion to these input routines (and Python’s interactive mode as well). CrossReference You may have noticed that you can’t read one character at a time (instead you have to wait until the user hits Enter). To read a single character on UNIX systems (or any system with curses support), you can use the getch function in the curses module (Chapter 22). For Windows systems, you can use the getch function in the msvcrt module (Chapter 37). Opening, Closing, and Positioning Files The remaining sections in this chapter show you how to use files in your programs. CrossReference Part II of this book — “Files, Data Storage, and Operating System Services” — covers many additional features you’ll find useful when using files. 121 4807-7 ch08.F 122 5/24/01 8:58 AM Page 122 Part I ✦ The Python Language open Before you can read or write a file, you have to open it using Python’s built-in open(name[, mode[, bufsize]]) function: >>> f = open(‘foo.txt’,’wt’,1) # Open foo.txt for writing. >>> f <open file ‘foo.txt’, mode ‘wt’ at 010C0488> The mode parameter is a string (similar to the mode parameter in C’s fopen function) and is explained in Table 8-1. Table 8-1 Mode Values for open Value Description R Opens for reading. W Creates a file for writing, destroying any previous file with the same name. A Opens for appending to the end of the file, creating a new one if it does not already exist. r+ Opens for reading and writing (the file must already exist). w+ Creates a new file for reading and writing, destroying any previous file with the same name. a+ Opens for reading and appending to the end of the file, creating a new file if it does not already exist. If you do not specify a mode string, open uses the default of ‘r’. To the end of the mode string you can append a ‘t’ to open the file in text mode or a ‘b’ to open it in binary mode: >>> f = open(‘somepic.jpg’,’w+b’) # Open/create binary file. If you omit the optional buffer size parameter (or pass in a negative number), open uses the system’s default buffering. A value of 0 is for unbuffered reading and writing, a value of 1 buffers data a line at a time, and any other number tells open to use a buffer of that size (some systems round the number down to the nearest power of 2). If for any reason the function call fails (file doesn’t exist, you don’t have permission), open raises the IOError exception. CrossReference The os module (Chapter 10) provides the fdopen, popen, popen2, and popen3 functions as additional ways to obtain file objects. You can also create a filelike object wrapping an open socket with the socket.makefile function (Chapter 15). 4807-7 ch08.F 5/24/01 8:58 AM Page 123 Chapter 8 ✦ Input and Output File object information Once you have a file object, you can use the name, fileno(), isatty(), mode, and closed methods and attributes to get different information about the object’s status: >>> f = open(‘foo.txt’,’wt’) >>> f.mode # Get the mode used to create the file object. ‘wt’ >>> f.closed # Boolean: has the file been closed already? 0 >>> f.name # Get the name of the file. ‘foo.txt’ >>> f.isatty() # Is the file connected to a terminal? 0 >>> f.fileno() # Get the file descriptor number. 0 CrossReference With the file descriptor returned by the fileno method you can call read and other functions in the os module (Chapter 10). close The close() method of a file object flushes any unwritten information and closes the file object, after which no more writing can occur: >>> f = open(‘foo.txt’,’wt’) >>> f.write(‘Foo!!’) >>> f.close() File position The tell() method tells you the current position within the file (in other words, the next read or write will occur at that many bytes from the beginning of the file): >>> f = open(‘tell.txt’,’w+’) # Open for reading AND writing. >>> f.write(‘BRAWN’) # Write 5 characters. >>> f.tell() 5 # Next operation will occur at offset 5 (starting from 0). The seek(offset[, from]) method changes the current file position. The following example continues the previous one by seeking to an earlier point in the file, overwriting some of the previous data, and then reading the entire file: >>> f.seek(2) # Move to offset 2 from the start of the file. >>> f.write(‘AI’) >>> f.seek(0) # Now move back to the beginning. >>> f.read() # Read everything from here on. ‘BRAIN’ 123 4807-7 ch08.F 124 5/24/01 8:58 AM Page 124 Part I ✦ The Python Language You can pass an additional argument to seek to change how it interprets the first parameter. Use a value of 0 (which is the default) to seek from the beginning of the file, 1 to seek relative to the current position, and 2 to seek relative to the end of the file. Using the previous example: >>> f.seek(-4,2) # Seek 4 bytes back from the end of the file. >>> f.read() ‘RAIN’ Caution When you open a file in text mode on a Microsoft Windows system, Windows silently and automatically translates newline characters (‘\n’) into ‘\r\n’ instead. In such cases use seek only with an offset of 0 (to seek to the beginning or the end of the file) or to seek from the beginning of the file with an offset returned from a previous call to tell. Writing Files The write(str) method writes any string to an open file (keep in mind that Python strings can have binary data and not just text). Notice that write does not add a newline character (‘\n’) to the end of the string: >>> f = open(‘snow.txt’,’w+t’) >>> f.write(‘Once there was a snowman,\nsnowman, snowman.\n’) >>> f.seek(0) # Move to the beginning of the file. >>> print f.read() Once there was a snowman, snowman, snowman. The writelines(list) method takes a list of strings to write to a file (as with write, it does not append newline characters to the end of each string you pass in). Continuing the previous example: >>> lines = [‘Once there was a snowman ‘,’tall, tall,’,’tall!’] >>> f.writelines(lines) >>> f.seek(0) >>> print f.read() Once there was a snowman, snowman, snowman. Once there was a snowman tall, tall, tall! Tip Like stdout, all file objects have a softspace attribute (covered in the first section of this chapter) telling whether or not Python should insert a space before writing out the next piece of data. As with stdout, you can modify this attribute to shut off that extra space. The truncate([offset]) method deletes the contents of the file from the current position until the end of the file: 4807-7 ch08.F 5/24/01 8:58 AM Page 125 Chapter 8 ✦ Input and Output >>> f.seek(10) >>> f.truncate() >>> f.seek(0) >>> print f.read() Once there Optionally you can specify a file position at which to truncate instead of the current file position: >>> f.seek(0) >>> f.truncate(5) >>> print f.read() Once You can also use the flush() method to commit any buffered writes to disk. CrossReference See the pickle, shelve, and struct modules in Chapter 12 for information on writing Python objects to files in such a way that you can later read them back in as valid objects. Reading Files The read([count]) method returns the specified number of bytes from a file (or less if it reaches the end of the file): >>> f = open(‘read.txt’,’w+t’) # Create a file. >>> for i in range(3): ... f.write(‘Line #%d\n’ % i) >>> f.seek(0) >>> f.read(3) # Read 3 bytes from the file. ‘Lin’ If you don’t ask for a specific number of bytes, read returns the remainder of the file: >>> print f.read() e #0 Line #1 Line #2 The readline([count]) method returns a single line, including the trailing newline character if present: >>> f.seek(0) >>> f.readline() ‘Line #0\012’ 125 4807-7 ch08.F 126 5/24/01 8:58 AM Page 126 Part I ✦ The Python Language You can have readline return a certain number of bytes or an entire line (whichever comes first) by passing in a size argument: >>> f.readline(5) ‘Line ‘ >>> f.readline() ‘#1\012’ The readlines([sizehint]) method repeatedly calls readline and returns a list of lines read: >>> f.seek(0) >>> f.readlines() [‘Line #0\012’, ‘Line #1\012’, ‘Line #2\012’] Note Once they reach the end of the file, the read and readline methods return empty strings, and the readlines method returns an empty list. The optional sizehint parameter limits how much data readlines reads into memory instead of reading until the end of the file. When you’re processing the lines of text in a file, you often want to remove the newline characters along with any leading or trailing whitespace. Here’s an easy way to open the file, read the lines, and remove the newlines all in a single step (this example assumes you have the read.txt file from above): >>> [x.strip() for x in open(‘read.txt’).readlines()] [‘Line #0’, ‘Line #1’, ‘Line #2’] # Yay, Python! One drawback to the readlines method is that it reads the entire file into memory before returning it to you as a list (unless you supply a sizehints parameter, in which case you have to call readlines over and over again until the end of the file). The xreadlines works like readlines but reads data into memory as needed: >>> for line in open(‘read.txt’).xreadlines(): ... print line.strip().upper() # Print uppercase version of lines. New Feature The xreadlines function is new in Python 2.1. Accessing Standard I/O The sys module provides three file objects that you can always use: stdin (standard input), stdout (standard output), and stderr (standard error). Most often stdin holds input coming from the user’s keyboard while stdout and stderr print messages to the user’s screen. 4807-7 ch08.F 5/24/01 8:58 AM Page 127 Chapter 8 ✦ Input and Output Note Some IDEs like PythonWin implement their own version of stdin, stdout, input, and so on, so redirecting them may behave differently. When in doubt, try it out from the command line. Routines like input and raw_input read from stdin, and routines like print write to stdout, so an easy way to redirect input and output is to put file objects of your own into sys.stdin and sys.stdout: >>> import sys >>> sys.stdout = open(‘fakeout.txt’,’wt’) >>> print “Now who’s going to the restaurant?” >>> sys.stdout.close() >>> sys.stdout = sys.__stdout__ >>> open(‘fakeout.txt’).read() “Now who’s going to the restaurant?\012” As the example shows, the original values are in the __stdin__, __stdout__, and __stderr__ members of sys; be a good Pythonista and point the variables to their original values when you’re done fiddling with them. Note External programs started via os.system or os.popen do not look in sys.stdin or sys.stdout. As a result, their input and output come from the normal sources, regardless of changes you’ve made to Python’s idea of stdin and stdout. Using Filelike Objects One of the great features of Python is its flexibility with data types, and a neat example of this is with file objects. Many functions or methods require that you pass in a file object, but more often than not you can get away with passing in an object that acts like a file instead. The following example implements a filelike object that reverses the order of anything you write to it and then sends it to the original version of stdout: >>> import sys,string >>> class Reverse: ... def write(self,s): ... s = list(s) ... s.reverse() ... sys.__stdout__.write(string.join(s,’’)) ... sys.__stdout__.flush() Not much of a file object is it? But, you’d be surprised at how often it’ll do the trick: >>> sys.stdout = Reverse() >>> print ‘Python rocks!’ !skcor nohtyP 127 4807-7 ch08.F 128 5/24/01 8:58 AM Page 128 Part I ✦ The Python Language Detecting Redirected Input Suppose you’re writing a nifty utility program that would most often be used in a script where the input would come from piped or redirected input, but you also want to provide more of an interactive mode for other uses. Instead of having to pass in a command line parameter to choose the mode, your program could use the isatty method of sys.stdin to detect it for you. To see this in action, save this tiny program to a file called myutil.py: import sys if sys.stdin.isatty(): print ‘Interactive mode!’ else: print ‘Batch mode!’ Now run it from an MS-DOS or UNIX shell command prompt: C:\temp>python myutil.py Interactive mode! Run it again, this time redirecting a file to stdin using the redirection character (any file works as input — in the example below I chose myutil.py because you’re sure to have it in your directory): C:\temp>python myutil.py < myutil.py Batch mode! Likewise, a more complex (and hopefully more useful) utility could automatically behave differently depending on whether a person or a file was supplying the input. In fact, you can trick most of Python into using your new file object, even when printing error messages: >>> sys.stderr = Reverse() >>> Reverse.foo # This action causes an error. :)tsal llac tnecer tsom( kcabecarT ? ni ,1 enil ,”>nidts<” eliF rorrEetubirttA :oof The point here is that no part of the Python interpreter or the standard libraries has any knowledge of your special file class, nor does it need to. Sometimes a custom class can act like one of a different type even if it’s not derived from a common base class (that is, files and Reverse do not share some common “generic file” superclass). One instance in which this feature is useful is when you’re building GUI-based applications (see Chapter 19) and you want text messages to go to a graphical window instead of to the console. Just write your own filelike class that sends a 4807-7 ch08.F 5/24/01 8:58 AM Page 129 Chapter 8 ✦ Input and Output string to the window, replace sys.stdout (and probably sys.stderr), and magically output goes to the right place, even if some third-party module that is completely ignorant of your trickery generates the output. This flexibility comes in handy at other times too. For example, map lets you pass in the function to apply. The ability to recognize cases where it is both useful and intuitive is a talent worth cultivating. Tip As of Python 2.1, you can create a xreadlines object around any filelike object that implements a readlines method: import xreadlines obj = SomeFileLikeObject() for line in xreadlines.xreadlines(obj): ... do some work ... Summary Whether you’re using files or standard I/O, Python makes handling input and output easy. In this chapter you: ✦ Printed information to the user’s console. ✦ Retrieved input from the keyboard. ✦ Learned to read and write text and binary files. ✦ Used filelike objects in place of actual file objects. In the next chapter you’ll learn to use Python’s powerful string handling features. With them you can easily search strings, match patterns, and manipulate strings in your programs. ✦ ✦ ✦ 129 4807-7 ch08.F 5/24/01 8:58 AM Page 130 4807-7 PO2.F 5/24/01 8:58 AM Page 131 P Files, Data Storage, and Operating System Services A R T II ✦ ✦ ✦ ✦ Chapter 9 Processing Strings and Regular Expressions Chapter 10 Working with Files and Directories Chapter 11 Using Other Operating System Services Chapter 12 Storing Data and Objects Chapter 13 Accessing Date and Time Chapter 14 Using Databases ✦ ✦ ✦ ✦ 4807-7 PO2.F 5/24/01 8:58 AM Page 132 4807-7 ch09.F 5/24/01 8:58 AM Page 133 9 CHAPTER Processing Strings and Regular Expressions S trings are a very common format for data display, input, and output. Python has several modules for manipulating strings. The most powerful of these is the regular expression module. Python also offers classes that can blur the separation between a string (in memory) and a file (on disk). This chapter covers all of the things you can do with strings, ordered from the crucial to the seldom used. Using String Objects String objects provide methods to search, edit, and format the string. Because strings are immutable, these functions do not alter the original string. They return a new string: >>> bob=”hi there” >>> bob.upper() # Say it LOUDER! ‘HI THERE’ >>> bob # bob is immutable, so he didn’t mutate. >>> ‘hi there’ >>> string.upper(bob) # Module function, same as bob.upper ‘HI THERE’ String object methods are also available (except as noted below) as functions in the string module. The corresponding module functions take, as an extra first parameter, the string object to operate on. ✦ ✦ ✦ ✦ In This Chapter Using string objects Using the string module Defining regular expressions Creating and using regular expression objects Using match objects Treating strings as files Encoding text Formatting floating point numbers ✦ ✦ ✦ ✦ 4807-7 ch09.F 134 5/24/01 8:58 AM Page 134 Part II ✦ Files, Data Storage, and Operating System Services CrossReference See Chapter 3 for an introduction to string syntax and formatting in Python. String formatting methods Several methods are available to format strings for printing or processing. You can justify the string within a column, strip whitespace, or expand tabs.ljust(width), center(width), or rjust(width). These methods right-justify, center, or left-justify a string within a column of a given width. They pad the string with spaces as necessary. If the string is longer than width, these methods return the original string. This kind of formatting works in a monospaced font, such as Courier New, where all characters have the same width. In a proportional font, strings with the same length generally have different widths on the screen or printed page. >>> “antici”.ljust(10)+”pation”.rjust(10) ‘antici pation’ lstrip, rstrip, strip lstrip returns a string with leading whitespace removed, rstrip removes trailing whitespace, and strip removes both. “Whitespace” characters are defined in string.whitespace — whitespace characters include spaces, tabs, and newlines. >>> “ hello world “.lstrip() ‘hello world ‘ >>> _.rstrip() # Interpreter trick: _ = last expression value ‘hello world’ expandtab([tabsize]) This method replaces the tab characters in a string with tabsize spaces, and returns the result. The parameter tabsize is optional, defaulting to eight. This method is equivalent to replace(“\t”,” “*tabsize). String case-changing methods You can convert strings to UPPERCASE, lowercase, and more. lower, upper These methods return a string with all characters shifted to lowercase and uppercase, respectively. They are useful for comparing strings when case is not important. capitalize, title, swapcase The method capitalize returns a string with the first character shifted to uppercase. 4807-7 ch09.F 5/24/01 8:58 AM Page 135 Chapter 9 ✦ Processing Strings and Regular Expressions The method title returns a string converted to “titlecase.” Titlecase is similar to the way book titles are written: it places the first letter of each word in uppercase, and all other letters in lowercase. Python assumes that any group of adjacent letters constitutes one word. The method swapcase returns a string where all lowercase characters changed to uppercase, and vice versa. >>> “hello world”.title() ‘Hello World’ >>> “hello world”.capitalize() ‘Hello world’ >>> “hello world”.upper() ‘HELLO WORLD’ String format tests (the is-methods) These methods do not have corresponding functions in the string module. Each returns false for an empty string. For instance, “”.isalpha() returns 0. ✦ isalpha — Returns true if each character is alphabetic. Alphabetic characters are those in string.letters. Returns false otherwise. ✦ isalnum — Returns true if each character is alphanumeric. Alphanumeric characters are those in string.letters or string.digits. Returns false otherwise. ✦ isdigit — Returns true if each character is a digit (from string.digits). Returns false otherwise. ✦ isspace — Returns true if each character is whitespace (from string. whitespace). Returns false otherwise. ✦ islower — Returns true if each letter in the string is lowercase, and the string contains at least one letter. Returns false otherwise. For example: >>> “2 + 2”.islower() # No letters, so test fails! 0 >>> “2 plus 2”.islower() # A-ok! 1 ✦ isupper — Returns true if each letter in the string is uppercase, and the string contains at least one letter. Returns false otherwise. ✦ istitle — Returns true if the letters of the string are in titlecase, and the string contains at least one letter. Returns false otherwise. (See the title formatting method discussed previously for a description of titlecase.) String searching methods Strings offer various methods for simple searching. For more powerful searching, use the regular expressions module (covered later in this chapter). 135 4807-7 ch09.F 136 5/24/01 8:58 AM Page 136 Part II ✦ Files, Data Storage, and Operating System Services find(substring[, firstindex[, lastindex]]) Search for substring within the string. If found, return the index where the first occurrence starts. If not found, return -1. A call to str.find searches the slice str[firstindex:lastindex]. So, the default behavior is to search the whole string, but you can pass values for firstindex and lastindex to limit the search. >>> >>> 0 >>> 12 >>> -1 str=”the rest of the story” str.find(“the”) str.find(“the”,1) # Start search at index 1. str.find(“futplex”) Here are some relatives of find, which you may find useful: ✦ index — Same syntax and effect as find, but raises the exception ValueError if it doesn’t find the substring . ✦ rfind — Same as find, but returns the index of the last occurrence of the substring. ✦ rindex — Same as index, but returns the index of the last occurrence of the substring. startswith(substr[,firstindex[,lastindex]]) Returns true if the string starts with substr. A call to str.startswith compares substr against the slice str[firstindex:lastindex]. You can pass values for firstindex and lastindex to test whether a slice of your string with substr. No equivalent function in the string module. endswith(substr[,firstindex[,lastindex]]) Same as startswith, but tests whether the string ends with substr. The string module contains no equivalent function. count(substr[,firstindex[,lastindex]]) Counts the number of occurrences of substr within a string. If you pass indices, count searches within the slice [firstindex:lastindex]. This example gives the answer to an old riddle: “What happens once today, three times tomorrow, but never in three hundred years?” >>> RiddleStrings=[“today”,”tomorrow”,”three hundred years”] >>> for str in RiddleStrings: print str.count(“o”) ... 1 3 0 4807-7 ch09.F 5/24/01 8:58 AM Page 137 Chapter 9 ✦ Processing Strings and Regular Expressions String manipulation methods Strings provide various methods to replace substrings, split the string on delimiters, or join a list of strings into a larger string. translate(table[,deletestr]) Returns a string translated according to the translation string table. If you supply a string deletestr, translate removes all characters in that string before applying the translation table. The string table must have a length of 256; a character with ASCII value n is replaced with table[n]. The best way to create such a string is with a call to string.maketrans, as described below. For example, this line of code converts a string to “Hungarian style,” with words capitalized and concatenated. It also swaps exclamation points and question marks: >>>ProductName=”power smart report now?” >>>ProductName.title().translate(string.maketrans(“?!”,”!?”),string.whitespace) ‘PowerSmartReportNow!’ replace(oldstr,newstr[,maxreplacements]) Returns a string with all occurrences of oldstr replaced by newstr. If you provide maxreplacements, replace replaces only the first maxreplacements occurrences of oldstr. >>> “Siamese cat”.replace(“c”,”b”) ‘Siamese bat’ split([separators[,maxsplits]]) Breaks the string on any of the characters in the string separators, and returns a list of pieces. The default value of separators is string.whitespace. If you supply a value for maxsplits, then split performs up to maxsplits splits, and no more. This method is useful for dealing with delimited data: >>> StockQuoteLine = “24-Nov-00,45.9375,46.1875,44.6875,45.1875,3482500,45.1875” >>> ClosingPrice=float(StockQuoteLine.split(“,”)[4]) >>> ClosingPrice 45.1875 splitlines([keepends]) Splits a string on line breaks (carriage return and/or line feed). If you set keepends to true, splitlines retains the terminating character on each line. The string module has no corresponding function. For example: >>> “The\r\nEnd\n\n”.splitlines() [‘The’, ‘End’, ‘’] >>> “The\r\nEnd\n\n”.splitlines(1) [‘The\015\012’, ‘End\012’, ‘\012’] 137 4807-7 ch09.F 138 5/24/01 8:58 AM Page 138 Part II ✦ Files, Data Storage, and Operating System Services join(StringSequence) Returns a string consisting of all the strings in StringSequence concatenated together, using the string as a delimiter. This method in generally used in the corresponding function form: string.join(StringSequence[, Delimiter]). The default value of Delimiter is a single space. >>> Words=[“Ready”,”Set”,”Go”] >>> “...”.join(Words) # weird-looking ‘Ready...Set...Go’ >>> string.join(Words,”...”) # equivalent, and more intuitive ‘Ready...Set...Go’ encode([scheme[,errorhandling]]) Returns the same string, encoded in the encoding scheme scheme. The parameter scheme defaults to the current encoding scheme. The parameter errorhandling defaults to “strict,” indicating that encoding problems should raise a ValueError exception. Other values for errorhandling are “ignore” (do not raise any errors), and “replace” (replace un-encodable characters with a replacement marker). See the section “Encoding Text,” for more information. Using the String Module Because strings have so many useful methods, it is often not necessary to import the string module. But, the string module does provide many useful members. Character categories The string module includes several constant strings that categorize characters as letters, digits, punctuation, and so forth. Avoid editing these strings, as it may break standard routines. ✦ letters — All characters considered to be letters; consists of lowercase + uppercase. ✦ lowercase — All lowercase letters. ✦ uppercase — All uppercase letters. ✦ digits — The string ‘0123456789’. ✦ hexdigits — The string ‘0123456789abcdefABCDEF’. 4807-7 ch09.F 5/24/01 8:58 AM Page 139 Chapter 9 ✦ Processing Strings and Regular Expressions ✦ octdigits — The string ‘01234567’. ✦ punctuation — String of all the characters considered to be punctuation. ✦ printable — All the characters that are considered printable. Consists of digits, letters, punctuation, and whitespace. ✦ whitespace — All characters that are considered whitespace. On most systems this string includes the characters space, tab, linefeed, return, formfeed, and vertical tab. Miscellaneous functions Most of the functions in the string module correspond to methods of a string object, and are covered in the section on string methods. The other functions, which have no equivalent object methods, are covered here. atoi,atof,atol The function string.atoi(str) returns an integer value of str, and raises a ValueError if str does not represent an integer. It is equivalent to the built-in function int(str). The function atof(str) converts a string to a float; it is equivalent to the float function. The function atol(str) converts a string to a long integer; it is equivalent to the long function. >>> print string.atof(‘3.5’)+string.atol(‘2’) 5.5 capwords(str) Splits a string (on whitespace) into words, capitalizes each word, then joins the words together with one space between them: >>> string.capwords(“The end...or is it?”) ‘The End...or Is It?’ maketrans(fromstring,tostring) Creates a translation table suitable for passing to maketrans (or to regex.compile). The translation table instructs maketrans to translate the nth character in fromstring into the nth character in tostring. The strings fromstring and tostring must have the same length. The translation table is a string of length 256 representing all ASCII characters, but with fromstring[n] replaced by tostring[n]. 139 4807-7 ch09.F 140 5/24/01 8:58 AM Page 140 Part II ✦ Files, Data Storage, and Operating System Services splitfields,joinfields These functions have the same effect as split and join, respectively. (Before Version 2.0, splitfields and joinfields accepted a string of separators, and split and join did not.) zfill(str,width) Given a numeric string str and a desired width width, returns an equivalent numeric string padded on the left by zeroes. Similar to rjust. For example: >>> string.zfill(“-3”,5) ‘-0003’ Defining Regular Expressions A regular expression is an object that matches some collection of strings. You can use regular expressions to search and transform strings in sophisticated ways. Regular expressions use their own special syntax to describe strings to match. They can be very efficient, but also very cryptic if taken to extremes. Regular expressions are widely used in UNIX world. The module re provides full support for Perl-like regular expressions in Python. The re module raises the exception re.error if an error occurs while compiling or using a regular expression. Prior to Version 1.5, the modules regex and regsub provided support for regular expressions. These modules are now deprecated. Regular expression syntax The definition of a regular expression is a string. In general, a character in the regular expression’s definition matches a character in a target string. For example, the regular expression defined by fred matches the string “fred,” and no others. Some characters have special meanings that permit more sophisticated matching. . A period (dot) matches any character except a newline. For example, b.g matches “big,” “bag,” or “bqg,” but not “b\ng.” If the DOTALL flag is set, then dot matches any character, including a newline. Brackets specify a set of characters to match. For example, p[ie]n matches “pin” or “pen” and nothing else. A set can include ranges: the set [a-ex-z] is equivalent to [abcdexyz]. Starting a set with ^ means “match any character except these.” For example, b[^ae]d matches “bid” or “b%d,” but not “bad” or “bed.” * An asterisk indicates that the preceding regular expression is optional, and may occur any number of times. For example, ba*n* matches “banana” or “baaaa” or “bn” or simply “b.” 4807-7 ch09.F 5/24/01 8:58 AM Page 141 Chapter 9 ✦ Processing Strings and Regular Expressions + A plus sign indicates that the preceding regular expression must occur at least once, and may occur many times. For example, [sweatrd]+ matches various words, the longest of which is “stewardesses.” The regular expression [0-9]+/[0-9]+ matches fractions like “13/64” or “2/3.” ? A question mark indicates that the preceding regular expression is optional, and can occur, at most, once. For example, col?d matches either “cod” or “cold,” but not “colld.” The question mark has other uses, explained below in the sections on “Nongreedy matching” and “Extensions.” {m,n} The general notation for repetition is two numbers in curly-braces. This syntax indicates that the preceding regular expression must appear at least m times, but no more than n times. If m is omitted, it defaults to 0. If n is omitted, it defaults to infinity. For example, [^a-zA-Z]{3,} matches any sequence of at least three non-alphabetic characters. ^ A caret matches the beginning of the string. If the MULTILINE flag is set, it also matches the beginning of a new line. For example, ^bob matches “bobsled” but not “discombobulate.” Note that the caret has an unrelated meaning inside brackets .$ A dollar sign matches the end of the string. If the MULTILINE flag is set, it also matches the end of a line. For example, is$matches “this” but not “fish.” It matches “This\nyear” only if the MULTILINE flag is set. | A vertical slash splits a regular expression into two parts, and matches either the first half or the last half. For example, ab|cd matches the strings “ab” and “cd.” () Enclosing part of a regular expression in parentheses does not change matching behavior. However, Python flags the regular expression enclosed in parentheses as a group. After the first match, you can match the group again using backslash notation. For instance, the regular expression ^[\w]*(\w)\1[\w]*$ matches a single word with double letters, like “pepper” or “narrow” but not “salt” or “wide.” (The syntax \w, explained below, matches any letter.) A regular expression can have up to 99 groups, which are numbered starting from 1. Grouping is useful even if the group is only matched once. For example, Ste(ph|v)en matches “Stephen” or “Steven.” Without parens, Steph|ven matches only the strings “Steph” and “ven.” Python also uses parentheses in extensions (see “Extensions” later in this chapter). \ Escape special characters. You can use a backslash to escape any special characters. For example, ca\$h matches the string “ca$h.” Note that without the backslash, ca$h could never match anything (except in MULTILINE mode). The backslash also forms character groups, as described below. 141 4807-7 ch09.F 142 5/24/01 8:58 AM Page 142 Part II ✦ Files, Data Storage, and Operating System Services Backslashes and raw strings You should generally write the Python string defining a regular expression as a raw string. Otherwise, because you must escape backslashes in the regular expression’s definition, the excessive backslashes become confusing: >>> ThePath=”c:\\temp\\download\\” >>> print ThePath c:\temp\download\ >>> re.search(r”c:\\temp”,ThePath) # Raw. Reasonably clear. <SRE_Match object at 007CC7A8> >>> re.search(“c:\\temp”,ThePath) # no match! >>> re.search(“c:\\\\temp”,ThePath) # Less clear than raw <SRE_Match object at 007ACFD0> The second search fails to find a match, because the regular expression defined by c:\temp matches only the string consisting of “c:,” then a tab, then “emp”! Character groups and other backslash magic In addition to escaping special characters, you can also use the backslash in conjunction with a letter to match various things. A rule of thumb is that if backslash plus a lowercase letter matches something, backslash plus the uppercase letter matches the opposite. \1, \2, etc. Matches a numbered group. If part of a regular expression is enclosed in parentheses, Python flags it as a group. Python numbers groups, starting from 1 and proceeding to 99. You can match groups again by number. For example, (.+ )\1 matches the names of 80’s bands “The The,” “Mister Mister,” and “Duran Duran.” Python interprets escaped three-digit numbers, or numbers starting with 0, as the octal value of a character. For example, \012 matches a newline. Inside set brackets , Python treats all escaped numbers as characters. \A Matches the start of the string: equivalent to ^. \b Matches a word boundary. Here “word” means “sequence of alphanumeric characters.” For example, snow\b matches “snow angel” but not “snowball.” Note that \b in the middle of a word indicates backspace, just as it would in an ordinary string. For instance, “bozo\b\b\b\bgentleman” matches the string consisting of “bozo,” four backspace characters, then “gentleman.” \B Matches a non-word-boundary. For example, \Bne\B matches part of “planet,” but not “nest” or “lane.” \d Matches a digit: equivalent to [0–9]. 4807-7 ch09.F 5/24/01 8:58 AM Page 143 Chapter 9 ✦ Processing Strings and Regular Expressions \D Matches a non-digit: equivalent to [^0–9]. \s Matches a whitespace character: equivalent to [ \t\n\r\f\v]. \S Matches a non-whitespace character: equivalent to [^ \t\n\r\f\v]. \w Matches an alphanumeric character: equivalent to [a–zA–Z0–9_]. If the LOCALE flag is set, \w matches [0–9_] or any character defined as alphabetic in the current locale. If the UNICODE flag is set, matches [0–9_] or any character marked as alphanumeric in the full Unicode character set. \W Matches a non-alphanumeric character. \Z Matches the end of the string: equivalent to$. \\ Matches a backslash. (Similarly, \. matches a period, \? matches a question mark, and so forth.) Nongreedy matching The repetition operators ?,+,* and {m,n} normally match as much as the target string as possible. You can modify the operators with a question mark to be “nongreedy,” and match as little of the target string as possible. For example, when matched against the string “over the top,” \b.*\b would normally match the entire string. The corresponding non-greedy version, \b.*?\b, matches only the first word, “over.” Extensions Syntax n of the form (?...) marks a regular expression extension. The meaning of the extension depends on the character after the question mark. (?#...) Is a comment. Python ignores this portion of the regular expression. (?P<name>...) Creates a named group. Named groups work like numbered groups. You can match them again using (?P=name). For example, this regular expression matches a single word that begins and ends with the same letter: ^(?P<letter>\w)\w*(?P=letter)$. A named group receives a number, and can be referred to by number or by name. (?:...) Are non-grouping parentheses. You can use these to enhance readability; they don’t change the regular expression’s behavior. For example, (?:\w+)(\d)\1 matches one or more letters followed by a repeated digit, such as “bob99” or “x22.” The string (?:\w+) does not create a group, so \1 matches the first group, (\d). (?i), (?L), (?m),(?s), (?u),(?x) Are REs that set the flags re.I, re.L, re.M, re.S, re.U, and re.X respectively. Note that (?L) uses an uppercase letter; the others are lowercase. 143 4807-7 ch09.F 144 5/24/01 8:58 AM Page 144 Part II ✦ Files, Data Storage, and Operating System Services (?=...) Is a lookahead assertion. Python matches the enclosed regular expression, but does not “consume” any of the target string. For example, blue(?=berry) matches the string “blue,” but only if it is followed by “berry.” (?!...) Is a negative lookahead assertion. The enclosed regular expression must not match the target string. For example, electron(?!ic\b) matches the string “electron” only when it is not part of the word “electronic.” Creating and Using Regular Expression Objects The function re.compile(pattern[, flags]) compiles the specified pattern string and returns a new regular expression object. The optional parameter flags tweak the behavior of the expression. Each flag value has a long name and an equivalent short name. You can combine flags using bitwise or. For example, this line returns a regular expression that searches for two occurrences of the word “the,” ignoring case, with any character (including newline) in between. re.compile(“the.the”,re.IGNORECASE | re.DOTALL) re.IGNORECASE, re.I Performs case-insensitive matching. re.LOCALE, re.L Interprets words according to the current locale. This interpretation affects the alphabetic group (\w and \W), as well as word boundary behavior (\b and \B). re.MULTILINE, re.M Makes$ match the end of a line (not just the end of the string) and makes ^ match the start of any line (not just the start of the string). re.DOTALL, re.S Makes a period (dot) match any character, including a newline. re.UNICODE, re.U Interprets letters according to the Unicode character set. This flag affects the behavior of \w, \W, \b, \B. re.VERBOSE, re.X Permits “cuter” regular expression syntax. It ignores whitespace (except inside a set or when escaped by a backslash), and treats unescaped # as a comment marker. For example, the following two lines of code are equivalent. They match a single word containing three consecutive pairs of doubled letters, such as “zrqqxxyy.” (Finding an 4807-7 ch09.F 5/24/01 8:58 AM Page 145 Chapter 9 ✦ Processing Strings and Regular Expressions English word matching this description is left as an exercise for the reader.) Note that the second VERBOSE form of the regular expression is a bit more readable. NewRE = re.compile(r”^\w*(\w)\1(\w)\2(\w)\3\w*$”) NewRE = re.compile(r”^\w* (\w)\1 (\w)\2 (\w)\3 \w*$#three doubled letters”, re.VERBOSE) Using regular expression objects You can use regular expressions to search, replace, split strings, and more. search(targetstring[,startindex[,endindex]]) The core use of a regular expression! The method search(targetstring) scans through targetstring looking for a match. If it finds one, it returns a MatchObject instance. If it finds no match, it returns None. (See below for MatchObject methods.) The search method searches the slice targetstring[startindex: endindex] — by default, the whole string. The characters $and ^ match the beginning and ending of the entire string, not necessarily the start or end of the substring. For example, ^friends$ does not match the string “are friends electric?” even if one takes the slice “friends” from index 4 to index 11. match(targetstring[,startindex[,endindex]]) Attempts to match the regular expression against the first part of targetstring. The match method is more restrictive than search, as it must match the first zero or more characters of targetstring. It returns a MatchObject instance if it finds a match, None otherwise. The parameters startindex and endindex function here as they do in search. findall(targetstring) Matches against targetstring and returns a list of nonoverlapping matches. For example: >>> re.compile(r”\w+”).findall(“the larch”) # Greedy matching [‘the’, ‘larch’] >>> re.compile(r”\w+?”).findall(“the larch”) # Nongreedy [‘t’, ‘h’, ‘e’, ‘l’, ‘a’, ‘r’, ‘c’, ‘h’] If the regular expression contains a group, the list returned is a list of group values (in tuple form, if it contains multiple groups). For example: >>> re.compile(r”(\w+)(\w+)”).findall(“the larch”) [(‘th’, ‘e’), (‘larc’, ‘h’)] 145 4807-7 ch09.F 146 5/24/01 8:58 AM Page 146 Part II ✦ Files, Data Storage, and Operating System Services split(targetstring[,maxsplit]) Breaks targetstring on each match of the regular expression, and returns a list of pieces. If the regular expression consists of a single large group, then the list of pieces includes the delimiting strings; otherwise, the list of pieces does not include the delimiters. If you specify a nonzero value for maxsplit, then split makes, at most, maxsplit cuts, and the remainder of the string remains intact. For example, this regular expression removes all ifs, ands, and buts from a string: >>> MyRE=re.compile(r”\bif\b|\band\b|\bbut\b”,re.I) >>> LongString=”I would if I could, and I wish I could, but I can’t.””” >>> MyRE.split(LongString) [‘I would ‘, ‘ I could, ‘, ‘ I wish I could, ‘, “ I can’t.”] >>> MyRE=re.compile(r”(\bif\b|\band\b|\bbut\b)”,re.I) >>> MyRE.split(LongString) # Keep the matches in the list. [‘I would ‘, ‘if’, ‘ I could, ‘, ‘and’, ‘ I wish I could, ‘, ‘but’, “ I can’t.”] sub(replacement, targetstring[, count]) Search for the regular expression in targetstring, and perform a substitution at each match. The parameter replacement can be a string. It can also be a function that takes a MatchObject as an argument, and returns a string. If you specify a nonzero value for count, then sub makes, at most, count substitutions. This example translates a string to “Pig Latin.” (It moves any leading consonant cluster to the end of the word, then adds “ay” so that “chair” becomes “airchay.”) >>> def PigLatinify(thematch): >>> ... return thematch.group(2)+thematch.group(1)+”ay” >>> ... >>> WordRE=re.compile(r”\b([b-df-hj-np-tv-z]*)(\w+)\b”,re.I) >>> WordRE.sub(PigLatinify, “fetch a comfy chair”) ‘etchfay aay omfycay airchay’ If replacement is a string, it can contain references to groups from the regular expression. For example, sub replaces a \1 or \g<1> in replacement with the first group from the regular expression. You can insert named groups with the syntax \g<name>. The sub method replaces empty (length-0) matches only if they are not adjacent to another substitution. subn(replacement, targetstring[, count]) Same as sub, but returns a two-tuple whose first element is the new string, and whose second element is the number of substitutions made. 4807-7 ch09.F 5/24/01 8:58 AM Page 147 Chapter 9 ✦ Processing Strings and Regular Expressions Applying regular expressions without compiling The methods of a regular expression object correspond to functions in the re module. If you call these functions directly, you don’t need to call re.compile in your code. However, if you plan to use a regular expression several times, it is more efficient to compile and reuse it. The following module functions are available: escape(str) Returns a copy of str with all special characters escaped. This feature is useful for making a regular expression for an arbitrary string. For example, this function searches for a substring in a larger string, just like string.find, but case-insensitively: def InsensitiveFind(BigString,SubString): TheMatch = re.search(re.escape(SubString),BigString,re.I) if (TheMatch): return TheMatch.start() else: return -1 search(pattern,targetstring[,flags]) Compiles pattern into a regular expression object with flags set, then uses it to perform a search against targetstring. match(pattern,targetstring[,flags]) Compiles pattern into a regular expression object with flags set, then uses it to perform a match against targetstring. split(pattern,targetstring[,maxsplit]) Compiles pattern into a regular expression object, then uses it to split targetstring. findall(pattern,targetstring) Compiles pattern into a regular expression object, then uses it to find all matches in targetstring. sub(pattern,replacement,targetstring[,count]) Compiles pattern into a regular expression object, then calls its sub method with parameters replacement, targetstring, and count. The function subn is similar, but calls the subn method instead. Using Match Objects Searching with a regular expression object returns a MatchObject, or None if the search finds no matches. The match object has several methods, mostly to provide details on groups used in the match. 147 4807-7 ch09.F 148 5/24/01 8:58 AM Page 148 Part II ✦ Files, Data Storage, and Operating System Services group([groupid,...]) Returns the substring matched by the specified group. For index 0, it returns the substring matched by the entire regular expression. If you specify several group identifiers, group returns a tuple of substrings for the corresponding groups. If the regular expression includes named groups, groupid can be a string. groups([nomatch]) Returns a tuple of substrings matched by each group. If a group was not part of the match, its corresponding substring is nomatch. The parameter nomatch defaults to None. groupdict([nomatch]) Returns a dictionary. Each entry’s key is a group name, and the value is the substring matched by that named group. If a group was not part of the match, its corresponding value is nomatch, which defaults to None. This example creates a regular expression with four named groups. The expression parses fractions of the form “1 1/3,” splitting them into integer part, numerator, and denominator. Non-fractions are matched by the “plain” group. >>> FractionRE=re.compile( ... r”(?P<plain>^\d+$)?(?P<int>\d+(?= ))? ?(?P<num>\d+(?=/))?/?(?P<den>\d+$)?”) >>> FractionRE.match(“1 1/3”).groupdict() {‘den’: ‘3’, ‘num’: ‘1’, ‘plain’: None, ‘int’: ‘1’} >>> FractionRE.match(“42”).groupdict(“x”) {‘den’: ‘x’, ‘num’: ‘x’, ‘plain’: ‘42’, ‘int’: ‘x’} start([groupid]), end([groupid]), span([groupid]) The methods start and end return the indices of the substring matched by the group identified by groupid. If the specified group didn’t contribute to the match, they return -1. The method span(groupid) returns both indices in tuple form: (start(groupid),end(groupid)). By default, groupid is 0, indicating the entire regular expression. 4807-7 ch09.F 5/24/01 8:58 AM Page 149 Chapter 9 ✦ Processing Strings and Regular Expressions re,string,pos,endpos, These members hold the parameters passed to search or match: ✦ re — The regular expression object used in the match ✦ string — The string used in the match ✦ pos — First index of the substring searched against ✦ endpos — Last index of the substring searched against Treating Strings as Files The module StringIO defines a class named StringIO. This class wraps an in-memory string buffer, and supports standard file operations. Since a StringIO instance does not correspond to an actual file, calling its close method simply frees the buffer. The StringIO constructor takes, as a single optional parameter, an initial string for the buffer. The method getvalue returns the contents of the buffer. It is equivalent to calling seek(0) and then read(). CrossReference See Chapter 8 for a description of the standard file operations. The module cStringIO defines a similar class, also named StringIO. Because cStringIO.StringIO is implemented in C, it is faster than StringIO.StringIO; the one drawback is that you cannot subclass it. The module cStringIO defines two additional types: InputType is the type for StringIO objects constructed with a string parameter, and OutputType is the type for StringIO objects constructed without a string parameter. The StringIO class is useful for building up long strings without having to do many small concatenations. For instance, the function demonstrated in Listing 9-1 builds up an HTTP request string, suitable for transmission to a Web server: Listing 9-1: httpreq.py import import import import import re urlparse cStringIO string socket Continued 149 4807-7 ch09.F 150 5/24/01 8:58 AM Page 150 Part II ✦ Files, Data Storage, and Operating System Services Listing 9-1 (continued) STANDARD_HEADERS = “””HTTP/1.1 Accept: image/gif, image/x-xbitmap, image/jpeg, */* Accept-Language: en-us Accept-Encoding: gzip, deflate User-Agent: Mozilla/4.0 (compatible)””” def CreateHTTPRequest(URL, CookieDict): “”” Create an HTTP request for a given URL (as returned by urlparse.urlparse) and a dictionary of cookies (where key is the host string, and the value is the cookie in the form “param=value”. “”” Buffer = cStringIO.StringIO() Buffer.write(“GET “) FileString = URL[2] # File name if URL[3]!=””: # Posted values FileString = FileString + “;” + URL[3] if URL[4]!=””: # Query parameters FileString = FileString + “?” + URL[4] FileString = string.replace(FileString,” “,”%20”) Buffer.write(FileString+”\r\n”) Buffer.write(STANDARD_HEADERS) # Add cookies to the request. GotCookies=0 for HostString in CookieDict.keys(): # Perform a case-insensitive search. (Call re.escape so # special characters like . are searched for normally.) if (re.search(re.escape(HostString),URL[1],re.I)): if (GotCookies==0): Buffer.write(“\r\nCookie: “) GotCookies=1 else: Buffer.write(“; “) Buffer.write(CookieDict[HostString]) if (GotCookies): Buffer.write(“\r\n”) Buffer.write(“Host: “+URL[1]) Buffer.write(“\r\n\r\n”) RequestString=Buffer.getvalue() Buffer.close() return RequestString if (__name__==”__main__”): CookieDict={} CookieDict[“python”]=”cookie1=value1” CookieDict[“python.ORG”]=”cookie2=value2” CookieDict[“amazon.com”]=”cookie3=value3” URL = urlparse.urlparse(“http://www.python.org/2.0/”) print CreateHTTPRequest(URL,CookieDict) 4807-7 ch09.F 5/24/01 8:58 AM Page 151 Chapter 9 ✦ Processing Strings and Regular Expressions Encoding Text All digital data, including text, is ultimately represented as ones and zeroes. A character set is a way of encoding text as binary numbers. For example, the ASCII character set represents letters using a number from 0 to 255. The built-in function ord returns the number corresponding to an ASCII character; the function chr returns the ASCII character corresponding to a number: >>> ord(‘a’) 97 >>> chr(97) ‘a’ The ASCII character set has limitations — it does not contain Cyrillic letters, Chinese ideograms, et cetera. And so, various character sets have been created to handle various collections of characters. The Unicode character set is the mother of all character sets. Unicode subsumes ASCII and Latin-1. It also includes all widely used alphabets, symbols of some ancient languages, and everything but the kitchen sink. Using Unicode strings A Unicode string behaves just like an ordinary string — it has the same methods. You can denote a string literal as Unicode by prefixing it with a u. You can denote Unicode characters with \u followed by four hexadecimal digits. For example: >>> >>> >>> 1 >>> >>> 2 >>> >>> 12 MyUnicodeString=u”Hello” MyString=”Hello” MyUnicodeString==MyString # Legal comparison MyUnicodeString=u”\ucafe\ubabe” len(MyUnicodeString) MyString=”\ucafe\ubabe” # No special processing! len(MyString) For a reference on the Unicode character set, and its character categories, see http://www.unicode.org/Public/UNIDATA/UnicodeData.html. Reading and writing non-ASCII strings You cannot use Unicode characters with an ordinary file object created by the open function: 151 4807-7 ch09.F 152 5/24/01 8:58 AM Page 152 Part II ✦ Files, Data Storage, and Operating System Services >>> MyUnicodeString=u”\ucafe\ubabe” >>> ASCIIFile=open(“test.txt”,”w”) # This file can’t handle unicode! >>> ASCIIFile.write(MyUnicodeString) Traceback (innermost last): File “<pyshell#39>”, line 1, in ? ASCIIFile.write(MyUnicodeString) UnicodeError: ASCII encoding error: ordinal not in range(128) The codecs module provides file objects to help read and write Unicode text. open(filename,mode[,encoding[,errorhandler[,buffering]]]) The function codecs.open returns a file object that can handle the character set specified by encoding. The encoding parameter is a string specifying the desired encoding. The errorhandler parameter, which defaults to “strict,” specifies what to do with errors. The “ignore” handler skips characters not in the character set; the “strict” handler raises a ValueError for unacceptable characters. The mode and buffering parameters have the same effect as for the built-in function open. >>> >>> >>> >>> >>> >>> Bob=codecs.open(“test-uni.txt”,”w”,”unicode-escape”) Bob.write(MyUnicodeString) Bob.close() Bob=codecs.open(“test-utf16.txt”,”w”,”utf16”) Bob.write(MyUnicodeString) Bob.close() You should generally read and write files using the same character set, or extreme garbling can result. The function sys.getdefaultencoding returns the name of the current default encoding. EncodedFile(fileobject,sourceencoding[,fileencoding[,errorhandler]]) The function codecs.EncodedFile returns a wrapper object for the file fileobject to handle character set translation. This function translates data written to the file from the sourceencoding character set to the fileencoding character set; data read from the file does the reverse. For example, this code writes a file using UTF-8 encoding, then translates from UTF-8 to escaped Unicode: >>> UTFFile=codecs.open(“utf8.txt”,”w”,”utf8”) >>> UTFFile.write(MyUnicodeString) >>> UTFFile.close() >>> MyFile=open(“utf8.txt”,”r”) >>> Wrapper=codecs.EncodedFile(MyFile,”unicode-escape”,”utf8”) >>> Wrapper.read() ‘\\uCAFE\\uBABE’ 4807-7 ch09.F 5/24/01 8:58 AM Page 153 Chapter 9 ✦ Processing Strings and Regular Expressions Using the Unicode database The module unicodedata provides functions to check a character’s meaning in the Unicode 3.0 character set. Categorization These functions give information about a character’s general category: category(unichr) Returns a string denoting the category of unichr. For example, underscore has category “PC” for connector punctuation. bidirectional(unichr) Returns a string denoting the bidirectional category of unichr. For example, unicode. bidirectional(u”e”) is “L,” indicating that “e” is normally written left-to-right. combining(unichr) Returns an integer indicating the combining class of unichr. Returns 0 for non-combining characters. mirrored(unichr) Returns 1 if unichr is a mirrored character, 0 otherwise. decomposition(unichr) Returns the character-decomposition string corresponding to unichr, or a blank string if no decomposition exists. Numeric characters These functions give details about numeric characters: decimal(unichr[,default]) Returns unichr’s decimal value as an integer. If unichr has no decimal value, returns default or (if default is unspecified) raises a ValueError. numeric(unichr[,default]) Returns unichr’s numeric value as a float. If unichr has no decimal value, returns default or (if default is unspecified) raises a ValueError. digit(unichr[,default]) Returns unichr’s digit value as an integer. If unichr has no digit value, returns default or (if default is unspecified) raises a ValueError. 153 4807-7 ch09.F 154 5/24/01 8:58 AM Page 154 Part II ✦ Files, Data Storage, and Operating System Services Formatting Floating Point Numbers The fpformat module provides convenience functions for displaying floating point numbers. fix(number,precision) Formats floating point value number with at least one digit before the decimal point, and at most precision digits after. The number is rounded to the specified precision as needed. If precision is zero, this function returns a string with the number rounded to the nearest integer. The parameter number can be either a float, or a string that can be passed to the function float. sci(number,precision) Formats floating point value number in scientific notation — one digit before the decimal point, and the exponent indicated afterwards. The parameters number and precision behave as they do for the function fix. Here are some examples of formatting with fpformat: >>> fpformat.fix(3.5,0) ‘4’ >>> fpformat.fix(3.555,2) ‘3.56’ >>> fpformat.sci(3.555,2) ‘3.56e+000’ >>> fpformat.sci(“0.03555”,2) ‘3.56e-002’ These functions raise the exception fpformat.NotANumber (a subclass of ValueError) if the parameter number is not a valid value. The exception argument is the value of number. Summary Python offers a full suite of string-manipulation functions. It also provides regular expressions, which enable even more powerful searching and replacing. In this chapter you: ✦ Searched, formatted, and modified string objects. ✦ Searched and parsed strings using regular expressions. ✦ Formatted floating point numbers cleanly and easily. In the next chapter you’ll learn how Python can handle files and directories. ✦ ✦ ✦ 4807-7 ch10.F 5/24/01 8:58 AM Page 155 10 CHAPTER Working with Files and Directories C hapter 8 discussed the basics of file input and output in Python, but the routines covered there assume you know what file you want to read and write and where it’s located. This chapter explains operating system features that Python supports such as finding a list of files that match a given search pattern, navigating directories, and renaming and copying files. This chapter and the next cover many modules, primarily os, os.path, and sys. Instead of organizing the chapters around the functions provided in each module, we’ve tried to group them by feature so that you can find what you need quickly. For example, you can find a file’s size with os.stat(filename) [stat.ST_SIZE] or with os.path.getsize(filename) (something you wouldn’t know unless you read through both the os and os.path modules), so I cover them in the same section. Where this is not possible, I’ve added cross-references to help guide you. Retrieving File and Directory Information With the exception of a few oddballs, modern operating systems let you store files in directories (locations in a named hierarchy or tree) for better organization. (Just imagine the mess if everything was in one chaotic lump.) This and the following sections consider a path to be a directory or file name. You can refer to a path relative to another one (..\temp\bob.txt means go up the tree a step, down into the temp directory to the file called bob.txt) while others are absolute (/usr/local/bin/destroystuff tells how to go from the top of the tree all the way down to destroystuff). ✦ ✦ ✦ ✦ In This Chapter Retrieving file and directory information Building and dissecting paths Listing directories and matching file names Obtaining environment and argument information Example: Recursive Grep Utility Copying, renaming, and removing paths Creating directories and temporary files Comparing files and directories Working with file descriptors Other file processing techniques ✦ ✦ ✦ ✦ 4807-7 ch10.F 156 5/24/01 8:58 AM Page 156 Part II ✦ Files, Data Storage, and Operating System Services The Secret Identities of os and os.path The os module contains plenty of functions for performing operating system-ish stuff like changing directories and removing files, while os.path helps extract directory names, file names, and extensions from a given path. The great thing is that these modules work on any Python-supported platform, making your programs much more portable. For example, to join a directory name with a file name, using os.path.join makes sure the result is correct for the current operating system: >>> print os.path.join(‘maps’,’dungeon12.map’) maps\dungeon12.map # Result when run on Windows >>> print os.path.join(‘maps’,’dungeon12.map’) maps/dungeon12.map # Result when run on UNIX To make this happen, each platform defines two modules to do the platform-specific work. (On Macintosh systems they are mac and macpath; on Windows they’re nt and ntpath, and so on.) When the os module is imported, it looks inside sys.builtin_module_names for the name of a platform-specific module (such as nt), loads its contents into the os namespace, and then loads the platform-specific path module and renames it to os.path. You can check the os.name variable to see which operating system-specific module os loaded, but you should rarely need to use it. The whole point of os and os.path is to make your programs blissfully ignorant of the underlying operating system. You can choose how you want to access path information: Python provides several functions to retrieve a single bit of information (does this path exist?) or all of it in one big glob (give me creation time, last access time, file size, and so forth). Note Please note that many of the examples in this chapter use file and directory names that may not exist in your system. Accept the examples on faith or substitute valid file names of your own (just don’t go and erase something important, though). The piecemeal approach The access(path, mode) function tests to see that the current process has permission to read, write, or execute a given path. The mode parameter can be any combination of os.R_OK (read permission), os.W_OK (write permission), or os.X_OK (execute permission): >>> os.access(‘/usr/local’,os.R_OK | os.X_OK) 1 # I have read AND execute permissions... >>> os.access(‘/usr/local’,os.W_OK) 0 # ...but not write permissions. 4807-7 ch10.F 5/24/01 8:58 AM Page 157 Chapter 10 ✦ Working with Files and Directories You can also use a mode of os.F_OK to test if the given path exists. Or you can use the os.path.exists(path) function: >>> os.path.exists(‘c:\\winnt’) # ‘\\’ to “escape” the slash 1 The inverse of access is os.chmod(path, mode) which lets you set the mode for the given path. The mode parameter is a number created by adding different octal values listed in Table 10-1. For example, to give the owner read/write permissions, group members read permissions, and others no access to a file: os.chmod(‘secretPlans.txt’,0640) Tip The first few times you use this function you may forget that the values in Table 10-1 are octal numbers. This is a convention held over from the underlying C chmod function; as octals, the different mode values combine in that cute way while making the implementation easier. Remember to stick in the leading zero on the mode so that Python sees it as an octal, and not a decimal, number. Table 10-1 Values for os.chmod Value 0400 Owner can read the path. 0200 Owner can write the path. 0100 Owner can execute the file or search the directory. 0040 Group members can read the path. 0020 Group members can write the path. 0010 Group members can execute the file or search the directory. 0004 Others can read the path. 0002 Others can write the path. 0001 Note Description Others can execute the file or search the directory. Different operating systems handle permissions differently (Windows, for example, doesn’t really manage file permissions with owners and groups). You should try a few tests out before relying on a particular behavior. Also, consult the UNIX chmod man page for additional mode values that vary by platform. The os.path.isabs(path) function returns 1 if the given path is an absolute path. On UNIX systems, a path is absolute if it starts with ‘/’; on Windows, paths are absolute if they either start with a backlash or if they start with a drive letter followed by a colon and a backslash: 157 4807-7 ch10.F 158 5/24/01 8:58 AM Page 158 Part II ✦ Files, Data Storage, and Operating System Services >>> os.path.isabs(‘c:\\temp’) 1 >>> os.path.isabs(‘temp\\foo’) 0 The following four functions in the os.path module, isdir(path), isfile(path), islink(path), and ismount(path), test what kind of file system entry the given path refers to: >>> 1 >>> 0 >>> 1 >>> 1 os.path.isdir(‘c:\\winnt’) # Is it a directory? os.path.isfile(‘c:\\winnt’) # Is it a normal file? os.path.islink(‘/usr/X11R6/bin/X’) # Is it a symbolic link? os.path.ismount(‘c:\\’) # It is a mount point? On platforms that support symbolic links, isdir and isfile return true if the path is a link to a directory or file, and the os.readlink(path) function returns the actual path to which a symbolic link points. A mounting point is essentially where two file systems connect. On UNIX, ismount returns true if path and path/.. have a different device or inode. On Windows, ismount returns true for paths like c:\ and \\endor\. Note An inode is a UNIX file system data structure that holds information about a directory entry. Each directory entry is uniquely identified by a device number and an inode number. Some of the following routines may return inode numbers; for UNIX machines these are valid, but for other platforms they are just dummy values. You can retrieve a file’s size in bytes using os.path.getsize(path): >>> os.path.getsize(‘c:\\winnt\\uninst.exe’) 299520 # About 290K The os.path.getatime(path) and os.path.getmtime(path) functions return the path’s last access and modified times, respectively, in seconds since the epoch (you know, New Year’s Eve 1969): >>> os.path.getmtime(‘c:\\winnt\\readme.exe’) 786178800 >>> os.path.getatime(‘c:\\winnt\\readme.exe’) 956901600 >>> import time >>> time.ctime(os.path.getatime(‘c:\\winnt\\readme.exe’)) ‘Fri Apr 28 00:00:00 2000’ 4807-7 ch10.F 5/24/01 8:58 AM Page 159 Chapter 10 ✦ Working with Files and Directories Going the other direction, the os.utime(path, (atime, mtime)) function sets the time values for the given path. The following example sets the last access and modification times of a file to noon on March 1, 1977: >>> sec = time.mktime((1977,3,1,12,0,0,-1,-1,-1)) >>> os.utime(‘c:\\temp\\foo.txt’,(sec,sec)) You can also “touch” a file’s times so that they are set to the current time: >>> os.utime(‘c:\\temp\\foo.txt’,None) # Set to current time. CrossReference See the time module in Chapter 13 for a discussion of its features and a better definition of the epoch. UNIX-compatible systems have the os.chown(path, userID, groupID) that changes the ownership of a path to that of a different user and group: os.chown(‘grumpy.png’,os.getuid(),os.getgid()) CrossReference Chapter 11 covers functions to get and set group and user IDs. Non-Windows systems include the os.path.samefile(path1,path2) and os.path. sameopenfile(f1,f2) functions that return true if the given paths or file objects refer to the same item on disk (they reside on the same device and have the same inode). The I-want-it-all approach If you want to know several pieces of information about a path (for example, you need to know a file’s size as well as the time it was last modified), the previous functions are inefficient because each one results in a call to the operating system. The os.stat(path) function solves this problem by returning a tuple with ten pieces of information all at once (many of the previous section’s functions quietly call os.stat behind the scenes and throw away the information you didn’t request): >>> os.stat(‘c:\\winnt\\uninst.exe’) (33279, 0, 2, 1, 0, 0, 299520, 974876400, 860551690, 955920365) Don’t worry too much if the numbers returned look useless! The stat module provides names (listed in Table 10-2) for indexes into the tuple: >>> import stat >>> os.stat(‘c:\\winnt\\uninst.exe’)[stat.ST_SIZE] # File size 299520 # Hmm... still about 290K 159 4807-7 ch10.F 160 5/24/01 8:58 AM Page 160 Part II ✦ Files, Data Storage, and Operating System Services Table 10-2 Index Names for os.stat Tuple Name Description ST_SIZE File size (in bytes) ST_ATIME Time of last access (in seconds since the epoch) ST_MTIME Time of last modification (in seconds since the epoch) ST_MODE Mode (see below for possible values) ST_CTIME Time of last status change (access, modify, chmod, chown, and so on) ST_UID Owner’s user ID ST_GID Owner’s group ID ST_NLINK Number of links to the inode ST_INO inode’s number ST_DEV inode’s device Once you have a path’s mode value (stat.ST_MODE), you can use other statprovided functions to test for certain types of path entries (see Table 10-3 for the complete list): >>> mode = os.stat(‘c:\\winnt’)[stat.ST_MODE] >>> stat.S_ISDIR(mode) # Is it a directory? 1 # Yes! Table 10-3 Path Type Test Functions Function Returns true for S_ISREG(mode) Regular file S_ISDIR(mode) Directory S_ISLNK(mode) Symbolic link S_ISFIFO(mode) FIFO (named pipe) S_ISSOCK(mode) Socket S_ISBLK(mode) Special block device S_ISCHR(mode) Special character device 4807-7 ch10.F 5/24/01 8:58 AM Page 161 Chapter 10 ✦ Working with Files and Directories When you call os.stat with a path to a symbolic link, it returns information about the path that the link references. The os.lstat(path) function behaves just like os.stat except that on symbolic links it returns information about the link itself (although the OS still borrows much of the information from the file it references). CrossReference See “Working with File Descriptors” later in this chapter for coverage of the os.fstat function that returns stats for open file descriptors. On UNIX-compatible systems you can call os.samestat(stat1,stat2) to see if two sets of stats refer to the same file (it compares the device and inode number). The Python standard library also comes with the statcache module, which behaves just like os.stat but caches the results for later use: >>> import statcache >>> statcache.stat(‘c:\\temp’) (16895, 0, 2, 1, 0, 0, 0, 975999600, 969904112, 969904110) You can call forget(path) to remove a particular cached entry, or reset() to remove them all. The forget_prefix(prefix) function removes all entries that start with a given prefix, and forget_except_prefix(prefix) removes all that do not start with the prefix (removing a cache entry means a call to stat will have to check with the operating system again). The forget_dir(prefix) function removes all entries in a directory, but not in its subdirectories. Building and Dissecting Paths The different path conventions that operating systems follow can make path manipulation a nuisance. Fortunately Python has plenty of routines to help. Joining path parts The os.path.join(part[, part...]) joins any number of path components into a path valid for the current operating system: >>> print os.path.join(‘c:’,’r2d2’,’c3po’,’r5d4’) c:\r2d2\c3po\r5d4 >>> print os.path.join(os.pardir,os.pardir,’tmp’) ..\..\tmp The separator character used is defined in os.sep. You can use os.curdir and os.pardir with join when you want to refer to the current and parent directories, respectively. 161 4807-7 ch10.F 162 5/24/01 8:58 AM Page 162 Part II ✦ Files, Data Storage, and Operating System Services Breaking paths into pieces Given a path, it’s not too hard to separate it into its pieces (file name, extension, directory name, and so on) using one of the os.path.split functions: >>> os.path.split(r’c:\temp\foo.txt’) # Yay, raw strings! (‘c:\\temp’, ‘foo.txt’) # Split into path and filename. >>> os.path.splitdrive(r’c:\temp\foo.txt’) (‘c:’, ‘\\temp\\foo.txt’) # Split off the drive. >>> os.path.splitext(r’c:\temp\foo.txt’) (‘c:\\temp\\foo’, ‘.txt’) # Split off the extension. >>> os.path.splitunc(r’\\endor\temp\foo.txt’) (‘\\\\endor\\temp’, ‘\\foo.txt’) # Split off machine and mount. The splitdrive function is present on UNIX systems, but for any path just returns the tuple (‘’,path); the splitunc function is available only on Windows. The os.path.dirname(path) and os.path.basename(path) functions are shorthand functions that together return the same information as split: >>> os.path.dirname(r’c:\temp\foo.txt’) ‘c:\\temp’ >>> os.path.basename(r’c:\temp\foo.txt’) ‘foo.txt’ Other path modifiers The os.path.normcase(path) function normalizes the case of a path (makes it all lowercase on case-insensitive platforms, leaves it unchanged on others) and replaces forward slashes with backwards slashes on Windows platforms: >>> print os.path.normcase(‘kEwL/lAmeR/hAckUr/d00d’) kewl\lamer\hackur\d00d The os.path.normpath(path) function normalizes a given path by removing redundant separator characters and collapsing references to the parent directory (it also fixes forward slashes for Windows systems): >>> print os.path.normpath(r’c:\work\\\temp\..\..\games’) c:\games The os.path.abspath(path) function normalizes the path and then converts it to an absolute path: >>> os.getcwd() ‘/export/home’ >>> os.path.abspath(‘fred/backup/../temp/cool.py’) ‘/export/home/fred/temp/cool.py’ 4807-7 ch10.F 5/24/01 8:58 AM Page 163 Chapter 10 ✦ Working with Files and Directories The os.path.expandvars(path) function searches the given path for variable names of the form $varname and${varname}. If the variables are defined in the environment, expandvars substitutes in their values, leaving undefined variable references in place (you can use  to print $): >>> os.environ.update({‘WORK’:’work’,’BAKFILE’:’kill.bak’}) >>> p = os.path.join(‘$WORK’,’${BAKFILE}’) >>> print os.path.expandvars(p) work\kill.bak The os.path.expanduser(path) function replaces “~” or “~username” at the beginning of a path with the path to the user’s home directory. For “~” (meaning the current user), expanduser uses the value of the HOME environment variable if present. On Windows, if HOME is not defined, then it also tries to find and join HOMEDRIVE and HOMEPATH, returning the original path unchanged if it fails. For users other than the current user (“~username”), Windows always returns the original path and UNIX uses the pwd module to locate that user’s home directory. CrossReference See Chapter 38 to learn more about the pwd module. Listing Directories and Matching File Names This section lists several ways to retrieve a list of file names, whether they are all the files in a particular directory or all the files that match a particular search pattern. The os.listdir(dir) function returns a list containing all the files in the given directory: >>> os.listdir(‘c:\\sierra’) [‘LAND’, ‘Half-Life’, ‘SETUP.EXE’] The dircache module provides its own listdir function that maintains a cache to increase the performance of repeated calls (and uses the modified time on the directory to detect when a cache entry needs to be tossed out): >>> import dircache >>> dircache.listdir(‘c:\\sierra’) [‘Half-Life’, ‘LAND’, ‘SETUP.EXE’] The list returned is a reference, not a copy, so modifying it means your modifications are returned to future callers too. The module also has an annotate(head,list) function that adds a slash to the end of any entry in the list that is a directory: >>> x = dircache.listdir(‘c:\\sierra’)[:] # Make a copy >>> dircache.annotate(‘c:\\sierra’,x) >>> x [‘Half-Life/’, ‘LAND/’, ‘SETUP.EXE’] 163 4807-7 ch10.F 164 5/24/01 8:58 AM Page 164 Part II ✦ Files, Data Storage, and Operating System Services Use the head parameter to join to each item in the list so that annotate can then call os.path.isdir. The os.path.commonprefix(list) function takes a list of paths and returns the longest prefix that all items have in common: >>> l = [‘c:\\ax\\nine.txt’,’c:\\ax\\ninja.txt’,’c:\\axle’] >>> os.path.commonprefix(l) ‘c:\\ax’ The os.path.walk(top,func,arg) function walks a directory tree starting at top, calling func in each directory. The function func should take three arguments: arg (whatever you passed to arg in the call to walk), dirname (the name of the current directory being visited), and names (a list of directory entries in this directory). The following example prints the names of any executable files in the d:\games directory or any of its subdirectories: >>> def walkfunc(ext,dir,files): ... goodFiles = [x for x in files if x.find(ext) != -1] ... if goodFiles: ... print dir,goodFiles ... >>> os.path.walk(‘d:\\games’,walkfunc,’.exe’) d:\games\Half-Life [‘10051013.exe’] d:\games\q3a [‘quake3.exe’] d:\games\q3a\Extras\cs [‘sysinfo.exe’] With the fnmatch module you can test to see if a file name matches a specific pattern. Asterisks match everything, question marks match any single character: >>> >>> 1 >>> 1 import fnmatch fnmatch.fnmatch(‘python’,’p*n’) # It’s a match! fnmatch.fnmatch(‘python’,’pyth?n’) You can also enclose in square brackets a sequence of characters to match: >>> 1 >>> 1 >>> 0 >>> 1 fnmatch.fnmatch(‘python’,’p[a,e,i,o,u,y,0-9]thon’) # Matches p + [any vowel or number] + thon fnmatch.fnmatch(‘p5thon’,’p[a,e,i,o,u,y,0-9]thon’) fnmatch.fnmatch(‘p5thon’,’p[!0-9]thon’) # Doesn’t match p + [any char EXCEPT a digit] + thon fnmatch.fnmatch(‘python’,’p[!0-9]thon’) The fnmatch module also has a fnmatchcase(filename,pattern) function that forces a case-sensitive comparison regardless of whether or not the filesystem is case-sensitive. 4807-7 ch10.F 5/24/01 8:58 AM Page 165 Chapter 10 ✦ Working with Files and Directories The glob module takes the fnmatch module a step further by returning all the paths matching a search pattern you provide: >>> import glob >>> for file in glob.glob(‘c:\\da*\\?ytrack\\s*.*[y,e]’): ... print file c:\dave\pytrack\sdaily.py c:\dave\pytrack\std.py c:\dave\pytrack\StkHistInfo.py c:\dave\mytrack\sdkaccess1.exe c:\dave\mytrack\sdkaccess2.exe Obtaining Environment and Argument Information It’s often useful to know a little about the world around Python. This section explains how to get and set environment variables, how to discover and change the current working directory, and how to read in options from the command line. Environment variables When you import the os module, it populates a dictionary named environ with all the environment variables currently in existence. You can use normal dictionary access to get and set the variables, and child processes or shell commands your programs execute see any changes you make: >>> os.environ[‘SHELL’] ‘/usr/local/bin/tcsh’ >>> os.environ[‘BOO’] = 2 + 2 # Convert value to string. >>> print os.popen(‘echo$BOO’).read() # Use %BOO% on Win32. 4 CrossReference See Chapter 11 for information on child processes and executing shell commands. The dictionary used is actually a subclass of UserDict, and requires that the value you assign be a string. Current working directory The current working directory is initially the directory in which you started the Python interpreter. You can find out what the current directory is and change to another directory using the os.getcwd() and os.chdir(path) functions: 165 4807-7 ch10.F 166 5/24/01 8:58 AM Page 166 Part II ✦ Files, Data Storage, and Operating System Services >>> os.chdir(‘/usr/home’) >>> os.chdir(‘..’) >>> os.getcwd() ‘/usr’ Command-line parameters The sys.argv variable is a list containing the command-line parameters passed to the program on startup. Save the tiny program in Listing 10-1 to a file called args.py and try the following example from a command prompt: C:\temp>args.py pants beable There are 3 arguments [‘C:\\temp\\args.py’, ‘pants’, ‘beable’] Listing 10-1: args.py – Display Command-Line Arguments #!/usr/bin/env python # Prints out command-line arguments import sys print ‘There are %d arguments’ % len(sys.argv) print sys.argv The sys.argv list always has a length of at least one; as in C, the item at index zero is the name of the script that is running. If you’re running the Python interpreter in interactive mode, however, that item is present but is the empty string. Example: Recursive Grep Utility Listing 10-2 combines several of the features covered so far in this chapter to create rgrep, a grep-like utility that searches for a string in a list of files in the current directory or any subdirectory. The sample output below shows searching for “def” in any file that matches the pattern “d*.py” or “h*”: D:\Dev\pytrack>\rgrep.py def d*.py h* D:\Dev\pytrack\dataio.py 185 def __init__(self,sTick): D:\Dev\pytrack\dataio.py 189 def getData(self): D:\Dev\pytrack\histInfo.py 9 def sum(self,count,tups,index): D:\Dev\pytrack\histInfo.py 16 def ave(self,count,tups,index): D:\Dev\pytrack\old\dataio.py 12 def __init__(self,sTick): D:\Dev\pytrack\old\dataio.py 16 def getData(self): ... 4807-7 ch10.F 5/24/01 8:58 AM Page 167 Chapter 10 ✦ Working with Files and Directories Listing 10-2: rgrep.py – Recursive File Search Utility #!/usr/bin/env python # Recursively searches for a string in a file or list of files. import sys, os, fnmatch def walkFunc(arg,dir,files): “Called by os.path.walk to process each dir” pattern,masks = arg # Cycle through each mask on each file. for file in files: for mask in masks: if fnmatch.fnmatch(file,mask): # Filename matches! name = os.path.join(dir,file) try: # Read the file and search. data = open(name,’rb’).read() # Do a quick check. if data.find(pattern) != -1: i=0 data = data.split(‘\n’) # Now a line-by-line check. for line in data: i += 1 if line.find(pattern) != -1: print name,i,line except (OSError,IOError): pass break # Stop checking masks. if __name__ == ‘__main__’: if len(sys.argv) < 3: print ‘Usage: %s pattern file [files...]’ % sys.argv[0] else: try: os.path.walk(os.getcwd(),walkFunc,(sys.argv[1],sys.argv[2:])) except KeyboardInterrupt: print ‘** Halted **’ Tip UNIX shells usually expand wildcards before your program gets them, so when running this on UNIX you’d have to enclose in quotes command-line parameters that contain asterisks: /usr/bin> rgrep.py alligator “*.txt” 167 4807-7 ch10.F 168 5/24/01 8:58 AM Page 168 Part II ✦ Files, Data Storage, and Operating System Services You can use rgrep as a starting point for a more powerful search tool. For example, you could make it accept true regular expressions (as seen in Chapter 9) or make it support case-insensitive searches too. Although performance is pretty decent, you could fix the fact that rgrep reads the entire file into memory by reading the files one piece at a time. Copying, Renaming, and Removing Paths The routines to copy, rename, and remove paths are in the os and shutil modules. The shutil module aims to provide features normally found in command shells. Copying and linking The shutil.copyfile(src, dest) function copies a file from src to dest; shutil.copy(src, dest) does about the same thing, except that if dest is a directory it copies the file into that directory (just like when you copy a file in an MS-DOS or UNIX shell). copy also copies the permission bits of the file. The shutil.copy2 (src, dest) function is identical to copy except that it also copies last access and last modification times of the original file. shutil.copyfileobj(src, dest[, buflen]) copies two file-like objects, passing the optional buflen parameter to the source object’s read function. CrossReference See Chapter 8 for more information on filelike objects. The shutil.copymode (src, dest) function copies the permission bits of a file (see os.chmod earlier in this chapter), as does shutil.copystat(src, dest), which also copies last access and last modification times. The shutil.copytree (src, dest[, symlinks]) function uses copy2 to recursively copy an entire tree. copytree raises an exception if dest already exists. If the symlinks parameter is 1, any symbolic links in the source tree also become symbolic links in the new copy of the tree. If symlinks is omitted or equal to zero, the copy of the tree contains copies of the files referenced by symbolic links. On platforms that support links, os.symlink(src,dest) creates a symbolic link to src and names it dest, and os.link(src,dest) creates a hard link to src named dest. Renaming The os.rename(old,new) function renames a path, and os.renames(old,new) renames an entire path from one thing to another, creating new directories as needed and removing empty ones to cleanup when done. For example: os.renames(‘cache/logs’,’/usr/home/dave/backup/0105’) 4807-7 ch10.F 5/24/01 8:58 AM Page 169 Chapter 10 ✦ Working with Files and Directories basically moves the logs directory in cache to /usr/home/dave/backup and calls it 0105. If the cache directory is empty after the move, the function deletes it. Before the move, renames creates any intermediate directories along the way to make /usr/home/dave/backup/0105 a valid path. The old and new parameters can be individual files and not just entire directories. Removing The os.remove(filename) function deletes a file, os.rmdir(dir) removes an empty directory, and os.removedirs(dir) removes an empty directory and all empty parent directories. If a directory is not empty, neither rmdir nor removedirs removes it. That job is reserved for shutil.rmtree(path[, ignore_errors[, onerror]]), which recursively deletes all files in the given directory (including the directory itself) as well as any subdirectories and their files. ignore_errors is 0 by default, if you supply a value of 1 then rmtree attempts to continue processing despite any errors that occur, and won’t bother to tell you about them. You can provide a function in the onerror parameter to handle any errors that occur. The function must take three arguments, as shown in this example: >>> def errFunc(raiser,problemPath,excInfo): ... print raiser.__name__,’had problems with’,problemPath >>> shutil.rmtree(‘c:\\temp\\foo’,0,errFunc) rmdir had problems with c:\temp\foo\bar\yeah rmdir had problems with c:\temp\foo\bar rmdir had problems with c:\temp\foo The arguments passed to your error function are the function object that raised an exception, the particular path it had a problem on, and information about the exception, equivalent to a call to sys.exc_info(). Caution Please be careful with rmtree; it assumes you’re smart and trusts your judgment. If you tell it to erase all your files on your hard drive, it’ll obediently do so and without hesitation. Creating Directories and Temporary Files The os.mkdir(dir[, mode]) function creates a new directory. The optional mode parameter is for the permissions on the new directory, and they follow the form of those listed for os.chmod in Table 10-1. (If you don’t supply mode, the directory has read, write, and execute permissions for everyone.) The os.makedirs(dir[, mode]) function creates a new directory and any intermediate directories needed along the way: >>> os.makedirs(r’c:\a\b\c\d\e\f\g\h\i’) >>> os.removedirs(r’c:\a\b\c\d\e\f\g\h\i’) 169 4807-7 ch10.F 170 5/24/01 8:58 AM Page 170 Part II ✦ Files, Data Storage, and Operating System Services Even though my computer didn’t have an a directory or an a\b directory, and so on, makedirs took care of creating them until at last it created i, a subdirectory of h (and then I used os.removedirs to clean up the mess). The tempfile module helps when you need to use a file as a temporary storage area for data. In such cases you don’t generally care about a file name or where the file lives on disk, so tempfile takes care of that for you. Temporary files can help conserve memory by storing temporary information on disk instead of keeping it all loaded in memory. The tempfile.mktemp([suffix]) function returns the absolute path to a unique temporary file name that does not exist at the time of the call, and includes the suffix in the file name if you supply it. Although two calls to mktemp won’t return the same file name, it doesn’t create the file, so it’s possible (although quite unlikely) that if you wait long enough someone else may create a file by the same name. While it’s safe to use the file name as soon as you get it, it isn’t as safe to save a copy of the name and then at a later date expect to create a file by that name, for example. You can set the tempfile.tempdir variable to tell mktemp where to store temporary files. By default, it tries its best to find a good home for them, first checking the values of the environment variables $TMPDIR,$TEMP, and $TMP. If none of them are defined, it then checks if it can create temporary files in known temporary file safe-havens such as /var/temp, /usr/tmp, or /tmp on UNIX and c:\temp or \temp on Windows. If all these fail, it’ll try to use the current working directory. tempfile.gettempprefix() returns the prefix of the temporary files you have (you can set this value via tempfile.template). The ultimate in hassle-free temporary files comes from the tempfile. TemporaryFile class. It gives you a file or filelike object that you can read and write to without worrying about cleanup when you’re done. You use tempfile.TemporaryFile([mode[, bufsize[, suffix]]]) to create a new instance object. The following example figures out how many digits it takes to write out the numbers from 1 to high. (Of the many better ways to do this, the simplest improvement is simply to add the length of each number to a counter instead of building the entire string and taking its length, but that wouldn’t give me an opportunity to use TemporaryFile now would it?): >>> def digitCount(high): ... import tempfile ... f = tempfile.TemporaryFile() ... for i in range(1,high+1): ... f.write(i) ... f.flush() ... f.seek(0) ... return len(f.read()) >>> digitCount(12) 15 # len(‘123456789101112’) = 15 >>> digitCount(100) 192 >>> digitCount(100000) 488895 4807-7 ch10.F 5/24/01 8:58 AM Page 171 Chapter 10 ✦ Working with Files and Directories By default, mode is ‘w+b’ so you can read and write data and not worry about the type of data you’re writing (binary or text). The optional bufsize argument gets passed to the open function, and the optional suffix argument is passed to mktemp. On UNIX systems, the file doesn’t even have a directory entry, making it more secure. Other systems delete the temporary file as soon as you call close or when Python garbage collects the object. On UNIX systems, the os module has three functions for working with temporary files. os.tmpfile() creates a new file object that you can read and write to. As with tempfile’s TemporaryFile class, the file has no directory entry and ceases to exist when you close the file. The os.tmpnam() function returns an absolute path to a unique file name suitable for use as a temporary file (it doesn’t create an actual file). os.tempnam([dir, [prefix]]) does the same as tmpnam except that it enables you to specify the directory in which the file name will live, as well as supplies an optional prefix to use in the temporary file’s name. Comparing Files and Directories The filecmp module aids in comparing files and directories. To compare two files, call filecmp.cmp(f1,f2[,shallow[,use_statcache]]): >>> import filecmp >>> open(‘one’,’wt’).write(‘Hey’) >>> open(‘two’,’wt’).write(‘Hey’) >>> filecmp.cmp(‘one’,’two’) 1 # Files match The shallow parameter defaults to 1, which means that if both are regular files with the same size and modification time, the comparison returns true. If they differ (or if shallow=0), the function compares the contents of the two. The use_statcache parameter defaults to 0 and cmp calls os.stat for file info. If 1, cmp calls statcache.stat. The filecmp.cmpfiles(a, b, common[, shallow[, use_statcache]]) function takes a list of file names located in two directories (each file is in both directory a and b) and returns a three-tuple containing a list of files that compared equal, a list of those that were different, and a list of files that weren’t regular files and therefore weren’t compared. The shallow and use_statcache parameters behave the same as for cmp. The dircmp class in the filecmp module can help you generate that list of common files, as well as do some other comparison work for you. You use filecmp. dircmp(a, b[, ignore[, hide]]) to create a new instance: 171 4807-7 ch10.F 172 5/24/01 8:58 AM Page 172 Part II ✦ Files, Data Storage, and Operating System Services >>> d = filecmp.dircmp(‘c:\\Program Files’,’d:\\Program Files’) >>> d.report() diff c:\Program Files d:\Program Files Only in c:\Program Files : [‘Accessories’, ‘Adobe’, ...<snip> Only in d:\Program Files : [‘AnalogX’, ‘Paint Shop Pro...<snip> Common subdirectories : [‘WinZip’, ‘Yahoo!’,’work’] The ignore function is a list of file names to ignore (it defaults to [‘RCS’, ‘CVS’, ‘tags’]) and hide is a list of file names not to show in the listings (it defaults to [os.curdir, os.pardir], the entries corresponding to the current and parent directories). The dircmp.report() method prints to standard output a comparison between a and b. dircmp.report_partial_closure() does the same, but also compares common immediate subdirectories. dircmp.report_full_closure() goes the whole nine yards and compares all common subdirectories, no matter how deep. After you create a dircmp object, you can access any of the attributes listed in Table 10-4 for more information about the comparison. Table 10-4 Other dircmp Object Attributes Attribute left_list Items in a after being filtered through hide and ignore right_list Items in b after being filtered through hide and ignore common Items in both a and b left_only Items only in a right_only Items only in b common_dirs Subdirectories found in both a and b common_files Files found in both a and b common_funny Items found in both a and b, but either the type differs between a and b or os.stat reports an error for that item same_files Common_files that are identical diff_files Common_files that are different funny_files Common_files that couldn’t be compared subdirs Tip Description Dictionary of dircmp objects — keys are common_dirs The Python distribution comes with ndiff (Tools/Scripts/ndiff.py), a utility that provides the details of what differs between two files (similar to the UNIX diff and Windows windiff utilities). 4807-7 ch10.F 5/24/01 8:58 AM Page 173 Chapter 10 ✦ Working with Files and Directories Working with File Descriptors An alternative to using Python’s file objects is to use file descriptors, a somewhat lower level approach to working with files. General file descriptor functions You create a file descriptor with the os.open(file, flags[, mode]) function. You can combine various values from the next table, Table 10-5, for the flags parameter, and the mode values are those you pass to os.chmod: >>> fd = os.open(‘fumble.txt’,os.O_WRONLY|os.O_CREAT) >>> os.write(fd,’I like fudge’) 12 # Wrote 12 bytes. >>> os.close(fd) >>> open(‘fumble.txt’).read() # Use the nice Python way. ‘I like fudge’ The os.dup(fd) function returns a duplicate of the given descriptor, and os.dup2(fd1,fd2) makes fd2 a duplicate of fd1, but closes fd2 first if necessary. Given a file descriptor, you can use os.fdopen(fd[, mode[, bufsize]]) to create an open Python file object connected to the same file. The optional mode and bufsize arguments are the same as those used for the normal Python open function. Table 10-5 File Descriptor Open Flags Name Description O_RDONLY Allow reading only O_WRONLY Allow writing only O_RDWR Allow reading and writing O_BINARY Open in binary mode O_TEXT Open in text mode O_CREAT Create file if it does not exist O_EXCL Return error if create and file exists O_TRUNC Truncate file size to 0 O_APPEND Append to the end of the file on each write O_NONBLOCK Do not block 173 4807-7 ch10.F 174 5/24/01 8:58 AM Page 174 Part II ✦ Files, Data Storage, and Operating System Services The os module also has other flags such as O_DSYNC, O_RSYNC, O_SYNC, and O_NOCTTY. Their behavior varies by platform so you should consult the UNIX open man page for your system for details. CrossReference The os.openpty function returns two file descriptors for a new pseudo-terminal. See Chapter 38 for details. The following os file descriptor functions closely mirror their file method counterparts covered mostly in Chapter 8, “Input and Output”: close(fd) write(str) isatty(fd) lseek(fd,pos,how) fstat(fd) ftruncate(fd,len) read(fd,n) UNIX systems can use the os.ttyname(fd) to retrieve the name of the terminal device the file descriptor represents (if it is a terminal): >>> os.ttyname(1) # 1 is stdout ‘/dev/ttyv1’ Pipes A pipe is a communications mechanism through which you can read or write data as if it were a file. You use os.pipe() to create two file descriptors connected via a pipe: >>> r,w = os.pipe() # One for reading, one for writing >>> os.write(r,’Pipe dream’) >>> os.write(w,’Pipe dream’) 10 >>> os.read(r, 1000) ‘Pipe dream’ On UNIX, the os.mkfifo(path[, mode]) function creates a named pipe (FIFO) that you can use to communicate between processes. The mode defaults to read and write permissions for everyone (0666). After you create the FIFO on disk, you open it and read or write to it just like any other file. Other File Processing Techniques The modules below provide alternative methods for operating on file contents. Randomly accessing lines in text files The linecache module returns to you any line in any file you want: >>> import linecache 4807-7 ch10.F 5/24/01 8:58 AM Page 175 Chapter 10 ✦ Working with Files and Directories >>> linecache.getline(‘linecache.py’,5) ‘that name.\012’ The first time you request a line from a particular file, it reads the file and caches the lines, but future calls for lines from the same file won’t have to go back to the disk. Line numbers are 1-based (yes, line one is line one). If keeping too many files around makes you nervous, you can call linecache. clearcache() to empty the cache. Also, calling linecache.checkcache() tosses out cached entries that are no longer valid. Note This module was designed to read lines from modules (Python uses it to print traceback information in exceptions), so if linecache can’t find the file you named it also searches for the file in the module search path. Using memory-mapped files A memory-mapped file (in the mmap module) behaves like some sort of file-mutable string hybrid. You can access individual characters and slices as well as change them, and you can use memory-mapped files with many routines that expect strings. (The re module, for example, is quite happy to do regular expression searching and mapping on a memory-mapped file.) They also work well for routines that operate on files, and you can commit to disk any changes you make to their contents. When you create a new mmap object, you supply a file descriptor to a file opened for reading and writing and a length parameter specifying the number of bytes from the file the memory map will use: >>> f = open(‘mymap’,’w+b’) >>> f.write(‘And now for something completely different’) >>> f.flush() >>> import mmap >>> m = mmap.mmap(f.fileno(),45) # Use the open file mymap. >>> m[5:10] # It slices. ‘ow fo’ >>> m[5:10] = ‘ew fi’ # It dices. >>> m[5:10] ‘ew fi’ >>> m.flush(); m.close() # But wait, there’s more! 1 >>> open(‘mymap’).read() ‘And new fir something completely different\000\000\000’ The Windows version for creating a new mmap object accepts an optional third argument of a string that represents the tag name for the mapping (Windows lets you have many mappings for the same file). If you use a mapping that doesn’t exist, Python creates a new one; otherwise the mapping by that name is opened. 175 4807-7 ch10.F 176 5/24/01 8:58 AM Page 176 Part II ✦ Files, Data Storage, and Operating System Services The UNIX version optionally takes flags and prot arguments. flags can be either MAP_PRIVATE or MAP_SHARED (the default), signifying that changes are visible only to the current process or are visible to all processes mapping the same portions of the file. The prot argument is the logical OR of arguments specifying the type of protection that mapping has, such as PROT_READ | PROT_WRITE (the default). Avoid using the optional flags if possible so that your code will work on Windows or UNIX. Tip You can use mmap.size() to retrieve the size of a mmap object, and mmap.resize(newsize) to change it: >>> m.size() 50 >>> m.resize(100) Call mmap.flush([offset, size]) to save changes to disk. Passing no arguments flushes all changes to disk, otherwise the memory map flushes only size bytes starting at offset. Caution Don’t forget to flush. If you don’t call flush, you have no guarantee that your changes will make it to disk. All mmap objects have the close(), tell(), seek(), read(num), write(str), readline(), and find(str[, start]) methods which behave just like their file and string counterparts. The mmap.read_byte() and mmap.write_byte(byte) methods are useful for reading and writing one byte at a time (the bytes are passed and returned as strings of length 1). You can copy data from one location to another within the memory-mapped file using mmap.move(dest, src, count). It copies count bytes from src to dest. Iterating over several files The fileinput class lets you iterate over several files as if they were a single file, eliminating a lot of the housekeeping involved. Its designed use is for iterating all files passed in on the command line, processing each line individually: >>> import fileinput >>> for line in fileinput.input(): ... print line The above example iterates over the files listed in sys.argv[1:] and prints out each line. The input(files,inplace,backup) function uses the command-line arguments if you don’t pass it a files list. Any file (or command-line argument) that is just ‘-’ reads from stdin instead. If the inplace parameter is 1, fileinput copies each file to a backup and routes any output on stdout to the original file, thus enabling in-place modification or filtering of each file. If inplace is 1 and you supply a value for backup (in the form of ‘.ext’), fileinput uses backup’s value as an extension when creating backups of the original files, and it doesn’t erase the backups when finished. 4807-7 ch10.F 5/24/01 8:58 AM Page 177 Chapter 10 ✦ Working with Files and Directories While iterating over the files, you can call fileinput.filename() to get the name of the current file, and filename.isstdin() to test if the current file is actually stdin. The fileinput.lineno() function gives you the overall line number of the line just read, and fileinput.filelineno() returns the number of that line within the current file. You can also call fileinput.isfirstline() to see if it is the first line of that file. The fileinput.nextfile() function skips the rest of the current file and moves to the next one in the sequence, and fileinput.close() closes the sequence and quits. Tip You can customize the fileinput functionality by subclassing the fileinput. FileInput class. Summary Python gives you a full toolbox of high-level functions to manipulate files and paths. In this chapter you learned to: ✦ Manipulate paths and retrieve file and directory information. ✦ Traverse directory trees and match file names to search patterns. ✦ Create and destroy directories and temporary files. ✦ Use file descriptors. The next chapter covers more of Python’s operating system features. You’ll learn to access process information, start child processes, and run shell commands. ✦ ✦ ✦ 177 4807-7 ch10.F 5/24/01 8:58 AM Page 178 4807-7 ch11.F 5/24/01 8:59 AM Page 179 11 CHAPTER Using Other Operating System Services T his chapter finishes coverage of Python’s main operating system services. One of the main points of focus is working outside the boundaries in which the interpreter is running. After you’re done with this chapter you’ll be able to execute commands in a sub-shell or spawn off an entirely new process. Executing Shell Commands and Other Programs The simplest way to execute a shell command is with the os.system(cmd) function (which is just a wrapper for the C system function). The following example uses the shell command echo to write contents to a file, including an environment variable set from within the Python interpreter: >>> import os >>> os.environ[‘GRUB’] = ‘spam!’ >>> os.system(‘echo Mmm, %GRUB% > mm.txt’) # Use$GRUB on UNIX 0 >>> print open(‘mm.txt’).read() Mmm, spam! The return values vary by system and command, but 0 generally means the command executed successfully. Unfortunately, os.system has some limitations. On Windows, your command runs in a separate MS-DOS window that rears its ugly head until the command is done, and on all operating systems it’s kind of a pain to retrieve the output from the command (especially if the output is on both stdout and ✦ ✦ ✦ ✦ In This Chapter Executing shell commands and other programs Spawning child processes Handling process information Retrieving system information Managing configuration files Understanding error names Handling asynchronous signals ✦ ✦ ✦ ✦ 4807-7 ch11.F 180 5/24/01 8:59 AM Page 180 Part II ✦ Files, Data Storage, and Operating System Services stderr). The next section shows how to get around this using the much cleaner calls to os.popen and friends. Windows systems can use os.startfile(path) to launch a program by sending a file to the program associated with its file type. For example, if the current directory has a file called yoddle.html, you can launch a Web browser to view that file like this: >>> os.startfile(‘yoddle.html’) The os.exec family of functions executes another program, but in doing so replaces the current process — your program doesn’t continue when the exec function returns. Instead, your program terminates and at the same time launches a different program. Each of the exec functions comes in two versions: one that accepts a variable number of arguments and one that takes all the program’s arguments in a list or tuple. All arguments are strings, and you always need to provide argument 0, which is just the name of the program being executed. The os.execv(path,args) and os.execl(path, arg0, arg1, ...) functions execute the program pointed to by path and pass it the arguments. The following example shuts down the Python interpreter and launches the Windows calculator (the location of the calc program may vary): >>> os.execv(‘c:\\winnt\\system32\\calc’,[‘calc’]) The os.execvp(file, args) and os.execlp(file, arg0, arg1, ...) functions work the same as execv, except they look in the PATH environment variable to find the executable, so you don’t have to name its absolute path. This example calls another Python interpreter, telling it to just print out a message. Note the use of the variable-argument form (execlp) and that you still have to list the program twice, once for the file argument, and once as argument 0: >>> os.execlp(‘python’,’python’,’-c’,’”print \’Goodbye!\’”’) Tip If you need to modify the PATH environment variable, you can use os.defpath to see the default PATH used if it isn’t set in the environment. os.pathsep is the separator character used between each directory listed in the PATH variable. The os.execve(path, args, env) and os.execle(path, arg0, arg1, ..., env) functions are also like execv, except that you pass in a dictionary containing all the environment variables to be defined for the new program. The dictionary should contain string keys mapping to string values. The final exec functions, os.execvpe(file, args, env) and os.execlpe(file, arg0, arg1, ..., env), are like execve and execvp combined. You pass in a file name instead of an absolute path because the functions search through the path for you, and you also pass in a dictionary of environment variables to use. 4807-7 ch11.F 5/24/01 8:59 AM Page 181 Chapter 11 ✦ Using Other Operating System Services Note You don’t really have to name the program twice for the exec calls. When supplying a value for argument 0, you can actually use any value you want. Be advised, however, that some programs (like gzip and gunzip) may expect argument 0 to have certain values. Spawning Child Processes Depending on your needs, you can start child processes using the popen, spawn, and fork functions. popen functions The popen family of functions opens pipes to communicate with a child process. The os.popen(cmd[, mode[, bufsize]]) function opens a single pipe to read or write to another process. You pass in the command to execute in the cmd parameter, followed by an optional mode parameter to tell whether you’ll be reading (‘r’) or writing (‘w’) with the pipe. An optional third parameter is a buffer size like the one used in the built-in open function. popen returns a file object ready for use: >>> a = os.popen(‘dir /w /ad e:\\’) # Mode defaults to ‘r’. >>> print a.read() Volume in drive E has no label. Volume Serial Number is 2C40-1AF5 Directory of e:\ [RACER] [FlaskMPEG] [VNC] [AnalogX] ... [maxdev] [Diablo II] [dxsdk] [Python20] [VideoDub] [archive] [VMware] The close() method of the file object returns None if the command was successful, or an error code if the command was unsuccessful. The os.popen2(cmd[, bufsize[, mode]]) function is a more flexible alternative to popen; it returns to you the two-tuple (stdin, stdout) containing the standard input and output of the child process (the mode parameter is ‘t’ for text or ‘b’ for binary). The following example uses the external program grep to look through lines of text and print any that have a colon character in them: >>> someText = “”” ... def printEvents(): ... for i in range(100): ... if i % 2 == 0: ... print i 181 4807-7 ch11.F 182 5/24/01 8:59 AM Page 182 Part II ✦ Files, Data Storage, and Operating System Services ... “”” >>> w,r = os.popen2(‘grep “:”’) # Grep for lines with ‘:’ >>> w.write(someText) >>> w.close() >>> print r.read() def printEvents(): for i in range(100): if i % 2 == 0: Tip Depending on the program you execute, you often need to flush or even close stdin of the child process in order to have it produce its output. The os.popen3(cmd[, bufsize[, mode]]) function does the same work as popen2 but instead returns the three-tuple (stdin, stdout, stderr) of the child process. os.popen4(cmd[, bufsize[, mode]]) does the same except that it returns the output of stdout and stderr together in a single stream for convenience. This function is a great way to execute arbitrary shell commands cleanly because you have to look in only one place for the output, and no matter what the command is, your users won’t see error output sneaking past you and onto the screen. And on Windows systems, you don’t get the ugly MS-DOS window while your command executes: >>> w,r = os.popen4(‘iblahblahasdfasdfr *.foo’) >>> print r.read() ‘iblahblahasdfasdfr’ is not recognized as an internal or external command, operable program or batch file. New Feature The popen2, popen3, and popen4 functions were new in Python 2.0. spawn functions The spawn functions start a child process that doesn’t replace the current process (like the exec functions do) unless specifically asked to. For example, to start up another Python interpreter (assuming it lives in D:\Python20) without stopping the current one: >>> os.spawnl(os.P_NOWAIT,’d:\\python20\\python’,’python’) 400 # Process ID of new interpreter Like the exec functions, the spawn functions have many variations, as shown in the following paragraphs. os.spawnv(mode, path, args) and os.spawnl(mode, path, arg0, arg1, ...) start a new child process. os.spawnve(mode, path, args, env) and os.spawnle(mode, path, arg0, arg1, ..., env) start a child process using the environment variables contained in the dictionary env. 4807-7 ch11.F 5/24/01 8:59 AM Page 183 Chapter 11 ✦ Using Other Operating System Services On UNIX systems, variants of each of the above functions search the current path for the program to execute, and are named spawnlp, spawnlpe, spawnvp, and spawnvpe. The arguments passed in should include the program name for argument 0. A mode of os.P_WAIT forces the current thread to wait until the child process ends. os.P_NOWAIT runs the child process concurrently, and os.P_OVERLAY terminates the calling process before running the child process (making it identical to the exec functions). os.P_DETACH also runs the process concurrently, but in the background where it has no access to the console or the keyboard. When you start a child process concurrently, the spawn function returns the process ID of the child process. If you use os.P_WAIT instead, the function returns the exit code of the child once the child process finally quits. fork The os.fork() function (available on UNIX systems) creates a new process that is a duplicate of the current process. To distinguish between the two processes, os.fork() returns 0 in the child process, and in the parent process it returns the process ID of the child: >>> def forkFunc(): ... pid = os.fork() ... if pid == 0: ... print ‘I am the child!’ ... os._exit(0) ... else: ... print ‘I am the parent. Child PID is’,pid >>> forkFunc() I am the parent. Child PID is 1844 I am the child! Notice that the child process can force itself to terminate by calling os._exit(status), which terminates a process without the usual cleaning up (which is good because the parent and child processes access some of the same resources, such as open file descriptors). CrossReference Chapter 38 has information on the pty (pseudo-terminal) module, its fork and spawn functions, and the os.forkpty function. Process management and termination When you call os._exit() to end a process, Python skips the normal cleanup operations. The normal way to end the current process is by calling sys.exit([status]). The status parameter can be a numerical status code that Python returns to the parent process (which by convention is 0 for success and nonzero for an error), or any other object. For non-numeric objects, sys.exit prints the object to stderr and then 183 4807-7 ch11.F 184 5/24/01 8:59 AM Page 184 Part II ✦ Files, Data Storage, and Operating System Services exits with a status code of 1, making it a useful way for programs to exit when users supply invalid command-line arguments: >>> import sys >>> sys.exit(‘Usage: zapper [-force]’) Usage: zapper [-force] C:\> Other ways to shut down Another way to terminate the current process is by raising the SystemExit exception (which is what sys.exit does anyway). You can cause the process to terminate abnormally by calling os.abort(), causing it to receive a SIGABRT signal. The atexit module provides a way for you to register cleanup functions for Python to call when the interpreter is shutting down normally. You can register multiple functions, and Python calls them in the reverse order of how you registered them. Use atexit.register(func [, args]) to register each function, where args are any arguments (normal or keyword) that you want sent to the function: >>> import atexit >>> def bye(msg): ... print msg >>> def allDone(*args): ... print ‘Here are my args:’,args >>> atexit.register(bye,”I’m melting!”) >>> atexit.register(allDone,1,2,3) >>> raise SystemExit # Shut down. Here are my args: (1, 2, 3) I’m melting! New Feature The atexit module was new in Python 2.0. Waiting around On UNIX systems, you can call os.wait([option]) to wait for any child process to stop or terminate, or os.waitpid(pid,option) to wait for a particular child process. The values available to use for the option parameter vary by system, but you can always use os.WNOHANG to tell wait to return immediately if no processes have a termination to report, or 0 to wait. The wait functions return a two-tuple (pid,status), and you can decipher the status using any of the os functions listed in Table 11-1. The following example forks off a child process that sleeps for five seconds and then exits. The parent waits until the child finishes and then prints the exit information for the child: 4807-7 ch11.F 5/24/01 8:59 AM Page 185 Chapter 11 ✦ Using Other Operating System Services >>> import os,time >>> def useless(): ... z = os.fork() ... if z == 0: ... for i in range(5): ... time.sleep(1) ... os._exit(5) ... else: ... print ‘Waiting on ‘,z ... status = os.waitpid(z,0)[1] ... print ‘Exited normally:’,os.WIFEXITED(status) ... print ‘Exit code:’,os.WEXITSTATUS(status) >>> useless() Waiting on 1915 Exited normally: 1 Exit code: 5 Table 11-1 Wait Status Interpretation Functions Function WIFSTOPPED(status) 1 if process was stopped (and not terminated) WSTOPSIG(status) Signal that stopped the process if WIFSTOPPED was true WIFSIGNALED(status) 1 if process was terminated due to a signal WTERMSIG(status) Signal that terminated the process if WIFSIGNALED was true WIFEXITED(status) 1 if the process exited due to _exit() or exit() WEXITSTATUS(status) CrossReference Value returned Status code if WIFEXITED was true Instead of spawning off separate processes to do your bidding, you may just need to use threads. Chapter 26 covers multithreaded Python programs. Handling Process Information Table 11-2 lists the plethora of functions in the os module for getting and setting information about the current process. Except where noted, the functions are available only on UNIX. 185 4807-7 ch11.F 186 5/24/01 8:59 AM Page 186 Part II ✦ Files, Data Storage, and Operating System Services Table 11-2 Process Information Functions in os Functions Description getpid() Gets the current process ID (Windows and UNIX). getppid() Gets the parent process ID. getegid() / setegid(id) Gets/sets effective group ID. getgid() / setgid(id) Gets/sets group ID. getuid() / setuid(id) Gets/sets user ID. geteuid() / seteuid(id) Gets/sets effective user ID. getprgrp() / setprgrp() Gets/sets process group ID. ctermid() Gets the file name of the controlling terminal. getgroups() Gets list of group IDs for this process. getlogin() Gets actual login name for current process. setpgid(pid, pgrp) Sets the process group for process pid (or the current process if pid is 0). setreuid(ruid, euid) Sets real and effective user IDs for the current process. setregid(rgid, egid) Sets real and effective group IDs for the current process. tcgetprgrp(fd) Gets the process group ID associated with fd (an open file descriptor of a terminal device). tcsetpgrp(fd, pg) Sets the process group ID associated with fd (an open file descriptor of a terminal device). setsid() Creates a new session/process group and returns the process group ID. The calling process is the group leader of the new process group. umask(mask) Sets the process’s file mode creation mask and returns the previous mask (Windows and UNIX). Nice(inc) Adds inc to the process’s nice value. The more you add, the lower the scheduling priority of that process (nicer means less important to the task scheduler). For example, the following gets the current process’s ID: >>> os.getpid() 1072 # Hi, I’m process 1072. 4807-7 ch11.F 5/24/01 8:59 AM Page 187 Chapter 11 ✦ Using Other Operating System Services Retrieving System Information Many programs don’t need to know too much about the platform on which they run, but when they do need to know, there’s plenty of information available to them: >>> import os, sys >>> os.name # Name of the os module implementation ‘posix’ >>> sys.byteorder # Is the processor big or little endian? ‘little’ >>> sys.platform # Platform identifier ‘freebsd3’ >>> os.uname() # UNIX only (‘FreeBSD’, ‘’, ‘3.4-RELEASE’, ‘FreeBSD 3.4-RELEASE #0’,’i386’) The five-tuple returned by os.uname is (sysname, nodename, release, version, machine). CrossReference See Chapter 38 for coverage of the UNIX statvfs module, useful for retrieving file system information. UNIX system configuration information is available through os.confstr, os.sysconf, os.pathconf, and os.fpathconf: os.confstr(name) Returns the string value for the specified configuration item; the list of items defined for the current platform is in os.confstr_ names. os.sysconf(name) Similar to os.confstr(name) except that the values os.sysconf(name) returns are integers. It also lists the names of the items you can retrieve. os.pathconf(path,name) and os.fpathconf(fd,name) Return system configuration information relating to a specific path of an open file descriptor. os.pathconf_names lists valid names. For example, to retrieve the system memory page size you can use the following: >>> os.sysconf(‘SC_PAGESIZE’) 8192 CrossReference Chapter 37 covers the winreg module that lets you access system information stored in the Windows registry. 187 4807-7 ch11.F 188 5/24/01 8:59 AM Page 188 Part II ✦ Files, Data Storage, and Operating System Services Managing Configuration Files The ConfigParser module makes reading and writing configuration files simple. Users can simply edit the configuration files to set various run-time options to customize your program’s behavior. The config files are normal text files, organized into sections that contain key-value pairs. The files can have comments and can contain variables that ConfigParser evaluates when your program accesses them. If you save the file shown in Listing 11-1 to your current working directory as sample.cfg, you can then follow along with the examples. Listing 11-1: sample.cfg – Sample Configuration File # This listing is a sample configuration file. # Comment lines start with pound symbols or semicolons. [Server] Address=171.15.2.5 Port=50002 [Hoth] ID: %(team)s-1 Team=gold DefaultName=%(__name__)s_User Notice that the file can contain blank and comment lines, and that key-value pairs can be separated by equal signs or colons. A value can be anything, and you can use variable substitution to create values from other values. For example, %(team)s evaluates to the value of the team variable, and %(__name__)s evaluates to the name of the current section. If ConfigParser does not find a variable name in the current section, it also looks in a section named DEFAULT. The variable name in parentheses should be lowercase. You create a ConfigParser by calling ConfigParser.ConfigParser([defaults]), where defaults is an optional dictionary containing values for the DEFAULT section. The readfp(f[, filename]) method reads a config file from an open filelike object. If the filelike object has a filename attribute, ConfigParser uses that for the config file’s name (some exceptions it raises include the file name). You can also pass in an optional file name to use. The read(filenames) method reads in the contents of one or more config files. It fails silently on nonexistent files, making it safe to pass in a list of potential config files that may or may not exist: >>> import ConfigParser >>> cfg = ConfigParser.ConfigParser() >>> cfg.read(‘sample.cfg’) [‘Server’, ‘Hoth’] 4807-7 ch11.F 5/24/01 8:59 AM Page 189 Chapter 11 ✦ Using Other Operating System Services When ConfigParser encounters an error while reading a file or retrieving values, it raises one of the exceptions listed in Table 11-3. Table 11-3 ConfigParser Exceptions Exception Raised when NoSectionError The specified section does not exist. DuplicateSectionError A section with the specified name already exists. NoOptionError An option with the specified name does not exist. InterpolationError A problem occurred while performing variable evaluation. InterpolationDepthError The variable evaluation required too many recursive substitutions. MissingSectionHeaderError A key-value pair is not part of any section. ParsingError ConfigParser encountered a syntactic problem not covered by any of the other exceptions. Once you have a valid ConfigParser instance object, you can use its methods to get and set values or learn more about the configuration file. The defaults() method returns a dictionary containing the default key-value pairs for this instance. sections() returns a list of section names for this config file (not including DEFAULT), and has_section(section) is a quick way to see if a given section exists. For any section, the options(section) method returns a list of options in that section, and has_option(section, option) tests for the existence of a particular option in that section: >>> cfg.has_option(‘Server’,’port’) 1 >>> cfg.options(‘Server’) [‘address’, ‘port’] Use the get(section, option[, raw[, vars]]) method to retrieve the value of an option in a given section. If raw is 1, no variable evaluation takes place. You can optionally pass in a dictionary of key-value pairs that get uses in the variable evaluation: >>> cfg.get(‘Hoth’,’ID’,1) # Raw version ‘%(team)s-1’ >>> cfg.get(‘Hoth’,’ID’) # After variable evaluation ‘gold-1’ >>> cfg.get(‘Hoth’,’ID’,vars={‘team’:’blue’}) ‘blue-1’ # Override values in the file 189 4807-7 ch11.F 190 5/24/01 8:59 AM Page 190 Part II ✦ Files, Data Storage, and Operating System Services ConfigParser has a few other get convenience methods. getint(section, option) coerces the value into an integer before returning it, getfloat(section, option) does the same for floats, and getboolean(section,option) makes sure the value is a 0 or a 1 and returns it as an integer. You can create a new section using the add_section(section) method, and you can set the value for an option by calling set(section, option, value): >>> cfg.get(‘Server’,’port’) ‘50002’ >>> cfg.set(‘Server’,’port’,’4000’) # Use string values! >>> cfg.get(‘Server’,’port’) ‘4000’ The write(file) method writes the configuration file out to the given filelike object. The output is guaranteed to be readable by a future call to read or readfp. The remove_option(section, option) method removes the given option from the given section. If the option didn’t exist, remove_option returns 0, otherwise 1. remove_section(section) removes the given section from the config file. As with remove_option, remove_section returns 0 if the section didn’t even exist, 1 otherwise. Understanding Error Names When an error occurs in the os module, it usually raises the OSError exception (found in os.error). OSError is a class, and instances of this class have the errno and strerror members that you can access to learn more about the problem: >>> try: ... os.close(-1) # A bogus file descriptor ... except OSError, e: ... print ‘Blech! %s [Err #%d]’ % (e.strerror,e.errno) ... Blech! Bad file descriptor [Err #9] The strerror member is the result of calling os.strerror(code) with the errno member of the exception: >>> os.strerror(2) ‘No such file or directory’ The errno module contains the textual message for each error code. The list of defined errors varies by system (for example, the Windows version includes some Winsock error messages), but you can access the whole list through the errno. errorcode dictionary. 4807-7 ch11.F 5/24/01 8:59 AM Page 191 Chapter 11 ✦ Using Other Operating System Services For errors involving files or directories, the filename member of OSError has a non-empty value: >>> try: ... os.open(‘asdfsf’,os.O_RDONLY) ... except OSError, e: ... print e.errno, e.filename, e.strerror ... 2 asdfsf No such file or directory Handling Asynchronous Signals The signal module lets your programs handle asynchronous process signals. If you’ve used the underlying C equivalents, you’ll find that the Python version is pretty similar. A signal is just a message sent from the operating system or a process to the current process; most signals aren’t handled directly by the process but are handled by default behavior in the operating system. The signal module lets you register handler functions that override the default behavior and let your process respond to the signal itself. To register a signal handler, call signal.signal(num,handler) where num is the signal to handle and handler is your handler function. A signal handler should take two arguments, the signal number and a frame object containing the current stack frame. Instead of a function, handler can also be signal.SIG_DFL (meaning that you want the default behavior to occur for that signal) or signal.SIG_IGN (meaning that you want that signal to be ignored). The signal function returns the previous value of handler. The signals that you can process vary by platform and are defined in your platform’s signal.h file, but Table 11-4 lists some of the most common signals. Table 11-4 Common Signals Name Description SIGINT Interrupt (Ctrl-C hit) SIGQUIT Quit the program SIGTERM Request program termination SIGFPE Floating point error occurred (for example, division by zero, overflow) SIGALRM Alarm signal (not supported on Windows) SIGBUS Bus error SIGHUP Terminal line hangup SIGSEGV Illegal storage access 191 4807-7 ch11.F 192 5/24/01 8:59 AM Page 192 Part II ✦ Files, Data Storage, and Operating System Services The getsignal(signalnum) function returns the current handler for the specified signal. It returns a callable Python object, SIG_DFL, SIG_IGN, or None (for nonPython signal handlers). default_int_handler is the default Python signal handler. Except for handlers for SIGCHD, all signal handlers ignore the underlying implementation and continue to work until they are reset. Even though the signal handling happens asynchronously, Python dispatches the signals between bytecode instructions, so a long call into a C extension module could delay the arrival of some signals. On UNIX, you can call signal.pause() to wait until a signal arrives (at which time the correct handler receives it). signal.alarm(time) causes the system to send a SIGALRM signal to the current process after time seconds; it returns the number of seconds left until the previous alarm would have gone off (if any). alarm cancels any previous alarm, and a time of 0 removes any current alarm. You can also call os.kill(pid, sig) to send the given signal to the process with the ID of pid. Caution Be careful when using threads and signals in the same program. In such cases you should call signal.signal only from the main thread (although other threads can call alarm, pause, and getsignal). Be aware that signals are always sent to the main thread, regardless of the underlying implementation. The following example prompts the user for input, but times out if the user doesn’t respond in the allotted time (it uses signal.alarm, so it works on UNIX systems): import signal,sys def handler(sig, frm): raise ‘timeout’ # Raise an exception when time runs out. signal.signal(signal.SIGALRM,handler) # Set up the handler. try: signal.alarm(2.5) # Send ALARM signal in 2.5 seconds. while 1: print ‘Enter code to halt detonation:’, s = sys.stdin.readline() if s.strip() == ‘stop’: print ‘You did it!’ break print ‘Sorry.’ signal.alarm(0) # Disable the alarm. except: # Handle all exceptions so Ctrl-C will blow you up too. print ‘\nSorry. Too late.\n*KABOOM*’ I saved the file as sig.py. Here’s some sample output: /work> python sig.py Enter code to halt detonation: Sorry. Too late. *KABOOM* [ Wait a few seconds. ] 4807-7 ch11.F 5/24/01 8:59 AM Page 193 Chapter 11 ✦ Using Other Operating System Services /work> python sig.py Enter code to halt detonation: Sorry. Enter code to halt detonation: You did it! foo stop Summary Python’s great support for executing shell commands makes it an ideal solution as a scripting language or as a glue that holds various technologies together. Python also has ample functionality for starting, controlling, and monitoring child processes. In this chapter you learned to: ✦ Launch other programs in the foreground or the background. ✦ Access process and system configuration information. ✦ Read and write human-readable configuration files. ✦ Used file descriptors. ✦ Interpret os error message codes. In the next chapter you’ll learn to covert data between various formats, compress it, and decompress it. You’ll also learn to convert Python objects to byte streams that can be saved for later retrieval or transmitted across a network. ✦ ✦ ✦ 193 4807-7 ch11.F 5/24/01 8:59 AM Page 194 4807-7 ch12.F 5/24/01 8:59 AM Page 195 12 CHAPTER Storing Data and Objects ✦ ✦ ✦ ✦ In This Chapter T his chapter covers the many ways that you can convert Python objects to some form suitable for storage. Storage, however, is not limited to just saving data to disk. By the end of this chapter you’ll be able to take a Python object and stick it in a database, compress it, send it across a network connection, or even convert it to a format that a C program could understand. Data Storage Overview Python’s data storage features are easy to use, but before you say, “Hey, store this stuff” (it really is that easy), you should put some thought into how you might use the data down the road. The issues listed below are merely some things you should keep in mind; don’t worry too much yet about how actually to deal with them. Text versus binary If you’re storing data to file, you have to choose whether to store it in text or binary mode. A configuration file, for example, is in text mode because humans have to be able to read it and edit it with a text editor. It’s often easier to debug your program if the output is stored in some human-readable format, and you can easily pass such a file around and use it on different platforms. Of course, storing it in a human-readable format means you handle the details of parsing it back in if you need to load it. A binary mode representation of data often takes up less space, and can be processed faster if it is stored in fixed-size blocks or records. Data storage overview Loading and saving objects Example: moving objects across a network Using database-like storage Converting to and from C structures Converting data to standard formats Compressing data ✦ ✦ ✦ ✦ 4807-7 ch12.F 196 5/24/01 8:59 AM Page 196 Part II ✦ Files, Data Storage, and Operating System Services Compression If the size of an object is an issue, compression may be something you want to consider. In return for some additional processing power, compression often significantly shrinks the size of your data, which could really help if you have a lot of data or are transferring it over slow network connections. Byte order (“Endianness”) The way a processor stores multibyte numbers in memory is either big-endian or little-endian: >>> import sys >>> print ‘“...%s-endian”, Gulliver said.’ % sys.byteorder “...little-endian”, Gulliver said. # On my Intel box Most Python programs wouldn’t care about such a low-level detail, but if your data has the potential to end up on another platform (by copying a data file, for example), the program on the other end has to know the byte order of the data in order to understand the data. Object state Before you store an object, you need to remember that some objects have state “outside” the Python interpreter. If you tried to save an open socket connection to disk, you certainly couldn’t expect the connection to be open once you reload the socket. Destination You should keep in mind the destination of your data, because knowing that may let you take advantage of features particular to that medium. Is it going to a file on disk? How about a network connection or a database? On the receiving end One last thing to consider is what the receiving end of your data will be (who will read it in the future?). If you are saving a file that your same program will read later, you can use just about whatever storage format you like. If a C program is on the other end, maybe you need to send it data in the form of a C structure. Or maybe you don’t even know who will read the data, so an industry standard format such as XDR or XML may be the answer. 4807-7 ch12.F 5/24/01 8:59 AM Page 197 Chapter 12 ✦ Storing Data and Objects Loading and Saving Objects To save an object to disk, you convert it to a string of bytes that the program can later read back in to recreate the original object. If you’re coming from a Java or C++ background, then you recognize this process as marshaling or serialization, but Python refers to making preserves out of your objects as pickling. Pickling with pickle The pickle module converts most Python objects to and from a byte representation: >>> import pickle >>> stuff = [5,3.5,’Alfred’] >>> pstuff = pickle.dumps(stuff) >>> pstuff “(lp0\012I5\012aF3.5\012aS’Alfred’\012p1\012a.” >>> pickle.loads(pstuff) [5, 3.5, ‘Alfred’] The pstuff variable in the above example is a string of bytes, so it’s easy to send it to another computer via a network connection or write it out to a file. The pickle.dumps(object[, bin]) function returns the serialized form of an object, and pickle.dump(object, file[, bin]) sends the serialized form to an open filelike object. If the optional bin parameter is 0 (the default), the object is pickled in a text form. A value of 1 generates a slightly more compact but less readable binary form. Either form is platform-independent. The pickle.loads(str) function unpickles an object, converting the given string to its original object form. pickle.load(file) reads a pickled object from the given filelike object and returns the original, unpickled object. The load and dump methods are really shorthand ways of instantiating the Pickle and Unpickler classes: >>> s = StringIO.StringIO() # Create a temp filelike object. >>> p = pickle.Pickler(s,1) # 1 = binary >>> p.dump([1,2,3]) >>> p.dump(‘Hello!’) >>> s.getvalue() # See the pickled form. ‘]q\000(K\001K\002K\003e.U\006Hello!q\001.’ >>> s.seek(0) # Reset the “file.” >>> u = pickle.Unpickler(s) >>> u.load() [1, 2, 3] >>> u.load() ‘Hello!’ 197 4807-7 ch12.F 198 5/24/01 8:59 AM Page 198 Part II ✦ Files, Data Storage, and Operating System Services Using the Pickler and Unpickler classes is convenient if you need to pickle many objects, or if you need to pass the picklers around to other functions. You can also subclass them to create a custom pickler. The cPickle module is a C version of the pickle module, making it up to several orders of magnitude faster than the pure Python pickle module. Anytime you need to do lots of pickling, use cPickle. Objects pickled by cPickle are compatible with those pickled by pickle, and vice versa. The only drawback to the cPickle module is that you can’t subclass Pickler and Unpickler. >>> import cPickle,pickle >>> s = cPickle.dumps({‘one’:1,’two’:2}) >>> pickle.loads(s) {‘one’: 1, ‘two’: 2} As Python evolves, future versions could change the format of pickled objects. To prevent disasters, each version of the format has a version number, and pickle has a list of other versions (in addition to the current one) that it knows how to read: >>> pickle.format_version ‘1.3’ >>> pickle.compatible_formats [‘1.0’, ‘1.1’, ‘1.2’] # It can read some pretty old objects. If you try to unpickle an unsupported version, pickle raises an exception. What can I pickle? You can pickle numbers, strings, None, and containers (tuples, lists, and dictionaries) that contain “picklable” objects. When you pickle built-in functions, your own functions, or class definitions, pickle stores its name along with the module name in which it was defined, but not its implementation. In order to unpickle such an object, pickle first imports its module, so you must define the function or class at the top level of that module. To save an instance object, pickle calls its __getstate__ method, which should return whatever information you need to capture the state of the object. When Python loads the object, pickle instantiates a new object and calls its __setstate__ method, passing it the unpickled version of its state: >>> class Point: ... def __init__(self,x,y): ... self.x = x; self.y = y ... def __str__(self): ... return ‘(%d,%d)’ % (self.x,self.y) ... def __getstate__(self): ... print ‘Get state called!’ ... return (self.x,self.y) ... def __setstate__(self,state): ... print ‘Set state called!’ 4807-7 ch12.F 5/24/01 8:59 AM Page 199 Chapter 12 ✦ Storing Data and Objects ... self.x,self.y = state ... >>> p = Point(10,20) >>> z = pickle.dumps(p) Get state called! >>> newp = pickle.loads(z) Set state called! >>> print newp (10,20) If an object doesn’t have a __getstate__ member, pickle saves the contents of its __dict__ member. When unpickling an object, the load function doesn’t normally call the object’s constructor (__init__). If you really want load to call the constructor, implement a __getinitargs__ method. As it saves the object , pickle calls __getinitargs__ for a tuple of arguments that it should pass to __init__ when the object is later loaded. You can add pickling support for data types in C extension modules using the copy_reg module. To add support, you register a reduction function and a constructor for the given type by calling copy_reg.pickle(type, reduction_func[, constructor_ob]). For example, imagine you’re creating a C extension module that determines the right stocks to trade on the stock market, and that the module defines a new data type called StockType (representing a particular security). Your constructor object (such as a function) returns a new StockType object and takes as arguments whatever data needed to create such an object. Your reduction function takes a StockType object and returns a two-tuple containing a constructor object for creating a new StockType object (most likely the same constructor function mentioned above). The reduction function also takes a tuple containing arguments to pass to that constructor. After registering your functions for the new type, any serialized StockType objects can use them. CrossReference See Chapter 29 for information on writing your own extension modules. Other pickling issues Because pickling a class doesn’t store the class implementation, you can usually change the class definition without breaking your pickled data (you can still unpickle instance objects that were saved previously). Multiple references to a particular object also reference a single object once you unpickle it. In the following example, a list has two members that are both references to another list. After pickling and unpickling it, the two members still refer to a single object: >>> >>> >>> 1 >>> z = [1,2,3] y = [z,z] y[0] is y[1] # Two references to the same object s = pickle.dumps(y) 199 4807-7 ch12.F 200 5/24/01 8:59 AM Page 200 Part II ✦ Files, Data Storage, and Operating System Services >>> x = pickle.loads(s) >>> x [[1, 2, 3], [1, 2, 3]] >>> x[0] is x[1] # Both members still reference one object. 1 Of course, if you pickle an object, modify it, and pickle it again, pickle saves only the first version of the object. Caution If, while pickling to a filelike object, an error occurs (for example, you try to serialize a module), pickle raises the PicklingError exception, but it may have already written bytes to the file. The contents of the file will be in an unknown state and not too trustworthy. The marshal module Under the covers, the pickle module calls the marshal module to do some of its work, but most programs should not use marshal at all. The one advantage of marshal is that, unlike pickle, it can handle code objects (the implementation itself): >>> ... >>> 12 >>> >>> >>> ... >>> >>> 30 CrossReference def adder(a,b): return a+b adder(10,2) import marshal s = marshal.dumps(adder.func_code) def newadder(): pass newadder.func_code = marshal.loads(s) newadder(20,10) Chapter 33 shows you how to access code objects and other attributes of Python objects such as functions. Example: Moving Objects Across a Network The example in this section puts all this pickling stuff to work for you. Listing 12-1 is the swap module that creates a background thread that sends objects between two Python interpreters running in interactive mode. Although it works on a single computer, you can also run it between two separate computers if you change the IP address it uses. 4807-7 ch12.F 5/24/01 8:59 AM Page 201 Chapter 12 ✦ Storing Data and Objects CrossReference Consider this example as a sneak preview. Chapter 15 covers networking and Chapter 26 covers threads. Here is some sample output from the program in Listing 12-1 (I opened two separate MS-DOS Windows on the same computer). After the sample output is a short explanation of how the program works. The first half shows what is happening in the first window, and the second in the other window, although both programs are running at the same time and interacting: C:\temp>python -i -c “import swap” Listen thread started. Use swap.send(obj) to send an object Look in swap.obj to see a received object >>> swap.send([‘game’,’of’,’the’,’year’]) # See Obj1 below. Received new object (5, 10) # Obj2 from below >>> swap.obj (5, 10) >>> swap.obj[1] # Yep, it’s a real Python object! 10 C:\temp>python -i -c “import swap” Listen thread started. Use swap.send(obj) to send an object Look in swap.obj to see a received object Received new object [‘game’, ‘of’, ‘the’, ‘year’] # Obj1 from above >>> swap.obj[2] # Poke around a little ‘the’ >>> swap.send((5,10)) # See Obj2 above Once both interpreters are up and running, they connect to each other via a network socket. Anytime you call swap.send(obj) in one interpreter, swap sends your object to the other interpreter, which stores it in swap.obj. Either side can send any picklable object to the other. Notice that I started the Python interpreter using the “-c” argument (telling it to execute the command import swap) and the “-i” argument (telling it to keep the interpreter running after it executes its command). This feature lets you start with the swap module already loaded and running. 201 4807-7 ch12.F 202 5/24/01 8:59 AM Page 202 Part II ✦ Files, Data Storage, and Operating System Services Listing 12-1: swap.py – Swap Objects Between Python Interpreters from socket import * import cPickle,threading ADDR = ‘127.0.0.1’ # ‘127.0.0.1’ = localhost PORT = 50000 bConnected = 0 def send(obj): “Sends an object to a remote listener” if bConnected: conn.send(cPickle.dumps(obj,1)) else: print ‘Not connected!’ def listenThread(): “Receives objects from remote side” global bServer, conn, obj, bConnected while 1: # Try to be the server. s = socket(AF_INET,SOCK_STREAM) try: s.bind((ADDR,PORT)) s.listen(1) bServer = 1 conn = s.accept()[0] except Exception, e: # Probably already in use, so I’m the client. bServer = 0 conn = socket(AF_INET,SOCK_STREAM) conn.connect((ADDR,PORT)) # Now just accept objects forever. bConnected = 1 while 1: o = conn.recv(8192) if not o: break; obj = cPickle.loads(o) print ‘Received new object’ print obj bConnected = 0 # Start up listen thread. threading.Thread(target=listenThread).start() print ‘Listen thread started.’ print ‘Use swap.send(obj) to send an object’ print ‘Look in swap.obj to see a received object’ 4807-7 ch12.F 5/24/01 8:59 AM Page 203 Chapter 12 ✦ Storing Data and Objects For the sake of simplicity, the example leaves out a lot of error checking that you’d want if you were to use this for something important. Note This module has two functions: send and listenThread. send takes any object you pass in, pickles it, and sends it out through the socket that is connected to the other Python interpreter. The listenThread function loops forever, waiting for objects to come in over the socket. When the function first starts, it tries to bind to the given IP address and port so it can act as the server side of the connection. If this attempt fails, it assumes that the bind failed because the other interpreter is already acting as the server, so listenThread tries to connect (thus becoming the client side of the connection). Once connected, listenThread receives each object, unpickles it, prints it out and also saves it to the global variable obj so that you can then fiddle with it in your interpreter. At the module level, a call to threading.Thread().start() starts the listening thread. By placing the call there, the background thread starts up automatically as soon as you import the module. After you’ve played around with this a little, sit back and relish the fact that all this power required a measly 50 lines of Python code! Using Database-Like Storage The shelve module enables you to save Python objects into persistent, databaselike storage, similar to the dbm module. CrossReference See Chapter 14 for information on dbm and other Python database modules. The shelve.open(file[, mode]) function opens and returns a shelve object. The mode parameter (which is the same as the mode parameter to dbm.open) defaults to ‘c’, which means that the function opens the database for reading and writing, and creates it if it doesn’t already exist. Use the close() method of the shelve object when you are finished using it. You access the data as if the database were a dictionary: >>> >>> >>> >>> >>> [5, >>> >>> 0 import shelve db = shelve.open(‘objdb’) # Don’t use a file extension! db[‘secretCombination’] = [5,23,17] db[‘account’] = 5671012 db[‘secretCombination’] 23, 17] del db[‘account’] db.has_key(‘account’) 203 4807-7 ch12.F 204 5/24/01 8:59 AM Page 204 Part II ✦ Files, Data Storage, and Operating System Services >>> db.keys() [‘secretCombination’] >>> db.close() The shelve module uses pickle, so you can store any objects that pickle can store. shelve has the same limitations as dbm. Among other things, you should not use it to store large Python objects. Converting to and from C Structures Although pickle makes converting Python objects to a byte stream easy, really only Python programs can convert them back to objects. The struct module, however, lets you create a string of bytes equivalent to a C structure, so you could read and write binary files generated by a non-Python program or send binary network messages to something besides a Python interpreter. To use struct, you call struct.pack(format, v1, v2, ...) with a format string describing the layout of the data followed by the data itself. Construct the format string using format characters listed in Table 12-1. Table 12-1 struct Format Characters Character C type Python type c Char string of length 1 s char string p (Pascal string) string i Int integer I Unsigned int integer or long* b Signed char integer B unsigned char integer h Short integer H unsigned short integer l Long integer L unsigned long long f Float float d Double float x (pad byte) - P void * integer or long* * The type Python uses is based on whether a pointer for this platform is 32 or 64 bits. 4807-7 ch12.F 5/24/01 8:59 AM Page 205 Chapter 12 ✦ Storing Data and Objects For example, to create the equivalent of this C struct: struct { int a; int b; char c; }; with the values 10, 20, and ‘Z,’ use: >>> import struct >>> z = struct.pack(‘iic’,10,20,’Z’) >>> z ‘\012\000\000\000\024\000\000\000Z’ Given a string of bytes in a particular format, you can convert them to Python objects by calling struct.unpack(format, data). It returns a tuple of the reconstructed data: >>> struct.unpack(‘iic’,z) (10, 20, ‘Z’) The format string you pass to unpack must account for all the data in the string you pass it, or struct raises an exception. Use the struct.calcsize(format) function to figure out how many bytes would be taken up by the given format string: >>> struct.calcsize(‘iic’) 9 >>> len(z) # The earlier example verifies this. 9 As a shortcut, you can put a number in front of any format character to repeat that data type that many times: >>> struct.pack(‘3f’,1.2,3.4,5.6) # ‘3f’ is the same as ‘fff’ ‘\232\231\231?\232\231Y@33\263@’ For clarity, you can put whitespace between format characters in your format string (but not between the format character and a repeater number): >>> struct.pack(‘2i h 3c’,5,6,7,’a’,’b’,’c’) ‘\005\000\000\000\006\000\000\000\007\000abc’ The repeater number works a little differently with the ‘s’ (string) format character. The repeater tells the length of the string (5s means a 5 character string). 0s means an empty string, but 0c means zero characters. The ‘I’ format character unpacks the given number to a Python long integer if the C int and long are the same size. If the C int is smaller than the C long, ‘I’ converts the number to a Python integer. 205 4807-7 ch12.F 206 5/24/01 8:59 AM Page 206 Part II ✦ Files, Data Storage, and Operating System Services The ‘p’ format character is for a Pascal string. Pascal uses the first byte to store the length of the string (so Pascal first truncates strings longer than the maximum length of 255) and then the characters in the string follow. If you supply a repeater number with this format character, it represents the total number of bytes in the string including the length byte. If the string is less than the specified number of bytes, pack adds empty padding characters to bring it up to snuff. By default, struct stores numbers using the native format for byte order and structure member alignment (whatever your current platform’s C compiler would use). You can override this behavior by starting your format string with one of the modifiers listed in Table 12-2. For example, you can force struct to use network order, a standard byte ordering for network messages: >>> struct.pack(‘ic’,65535,’D’) # Native is little-endian. ‘\377\377\000\000D’ >>> struct.pack(‘!ic’,65535,’D’) # Force network order. ‘\000\000\377\377D’ Table 12-2 Order, Alignment, and Size Modifiers Modifier Byte order Alignment Size < Little-endian None Standard > or ! Big-endian (Network) None Standard = Native None Standard @ Native Native Native If you don’t choose a modifier from Table 12-2, struct uses native byte ordering, alignment, and size. When you use a modifier whose size is “standard,” a C short takes up 2 bytes, an int, long, or float uses 4, and a double uses 8. If you need to have alignment but aren’t using the ‘@’ (native alignment) modifier, you can insert pad bytes using the ‘x’ format character from Table 12-1. If you need to force the end of a structure to be aligned according to the alignment rules for a particular type, you can end your format string with the format code for that type with a count of 0. The following example shows how to force a single-character structure to end on an integer boundary: >>> struct.pack(‘c’,’A’) ‘A’ >>> struct.pack(‘c0i’,’A’) ‘A\000\000\000’ The ‘P’ (pointer) format character is available with native alignment only. 4807-7 ch12.F 5/24/01 8:59 AM Page 207 Chapter 12 ✦ Storing Data and Objects The struct module is very useful for reading and writing binary files. For example, if you read the first 36 bytes of a Windows WAV file, you can use struct to extract some information about the file. The header of a WAV file starts with: ‘RIFF’ (4 bytes) little-endian length field (4 bytes) ‘WAVE’ (4 bytes) ‘fmt ‘ (4 bytes) format subchunk length (4 bytes) format specifier (2 bytes) number of channels (2 bytes) sample rate in Hertz (4 bytes) bytes per second (4 bytes) bytes per sample (2 bytes) bits per channel (2 bytes) One way to represent this header would be with the format string ‘<4s i 4s 4s ihhiihh’ The following code extracts this information from a WAV file: >>> s = open(‘c:\\winnt\\media\\ringin.wav’,’rb’).read(36) >>> struct.unpack(‘<4si4s4sihhiihh’,s) (‘RIFF’, 10018, ‘WAVE’, ‘fmt ‘, 16, 1, 1, 11025, 11025, 1, 8) Extending that example, the following function rates the sound quality of a given WAV file: >>> def rateWAV(filename): ... format = ‘<4si4s4sihhiihh’ ... fsize = struct.calcsize(format) ... data = open(filename,’rb’).read(fsize) ... data = struct.unpack(format,data) ... if data[0] != ‘RIFF’ or data[2] != ‘WAVE’: ... print ‘Not a WAV file!’ ... rate = data[7] ... if rate == 11025: ... print ‘Telephone quality!’ ... elif rate == 22050: ... print ‘Radio quality!’ ... elif rate == 44100: ... print ‘Oooh, CD quality!’ ... else: ... print ‘Rate is %d Hz’ % rate >>> rateWAV(r’c:\winnt\media\notify.wav’) Radio quality! >>> rateWAV(‘online.wav’) Oooh, CD quality! 207 4807-7 ch12.F 208 5/24/01 8:59 AM Page 208 Part II ✦ Files, Data Storage, and Operating System Services Converting Data to Standard Formats Now that you have the struct module under your belt, you can build on that knowledge to read and write just about any file format. If your data needs to be readable by your own programs only, then you can create your own convention for storing data. In other cases, however, you may find it useful to convert your data to an industry-wide standard. Sun’s XDR format The XDR (eXternal Data Representation) format is a standard data format created by Sun Microsystems. RFC 1832 defines the format, and it’s most common use is in NFS (Network File System). Storing data in a standard format like XDR makes sharing files easier for different hardware platforms and operating systems. The xdrlib module implements a subset of the XDR format, leaving out some of the less-used data types. To convert data to XDR, you create an instance of the xdrlib.Packer class, and to convert from XDR, you create an instance of xdrlib.Unpacker. Packer objects The Packer constructor takes no arguments: >>> import xdrlib >>> p = xdrlib.Packer() Once you have a Packer object you can use any of its pack_<type> methods to pack basic data types: >>> >>> >>> >>> >>> >>> >>> >>> >>> p.pack_float(3.5) p.pack_double(10.5) p.pack_int(-15) p.pack_uint(15) p.pack_hyper(100) p.pack_uhyper(200) p.pack_enum(3) p.pack_bool(1) p.pack_bool(“Hi”) # 32-bit floating point number # 64-bit floating point number # Signed 32-bit integer # Unsigned 32-bit integer # Signed 64-bit integer # Unsigned 64-bit integer # Enumerated type # Booleans are 1 or 0 # Value is true, so stores a 1 The pack_fstring(count, str) method packs a fixed-length string count characters long. The function does not store the size of the string, so to unpack it you have to know how long it is beforehand. Better yet, use pack_string(str), which lets you pack a variable-length string: >>> p.pack_string(‘Lovely’) >>> p.pack_fstring(3,’day’) 4807-7 ch12.F 5/24/01 8:59 AM Page 209 Chapter 12 ✦ Storing Data and Objects The pack_string function calls pack_uint with the size of the string and then pack_fstring with the string itself. To more fully follow the XDR specification, a Packer object also has pack_bytes and pack_opaque methods, but they are really just calls to pack_string. Likewise, a call to pack_fopaque is really just a call to pack_fstring. The pack_farray(count, list, packFunc) function packs a fixed-length array (count items long) of homogenous data. Unfortunately, pack_farray requires that you pass in the count as well as the list itself, but it won’t let you use a count that is different from the length of the list (go figure). As with pack_fstring, the function does not store the length of the array with the data, so you have to know the length when you unpack it. Or you can call pack_array(list, packFunc) to pack the size and then the list itself. The packFunc tells Packer which method to use to pack each item. For example, if each item in the list is an integer: >>> p.pack_array([1,2,3,4],p.pack_int) The pack_list(list,packFunc) method also packs an array of homogenous data, but it works with sequence objects whose size might not be known ahead of time. For example, you could create a class that defines its own __getitem__ method: >>> ... ... ... ... >>> >>> ... 0 1 2 3 4 >>> class MySeq: def __getitem__(self,i): if i < 5: return i raise IndexError m = MySeq() for i in m: print i p.pack_list(m,p.pack_int) The get_buffer() method returns a string representing the packed form of all the data you’ve packed. reset() empties the buffer: >>> p.reset() >>> p.pack_int(10) >>> p.get_buffer() ‘\000\000\000\012’ >>> p.reset() >>> p.get_buffer() ‘’ 209 4807-7 ch12.F 210 5/24/01 8:59 AM Page 210 Part II ✦ Files, Data Storage, and Operating System Services Unpacker objects Not surprisingly, an Unpacker object has methods that closely mirror those of a Packer object. When you construct an Unpacker, you pass in a string of bytes for it to decode, and then begin calling its unpack_<type> methods (each pack_ method has a corresponding unpack_ method): >>> >>> >>> >>> >>> import xdrlib p = xdrlib.Packer() p.pack_float(2.0) p.pack_fstring(4,’Dave’) p.pack_string(‘/export/home’) >>> u = xdrlib.Unpacker(p.get_buffer()) >>> u.unpack_float() 2.0 >>> u.unpack_fstring(4) ‘Dave’ >>> u.unpack_string() ‘/export/home’ >>> u.done() The done() method tells the Unpacker that you are finished decoding data. If Unpacker still has data left in its internal buffer, it raises an Error exception to inform you that the internal buffer has leftover data. Calling the reset(str) method replaces the current buffer with the data in str. At any time, you can call the get_buffer() method to retrieve the string representation of the data stream. You can use the get_position() and set_position(pos) methods to track and reposition where in the buffer the Unpacker decodes from next. To be safe, set a position to 0 or to a value returned from get_position. Other formats Of course, you might use many other data formats. XML is gaining popularity as a data storage markup language; see Chapter 18 for more information. For any given file format, a quick search on a Web search engine locates many documents describing the details of that format (for example, try searching for “WAV spec”). Once you have that information, creating format strings that struct can understand is usually a straightforward process. Compressing Data This final section covers the use of the zlib, a module wrapping the free zlib compression library. The gzip and zipfile modules use zlib to manipulate GZIP and ZIP files, respectively. 4807-7 ch12.F 5/24/01 8:59 AM Page 211 Chapter 12 ✦ Storing Data and Objects zlib You can use the zlib module to compress any sort of data; if you are transferring large messages over a network, it may be worthwhile to compress them first, for example. The most straightforward use of zlib is through the compress(string[, level]) and decompress(string[, wbits[, bufsize]]) functions. The level used during compression is from 1 (fastest) to 9 (best compression), defaulting to 6. During decompression, the wbits argument controls the size of the history buffer, and should have a value between 8 and 15 (the default). A higher value consumes more memory but increases the chances of better compression. The bufsize argument determines the initial size of the buffer used to hold decompressed data. The library modifies this size as needed, so you never really have to change it from its default of 16384. Both compress and decompress take a string of bytes and return the compressed or decompressed equivalent: >>> import zlib >>> longString = 100 * ‘That zlib module sure is fun!’ >>> compressed = zlib.compress(longString) >>> len(longString); len(compressed) 2900 62 @code:# Yay, zlib! >>> zlib.decompress(compressed)[:40] ‘That zlib module sure is fun!That zlib m’ Tip To learn more about zlib’s features, visit the zlib Web site at http:// www.info-zip.org/pub/infozip/zlib/. The zlib module has two functions for computing the checksum of a string (useful in detecting changes and errors in data or as a way to warm your CPU), crc32(string[, value]) and adler32(string[, value]). If present, the optional value argument is the starting value of the checksum, so you can calculate the checksum of several pieces of input. The following example shows you how to use a checksum to detect data corruption: >>> data = ‘My dog has no fleas!’ >>> zlib.adler32(data) 1193871046 >>> data = data[:5]+’z’+data[6:] >>> data ‘My doz has no fleas!’ # A solar flare corrupts your data... >>> zlib.adler32(data) 1212548825 # ...resulting in a different checksum. The value returned from crc32 is more reliable than that returned from adler32, but it also requires much more computation. (More reliable means that the function is less likely to return the same checksum if the data changes at all.) Don’t forget to dazzle your friends by informing them that Mark Adler wrote the decompression portion of zlib. 211 4807-7 ch12.F 212 5/24/01 8:59 AM Page 212 Part II ✦ Files, Data Storage, and Operating System Services If you have more data than you can comfortably fit in memory, zlib lets you create compression and decompression objects. Create a compression object by calling compressobj([level]). Once you have your object, you can repeatedly call its compress(string) method. Each call returns another portion of the compressed version of the data, although some is saved for later processing. Calling the compression object’s flush([mode]) method finishes the compression and returns the remaining compressed data: >>> >>> >>> >>> >>> 115 c = zlib.compressobj(9) out = c.compress(1000 * ‘I will not throw knives’) out += c.compress(200 * ‘or chairs’) out += c.flush() len(out) # out holds the entire compressed stream. If you call flush with a mode of Z_FULL_FLUSH or Z_SYNCH_FLUSH, all the currently buffered compressed data is returned, but you can later compress more data with the same object. Without those mode values, the compression object assumes you’re finished and doesn’t allow any additional compression. You create a decompression object by calling zlib’s decompressobj([wbits]) function. A decompression object lets you decompress a stream of data one piece at a time (for example, you could decompress a file by repeatedly reading a chunk of data, decompressing that chunk, and writing the result to an output file). Call the decompress(string) method of your decompression object to decompress the next chunk of data. decompress returns the largest amount of decompressed data that it can, although it may need to buffer some until you supply more data to decompress. The following code decompresses the output from the previous example 20 bytes at a time: >>> d = zlib.decompressobj() # Create a decompressor. >>> msg = ‘’ >>> while out: ... msg += d.decompress(out[:20]) # Decompress some. ... out = out[20:] >>> msg += d.flush() # Let it know that we’re all done. >>> len(msg) 24800 >>> 1000 * len(‘I will not throw knives’) +\ ... 200 * len(‘or chairs’) 24800 # Length matches that of the original message. >>> msg[:50] # Looks like the message itself matches too. ‘I will not throw knivesI will not throw knivesI wi’ Call the decompression object’s flush() method when you’re done giving it more data (after this you can’t call decompress any more with that object). 4807-7 ch12.F 5/24/01 8:59 AM Page 213 Chapter 12 ✦ Storing Data and Objects Decompression objects also have an unused_data member that holds any leftover compressed data from the last call to decompress. A nonempty unused_data string means that the decompression object is still waiting on additional data to finish decompressing this particular piece of data. gzip The gzip module lets you read and write .gz (GNU gzip) files as if they were ordinary files (that is, your program can pretty much ignore the fact that compression/ decompression is taking place). Note The GNU gzip and gunzip programs support additional formats (for example, compress and pack), but the gzip Python module does not. The gzip.GzipFile([filename[, mode[, compresslevel[, fileobj]]]]) function constructs a new GzipFile object. You must supply either the filename or the fileobj argument, although the file object can be anything that looks like a file such as a cStringIO object. The compresslevel parameter has the same values as for zlib module earlier in this section. If you don’t supply a mode, then gzip tries to use the mode of fileobj. If that’s not possible, the mode defaults to ‘rb’ (open for reading). A GzipFile can’t be open for both reading and writing, so you should use a mode of ‘rb’, ‘wb’, or ‘ab’. When you call the close() method of a GzipFile, the file object (if you supplied one) remains open. To further the illusion of normal file I/O, you can call the open(filename[, mode[, level]]) function in the gzip module. The filename argument is required, so the call looks very similar to Python’s built-in open function: >>> f = gzip.open(‘small.gz’,’wb’) >>> f.write(‘’’Old woman! ... Man! ... Old Man, sorry. What knight lives in that castle over there? ... I’m thirty-seven. ... What? ... I’m thirty-seven -- I’m not old! ... Well, I can’t just call you ‘Man’. ... Well, you could say ‘Dennis’. >>> f.close() >>> f = gzip.open(‘small.gz’) >>> print f.read() Old woman! Man! Old Man, sorry. What knight lives in that castle over there? I’m thirty-seven. 213 4807-7 ch12.F 214 5/24/01 8:59 AM Page 214 Part II ✦ Files, Data Storage, and Operating System Services What? I’m thirty-seven -- I’m not old! Well, I can’t just call you ‘Man’. Well, you could say ‘Dennis’. zipfile The zipfile module lets you read, write, and get information about files stored in the common ZIP file format. Note The zipfile module does not currently support ZIP files with appended comments or files that span multiple disks. The ipfile.is_zipfile(filename) function returns true if the given file name appears to be a valid zip file. The zipfile module defines the ZipFile, ZipInfo, and PyZipFile classes. The ZipFile class This class is the primary one used to read and write a ZIP file. You create a ZipFile instance object by calling the ZipFile(filename[, mode[, compression]]) constructor: >>> import zipfile >>> z = zipfile.ZipFile(‘room.zip’) >>> z.printdir() # Print formatted summary of the archive File Name Modified Size world 2000-09-05 09:25:14 10919 cryst.cfg 1999-03-07 06:14:34 27 The mode is ‘r’ (read, the default), ‘w’ (write), or ‘a’ (append). If you append to a ZIP file, Python adds new files to it. If you append to a non-ZIP file, however, Python adds a ZIP archive to the end of the file. Not all ZIP readers can understand this format. The compression argument is either ZIP_STORED (no compressed) or ZIP_DEFLATED (use compression). The namelist() method of your ZipFile object returns the list of files the ZIP contains. You can get a ZipInfo object (described in the next section) for any file via the getinfo(name) method, or you can get a list of ZipInfos for the entire archive with the infolist() method: >>> z.namelist() [‘world’, ‘cryst.cfg’] # The ZIP contains two files. >>> z.getinfo(‘world’) # Get some info for file named ‘world.’ <zipfile.ZipInfo instance at 010FD14C> >>> z.getinfo(‘world’).file_size 10919 4807-7 ch12.F 5/24/01 8:59 AM Page 215 Chapter 12 ✦ Storing Data and Objects >>> z.infolist() [<zipfile.ZipInfo instance at 010FD14C>, <zipfile.ZipInfo instance at 010E116C>] If you open the ZIP in read or append mode, read(name) decompresses the specified file and returns its contents: >>> print z.read(‘cryst.cfg’) [World] MIXLIGHTS=true_rgb The testzip() method returns the name of the first corrupt file or None if all files are okay: >>> z.testzip() ‘world’ # The file called ‘world’ is corrupt. For ZIPs opened in write or append mode, the write(zipInfo, bytes) method adds a new file to the archive. bytes contains the content of the file, and zipInfo is a ZipInfo object (see the next section) with the file’s information. You don’t have to fill in every attribute of ZipInfo, but at least fill in the file name and compression type. The write(filename[, arcname[, compress_type]]) function adds the contents of the file filename to the archive. If you supply a value for arcname, that is the name of the file stored in the archive. If you supply a value for compress_type, it overrides whatever compression type you used when you created the ZipFile. After making any changes to a ZIP file, calling the close() method is essential to guaranteeing the integrity of the archive. Tip A ZipFile object has a debug attribute that you can use to change the level of debug output messages. Most output comes with a value of 3, the least (no output) is with a value of 0, the default. The ZipInfo class Information about each member of a ZIP archive is represented by a ZipInfo object. You can use the ZipInfo([filename[, date_time]]) constructor to create one; getinfo() and infolist() also return ZipInfo objects. The filename should be the full path of the file and date_time is a six-tuple containing the last modification timestamp (see the date_time attribute in Table 12-3). Each ZipInfo instance object has many attributes; the most useful are listed in Table 12-3. 215 4807-7 ch12.F 216 5/24/01 8:59 AM Page 216 Part II ✦ Files, Data Storage, and Operating System Services Table 12-3 ZipInfo Instance Attributes Name Description filename Name of the archived file compress_size Size of the compressed file file_size Size of the original file date_time Last modification date and time, a six-tuple consisting of year, month (1–12), day (1–31), hour (0–23), minute (0–59), second (0–59) compress_type Type of compression (stored or deflated) CRC The CRC32 of the original file comment Comment for this entry extract_version Minimum software version needed to extract the archive header_offset Byte offset to the file’s header file_offset Byte offset to the file’s data The PyZipFile class The PyZipFile class is a utility class for creating ZIP files that contain Python modules and packages. PyZipFile is a subclass of ZipFile, so its constructor and methods are the same as for ZipFile. The only method that PyZipFile adds is writepy(pathname), which searches for *.py files and adds their corresponding bytecode files to the ZIP file. For each Python module (for example, file.py), writepy archives file.pyo if it exists. If not, it adds file.pyc if it exists. If that doesn’t exist either, writepy compiles the module to create file.pyc and adds it to the archive. If pathname is the name of a package directory (a directory containing the __init__.py file), writepy searches that directory and all package subdirectories for all *.py files. If pathname is the name of an ordinary directory, it searches for *.py files in that directory only. Finally, if pathname is just a normal Python module (for example, file.py), writepy adds its bytecode to the ZIP file. CrossReference Refer to Chapter 6 for more information on Python packages. 4807-7 ch12.F 5/24/01 8:59 AM Page 217 Chapter 12 ✦ Storing Data and Objects Summary Python makes a breeze of serializing or marshaling objects to disk or over a network, and its support for compression and data conversion only makes life easier. In this chapter you: ✦ Serialized objects. ✦ Transported objects across a network connection. ✦ Converted objects to formats readable by C programs. ✦ Stored objects in the standard XDR format. ✦ Compressed data to save space. In the next chapter you’ll learn to track how long parts of your program take to run, retrieve the date and time, and print the date and time in custom formats. ✦ ✦ ✦ 217 4807-7 ch12.F 5/24/01 8:59 AM Page 218 4807-7 ch13.F 5/24/01 8:59 AM Page 219 13 13 CHAPTER Accessing Date and Time ✦ ✦ ✦ ✦ In This Chapter D ates can be written in many ways. Converting between date formats is a common chore for computers. Date arithmetic — like finding the number of days between June 10 and December 13 — is another common task. Python’s time and calendar modules help track dates and times. They even handle icky details like daylight savings time and leap years. Telling Time in Python Telling time in Python Converting between time formats Parsing and printing dates and times Accessing the calendar Time is usually represented as either a number or a tuple. The time module provides functions for working with times, and for converting between representations. Using time zones Ticks ✦ You can represent a point in time as a number of “ticks” — the number of seconds that have elapsed since the epoch. The epoch is an arbitrarily chosen “beginning of time.” For UNIX and Windows systems, the epoch is 12:00am, 1/1/1970. For example, on my computer, my next birthday is 983347200 in ticks (which translates into February 28, 2001). The function time.time returns the current system time in ticks. For example, here is the number of days from now until my birthday: >>> 983347200 - time.time() 7186162.7339999676 Note that Python uses a floating-point value for ticks. Because time precision varies by operating system, time.time is always an integer on some systems. Allowing two-digit years ✦ ✦ ✦ 4807-7 ch13.F 220 5/24/01 8:59 AM Page 220 Part II ✦ Files, Data Storage, and Operating System Services Date arithmetic is easy to do with ticks. However, dates before the epoch cannot be represented in this form. Dates in the far future also cannot be represented this way — the cutoff point is sometime in 2038 for UNIX and Windows. Third-party modules such as mxDateTime provide date/time classes that function outside the range 1970–2038. Note TimeTuple Many of Python’s time functions handle time as a tuple of 9 numbers, as shown in Table 13-1: Table 13-1 Time Functions Index Field Values 0 4-digit year 1993 1 Month 1–12 2 Day 1–31 3 Hour 0–23 (0 is 12 a.m.) 4 Minute 0–59 5 Second 0–61 (60 or 61 are leap-seconds) 6 Day of week 0–6 (0 is Monday) 7 Day of year 1–366 (Julian day) 8 Daylight savings -1,0,1 Note that the elements of the tuple proceed from broadest (year) to most granular (second). This means that one can do linear comparisons on TimeTuples: >>> TimeA = (1972, 5, 15, 12, 55, 32, 0, 136, 1) >>> TimeB = (1972, 5, 16, 7, 9, 10, 1, 137, 1) >>> TimeA<TimeB # TimeA is a day before TimeB. 1 Note that a TimeTuple does not include a time zone. To pinpoint an actual time, one needs a time zone as well as a TimeTuple. Stopwatch time The clock function acts as a stopwatch for timing Python code — you call clock before doing something, call it again afterwards, and take the difference between 4807-7 ch13.F 5/24/01 8:59 AM Page 221 Chapter 13 ✦ Accessing Date and Time numbers to get the elapsed seconds. The actual values returned by clock are system-dependent and generally don’t translate into a time-of-day. This code checks how quickly Python counts to one million: >>> def CountToOneMillion(): ... StartTime=time.clock() ... for X in xrange(0,1000000): pass ... EndTime=time.clock() ... print EndTime-StartTime ... >>> CountToOneMillion() # Elapsed time, in seconds 0.855862726726 Note The proper way to pause execution is with time.sleep(n), where n is a floating point number of seconds. In a Tkinter application, once can call the after method on the root object to make a function execute after n seconds. (See Chapter 19 for more on Tkinter.) Converting Between Time Formats The function localtime converts from ticks to a TimeTuple for the local time zone. For example, this code gets the current time: >>> time.localtime(time.time()) (2000, 12, 6, 20, 0, 9, 2, 341, 0) Reading the fields of the TimeTuple, I can see that it is the year 2000, December 6, at 20:00 (8 p.m.) and 9 seconds. The day of the week is 2 (Wednesday), it is the 341st day of the year, and local clocks are not currently on Daylight Savings Time. The function gmtime also converts from EpochSeconds to a TimeTuple. It returns the current TimeTuple for UTC (Universal Coordinated Time, formerly Greenwich Mean Time). This call to gmtime shows that it is 4 a.m. in England (a bad time to telephone): >>> time.gmtime(time.time()) (2000, 12, 7, 4, 4, 9, 3, 342, 0) The function mktime converts from a TimeTuple to EpochSeconds. It interprets the TimeTuple according to the local time zone. The function mktime is the inverse of localtime, and it is useful for doing date arithmetic. (The inverse function of gmtime is calendar.timegm.) This code finds the number of seconds between two points in time: >>> TimeA = (1972, 5, 15, 12, 55, 32, 0, 136, 1) >>> TimeB = (1972, 5, 16, 7, 9, 10, 1, 137, 1) >>> time.mktime(TimeB)-time.mktime(TimeA) 65618.0 >>> _ / (60*60) # How many hours is that? 18.227222222222224 221 4807-7 ch13.F 222 5/24/01 8:59 AM Page 222 Part II ✦ Files, Data Storage, and Operating System Services Parsing and Printing Dates and Times The asctime function takes a TimeTuple, and returns a human-readable timestamp. It is especially useful in log files: >>> Now=time.localtime(time.time()) # Now is a TimeTuple. >>> time.asctime(Now) ‘Sun Dec 10 10:09:41 2000’ >>> # In version 2.1, you can call asctime() and localtime() >>> # with no arguments to use the current time: >>> time.asctime() ‘Sun Dec 10 10:09:41 2000’ The function ctime returns a timestamp for a time expressed in ticks: >>> time.ctime(time.time()) ‘Sun Dec 10 10:11:29 2000’ Fancy formatting The function strftime(format,timetuple) formats a TimeTuple in a format you specify. The function strftime returns the string format after performing substitutions on various codes marked with a percent sign, as shown in Table 13-2: Table 13-2 Time Formatting Syntax Code Substitution Example / Range %a Abbreviated day name Thur %A Full day name Thursday %b Abbreviated month name Jan %B Full month name January %c Date and time representation (equivalent to %x %X) 12/10/00 10:09:41 %d Day of the month 01–31 %H Hour (24-hour clock) 00–23 %h Hour (12-hour clock) 01–12 %j Julian day (day of the year) 001–366 %m Month 01–12 %M Minute 00–59 %p A.M. or P.M. AM 4807-7 ch13.F 5/24/01 8:59 AM Page 223 Chapter 13 ✦ Accessing Date and Time Code Substitution Example / Range %S Second 00–61 %U Week number. Week starts with Sunday; days before the first Sunday of the year are in week 0. 00–53 %w Weekday as a number (0=Sunday) 0–6 %W Week number. Week starts with Monday; days before the first Monday of the year are in week 0. 00–53 %x Date 12/10/00 %X Time 10:09:41 %y 2-digit year 00–99 %Y 4-digit year 2000 %Z Time-zone name Pacific Standard Time %% Literal % sign For example, I can print the current week number: >>> time.strftime(“It’s week %W!”,Now) “It’s week 49!” Here is the default formatting string (with the same results as calling ctime): >>> time.strftime(“%a %b %d %I:%M:%S %Y”,Now) ‘Sun Dec 10 10:09:41 2000’ Parsing time The function strptime(timestring[,format]) is the reverse of strftime; it parses a string and returns a TimeTuple. It guesses at any unspecified time components. It raises a ValueError if it cannot parse the string timestring using the format format. The default format is the one that ctime uses: “%a %b %d %I:%M:%S %Y”. Note The strptime function is available on most UNIX systems; however, it is unavailable on Windows. Localization Different countries write dates differently — for example, the string “2/5” means “February 5” in the United States, but “May 2” in England. The function strftime refers to the current locale when performing each substitution. For example, the 223 4807-7 ch13.F 224 5/24/01 8:59 AM Page 224 Part II ✦ Files, Data Storage, and Operating System Services format string “%x” uses the correct day-month ordering for the current locale. However, you still need to take locale into account when writing code — for instance, the format string “%m/%d” is not correct for all locales. CrossReference See Chapter 34 for an overview of the locale module and other information on internationalization. Accessing the Calendar The calendar module provides high-level functions and constants that complement the lower-level functions in the time module. Because calendar uses ticks internally to represent dates, it cannot provide calendars outside the epoch (usually 1970–2038). Printing monthly and yearly calendars The following sections show examples of printing monthly and yearly calendars. monthcalendar(yearnum,monthnum) The function monthcalendar returns a list of lists, representing a monthly calendar. Each entry in the main list represents a week. The sublists contain the seven dates in that week. A 0 (zero) in the sublist represents a day from the previous or next month: >>> calendar.monthcalendar(2000,5) # 4 1/2 weeks in May, 2000 [[1, 2, 3, 4, 5, 6, 7], [8, 9, 10, 11, 12, 13, 14], [15, 16, 17, 18, 19, 20, 21], [22, 23, 24, 25, 26, 27, 28], [29, 30, 31, 0, 0, 0, 0]] month(yearnum,monthnum[,width[,linesperweek]]) The month function returns a multiline string that looks like a monthly calendar for month monthnum of year yearnum. Months are numbered normally (from 1 for January up to 12 for December). The parameter width specifies how wide each column is; the minimum (and default) value is 2. The parameter linesperweek specifies how many rows to print for each week. It defaults to 1; setting it to a higher number like 5 leaves space to write on a printed calendar. Here are two examples: >>> print calendar.month(2002,5) May 2002 Mo Tu We Th Fr Sa Su 12345 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 4807-7 ch13.F 5/24/01 8:59 AM Page 225 Chapter 13 ✦ Accessing Date and Time >>> # 2 rows per week; 3 cols per day >>> print calendar.month(2002,5,3,2) May 2002 Mon Tue Wed Thu Fri Sat Sun 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 The function prmonth(yearnum,monthnum[,width[,linesperweek]]) prints the corresponding output of month. calendar(yearnum[,width[,linesperweek[,columnpadding]]]) The function calendar prints a yearly calendar, with three months per row. The parameters width and linesperweek function as for month. The parameter columnpadding indicates how many spaces to add between month-columns; it defaults to 6. The function prcalendar prints the corresponding output of calendar. Calendar information The weekday function looks up the day of the week for a particular date. The syntax is weekday(year,month,day). Weekdays range from Monday (0) to Sunday (6). Constants for each day (in all-caps) are available, for convenience and code-clarity: >>> # Is May 1, 2002 a Wednesday? >>> calendar.weekday(2002,5,1)==calendar.WEDNESDAY 1 The function monthrange(yearnum,monthnum) returns a two-tuple: The weekday of the first day of month monthnum in year yearnum, and the length of the month. >>> calendar.monthrange(2000,2) # 2000 was a leap year! (1, 29) By default, calendar starts its weeks on Monday, and ends them on Sunday. I like this setting best, because the week ends with the weekend. But you can start your calendar’s weeks on another day by calling setfirstweekday(weekday). The function firstweekday tells you which day of the week is currently the first day of the week: 225 4807-7 ch13.F 226 5/24/01 8:59 AM Page 226 Part II ✦ Files, Data Storage, and Operating System Services >>> calendar.setfirstweekday(calendar.WEDNESDAY) >>> print calendar.month(2002,5) May 2002 We Th Fr Sa Su Mo Tu 1234567 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 >>> calendar.firstweekday() # Weeks start with day #2 (Wed.) 2 Leap years The function isleap(yearnum) returns true if year yearnum is a leap year. The function leapdays(firstyear,lastyear) returns the number of leap days from firstyear to lastyear, inclusive. Using Time Zones The value time.daylight indicates whether a local DST (Daylight Savings Time) time zone is defined. A value of 1 indicates that a DST time zone is available. The value time.timezone is the offset, in seconds, from the local time zone to UTC. This makes it easy to convert between time zones. The value time.altzone is an offset from the local DST time zone to UTC. The offset altzone is more accurate, but it is available only if time.daylight is 1. >>> Now=time.time() >>> time.ctime(Now) # Time in Mountain time zone, USA ‘Sun Dec 10 10:44:49 2000’ >>> time.ctime(Now+time.altzone) # Time in England ‘Sun Dec 10 17:44:49 2000’ The value time.tzname is a tuple. The first entry is the name of the local time zone. The second entry, if available, is the name of the local Daylight Savings Time time zone. The second entry is available only if time.daylight is nonzero. For example: >>> time.tzname (‘Pacific Standard Time’, ‘Pacific Daylight Time’) 4807-7 ch13.F 5/24/01 8:59 AM Page 227 Chapter 13 ✦ Accessing Date and Time Allowing Two-Digit Years Two-digit dates are convenient, but they can be ambiguous. For example, the year “97” should precede the year “03” if the years are 1997 and 2003, but not if they are 1997 and 1903. In 1999, programmers around the world began rooting through legacy code to solve the Y2K Bug — a blanket term for all bugs caused by indiscriminate use of two-digit years. Some people worried that the Y2K Bug would cause The End Of The World As We Know It on January 1, 2000. Fortunately, it didn’t and we can all sleep safely at night — at least until 2038 when epoch-based time starts to overflow. Normally, Python adds 2000 to a two-digit year from 00 to 68, and adds 1900 to twodigit years from 69 to 99. However, for paranoia’s sake, the value time.accept2dyear can be set to 0; this setting causes all two-digit years to be rejected. If you set the environment variable PYTHON2K, the value time.accept2dyear is initialized to 0. For example: >>> Y4=(2000, 12, 10, 10, 9, 41, 6, 345, 0) >>> Y2=(00, 12, 10, 10, 9, 41, 6, 345, 0) # Same date >>> time.mktime(Y4) 976471781.0 >>> time.mktime(Y2) # 2-digit year below 69; add 2000 976471781.0 >>> time.accept2dyear=0 # Zero tolerance for YY! >>> time.mktime(Y2) Traceback (most recent call last): File “<stdin>”, line 1, in ? ValueError: year >= 1900 required Summary Python includes standard libraries for telling time, doing date arithmetic, and converting between time zones. In this chapter, you: ✦ Converted time between tuple and ticks representations. ✦ Formatted and parsed times in human-readable formats. ✦ Checked months and days on a yearly calendar. ✦ Handled various time zones, as well as Daylight Savings Time. In the next chapter you will learn how to use Python to store and retrieve data from databases. ✦ ✦ ✦ 227 4807-7 ch13.F 5/24/01 8:59 AM Page 228 4807-7 ch14.F 5/24/01 8:59 AM Page 229 14 CHAPTER Using Databases ✦ D atabases support permanent storage of large amounts of data. You can easily perform CRUD (Create, Read, Update, and Delete) on database records. Relational databases divide data between tables and support sophisticated SQL operations. Python’s standard libraries include a simple disk-dictionary database. The Python DB API provides a standard way to access relational databases. Various third-party modules implement this API, providing easy access to many flavors of database, including Oracle and MySQL. Using Disk-Based Dictionaries Python’s standard libraries provide a simple database that takes the form of a single disk-based dictionary (or disktionary). This functionality is based on the UNIX utility dbm — on UNIX, you can access databases created by the dbm utility. Several modules define such a database, as shown in Table 14-1. Table 14-1 Disk-Based Dictionary Modules ✦ ✦ ✦ In This Chapter Using disk-based dictionaries DBM example: tracking telephone numbers Advanced disk-based dictionaries Accessing relational databases Example: “soundslike” queries Examining relational metadata Example: creating auditing tables Module Description Advanced features of the DB API anydbm Portable database; chooses the best module from among the others ✦ dumbdbm Slow and limited, but available on all platforms dbm Wraps the UNIX dbm utility; available on UNIX only gdbm Wraps GNU’s improved dbm; available on UNIX only dbhash Wraps the BSD database library; available on UNIX and Windows ✦ ✦ ✦ 4807-7 ch14.F 230 5/24/01 8:59 AM Page 230 Part II ✦ Files, Data Storage, and Operating System Services In general, it is recommended that you use anydbm, as it is available on any platform (even if it has to use dumbdbm!) Each dbm module defines a dbm object and an exception named error. The features in this section are available from every flavor of dbm; the “Advanced DiskBased Dictionaries” section describes extended features not available in dumbdbm. The open function creates a new dbm object. The function’s syntax is open (filename[,flag[,mode]]). The filename parameter is the path to the file used to store the data. The flag parameter is normally optional, but is required for dbhash. It has the following legal values: r [default] Opens the database for read-only access w Opens the database for read and write access c Same as w, but creates the database file if necessary n Same as w, but always creates a new, empty database file Note The flag parameter is required for dbhash.open. Caution Some flavors of dbm (including dumbdbm) permit modifications to a database opened read-only! The optional parameter mode specifies the UNIX-style permissions to set on the database file. Once you have opened a database, you can access it much like a standard dictionary: >>> SimpleDB=anydbm.open(“test”,”c”) # create a new datafile >>> SimpleDB[“Terry”]=”Gilliam” # add a record >>> SimpleDB[“John”]=”Cleese” >>> print SimpleDB[“Terry”] # access a record Gilliam >>> del SimpleDB[“John”] # delete a record The keys and values in a dbm must all be strings. For example: >>> SimpleDB[“Eric”]=5 Traceback (most recent File “<stdin>”, line TypeError: bsddb value # illegal; value is not a string! call last): 1, in ? type must be string Attempting to access a key with no value raises a KeyError exception. You can use the has_key method to verify that a key exists, or call keys to get a list of keys. However, the safe get method from a dictionary is not available: 4807-7 ch14.F 5/24/01 8:59 AM Page 231 Chapter 14 ✦ Using Databases >>> SimpleDB.keys() [‘Terry’] >>> SimpleDB.has_key(“Eric”) 0 When you are finished with a dbm object, call its close method to sync it to disk and free its used resources. DBM Example: Tracking Telephone Numbers The example shown in Listing 14-1 uses a dbm object to track telephone numbers. The dictionary key is a person’s name; the value is his or her telephone number. Listing 14-1: Phone list import anydbm import sys def AddName(DB): print “Enter a name. (Null name to cancel)” # Take the [:-1] slice to remove the \n at the end NewName=sys.stdin.readline()[:-1] if (NewName==””): return print “Enter a phone number.” PhoneNumber=sys.stdin.readline()[:-1] DB[NewName]=PhoneNumber # Poke value into database! def PrintList(DB): # Note: A large database may have MANY keys (too many to # casually put into memory). See Listing 14-2 for a better # way to iterate over keys in dbhash. for Key in DB.keys(): print Key,DB[Key] if (__name__==”__main__”): PhoneDB= dbhash.open(“phone”,”c”) while (1): print “\nEnter a name to look up\n+ to add a name” print “* for a full listing\n. to exit” Command=sys.stdin.readline()[:-1] if (Command==””): continue # Nothing to do; prompt again if (Command==”+”): AddName(PhoneDB) elif (Command==”*”): PrintList(PhoneDB) Continued 231 4807-7 ch14.F 232 5/24/01 8:59 AM Page 232 Part II ✦ Files, Data Storage, and Operating System Services Listing 14-1 (continued) elif (Command==”.”): break # quit! else: try: print PhoneDB[Command] except KeyError: print “Name not found.” print “Saving and closing...” PhoneDB.close() Advanced Disk-Based Dictionaries The various flavors of dbm don’t use compatible file formats — for example, a database created using dbhash cannot be read using gdbm. This means that the only database file-format available on all platforms is that used by dumbdbm. The whichdb module can examine a database to determine which flavor of dbm created it. The function whichdb.whichdb(filename) returns the name of the module that created the datafile filename, returns None if the file is unreadable or does not exist, and returns an empty string if it can’t figure out the file’s format. For example, the following code uses anydbm to create a database, and then queries the database to see what type it really is: >>> MysteryDB=anydbm.open(“Unknown”,”c”) >>> MysteryDB.close() # write file so we can check its db-type >>> whichdb.whichdb(“Unknown”) ‘dbhash’ dbm The dbm module provides an extra string variable, library, which is the name of the underlying ndbm implementation. gdbm The gdbm module provides improved key navigation. The dbm method firstkey returns the first key in the database; the method nextkey(currentkey) returns the key after currentkey. After doing many deletions from a gdbm database, you can call reorganize to free up space used by the datafile. In addition, the method sync flushes any unwritten changes to disk. 4807-7 ch14.F 5/24/01 8:59 AM Page 233 Chapter 14 ✦ Using Databases dbhash The dbhash module also provides key navigation. The dbm methods first and last return the first and last keys, respectively. The methods next(currentkey) and previous(currentkey) return the key before and after currentkey, respectively. In addition, the method sync flushes any unwritten changes to disk. Databases can be very large, so accessing the list of all keys returned by the keys method of a database may eat a lot of memory. The key-navigation methods provided by gdbm and dbhash enable you to iterate over all keys without loading them all into memory. The code in Listing 14-2 is an improved replacement for the PrintList method in the previous telephone list example. Listing 14-2: Improved list iteration with dbhash def PrintList(DB): Record=None try: # first() raises a KeyError if there are no entries Record = DB.first() except KeyError: return # Zero entries while 1: print Record try: # next() raises a KeyError if no next entry Record = DB.next() except KeyError: return # all done! Using BSD database objects The bsddb module, available on UNIX and Windows, provides access to the Berkeley DB library. It provides hashtable, b-tree, and record objects for data storage. The three constructors — hashopen, btopen, and rnopen — take the same parameters (filename, flag, and mode) as the dbm constructor. The constructors take other optional parameters — they are passed directly to the underlying BSD code, and should generally not be used. BSD data objects provide the same functionality as dbm objects, as well as some additional methods. The methods first, last, next, and previous navigate through (and return) the records in the database. The records are ordered by key value for a b-tree object; record order is undefined for a hashtable or record. In addition, the method set_location(keyvalue) jumps to the record with key keyvalue: 233 4807-7 ch14.F 234 5/24/01 8:59 AM Page 234 Part II ✦ Files, Data Storage, and Operating System Services >>> bob=bsddb.btopen(“names”,”c”) >>> bob[“M”]=”Martin” >>> bob[“E”]=”Eric” >>> bob[“X”]=”Xavier” >>> bob.first() # E is first, since this is a b-tree (‘E’, ‘Eric’) >>> bob.next() (‘M’, ‘Martin’) >>> bob.next() (‘X’, ‘Xavier’) >>> bob.next() # navigating “off the edge” raises KeyError Traceback (most recent call last): File “<stdin>”, line 1, in ? KeyError >>> bob.set_location(“M”) (‘M’, ‘Martin’) The sync method of a BSD database object flushes any changes to the datafile. Accessing Relational Databases Relational databases are a powerful, flexible way to store and retrieve many kinds of data. There are many relational database implementations, which vary in scalability and richness of features. The standard libraries do not include relational database support; however, Python modules exist to access almost any relational database, including Oracle, MySQL, DB/2, and Sybase. The Python Database API defines a standard interface for Python modules that access a relational database. Most third-party database modules conform to the API closely, though not perfectly. This chapter covers Version 2.0 of the API. Connection objects The connect method constructs a database connection. The connection is used in constructing cursors. When finished with a connection, call its close method to free it. Databases generally provide a limited pool of connections, so a program should not needlessly use them up. The parameters of the connect method vary by module, but typically include dsn (data source name), user, password, host, and database. Transactions Connections oversee transactions. A transaction is a collection of actions that must execute atomically — completely, or not at all. For example, a bank transfer might debit one account and credit another; this should be done within a single transaction, as performing only one half of the transfer would obviously be unacceptable. 4807-7 ch14.F 5/24/01 8:59 AM Page 235 Chapter 14 ✦ Using Databases Calling the commit connection method completes the current transaction; calling rollback cancels the current transaction. Not all databases support transactions — for example, Oracle does, MySQL doesn’t (yet). The commit method is always available; rollback is only available where transaction support is provided. Cursor objects A cursor can execute SQL statements and retrieve data. The connection method cursor creates and returns a new cursor. The cursor method execute(command [,parameters]) executes the specified SQL statement command, passing any necessary parameters. After executing a command that affects row data, the cursor attribute rowcount indicates the number of rows altered or returned; and the description attribute (described in the “Examining Relational Metadata” section) describes the columns affected. After executing a command that selects data, the method fetchone returns the next row of data (as a sequence, with one entry for each column value). The method fetchmany([size]) returns a sequence of rows — up to size of them. The method fetchall returns all the rows. After using a cursor, call its close method to free it. Databases typically have a limited pool of available cursors, so it is important to free cursors after use. Example: “Sounds-Like” Queries The example shown in Listing 14-3 uses the mxODBC module to look up people whose names “sound like” another name. ODBC is a standard interface for relational databases; ODBC drivers are available for many databases, including Oracle and MySQL. Therefore, the mxODBC module can handle most of the databases you are likely to deal with. Listing 14-4 shows the output from the example. Listing 14-3: Soundex.py # Replace this import with the appropriate one for your system: import ODBC.Windows # Dictionary used for sounds-like coding SoundexDict = {“B”:”1”,”P”:”1”,”F”:”1”,”V”:”1”, “C”:”2”,”S”:”2”,”G”:”2”,”J”:”2”, “K”:”2”,”Q”:”2”,”X”:”2”,”Z”:”2”, “D”:”3”,”T”:”3”, “L”:”4”, “M”:”5”,”N”:”5”, “R”:”6”, “A”:”7”,”E”:”7”,”I”:”7”,”O”:”7”,”U”:”7”,”Y”:”7”, “H”:”8”,”W”:”8”} Continued 235 4807-7 ch14.F 236 5/24/01 8:59 AM Page 236 Part II ✦ Files, Data Storage, and Operating System Services Listing 14-3 (continued) # These SQL statements may need to be tweaked for your database # (They work with MySQL) CREATE_EMPLOYEE_SQL = “””CREATE TABLE EMPLOYEE ( EMPLOYEE_ID INT NOT NULL, FIRST_NAME VARCHAR(20) NOT NULL, LAST_NAME VARCHAR(20) NOT NULL, MANAGER_ID INT )””” DROP_EMPLOYEE_SQL=”DROP TABLE EMPLOYEE” INSERT_SQL = “INSERT INTO EMPLOYEE VALUES “ def SoundexEncoding(str): “””Return the 4-character SOUNDEX code for a string. Take first letter, then encode subsequent consonants as numbers. Ignore repeated codes (e.g MM codes as 5, not 55), unless separated by a vowel (e.g. SOS codes as 22)””” if (str==None or str==””): return None str = str.upper() # ignore case! SoundexCode=str[0] LastCode=SoundexDict[str[0]] for char in str[1:]: CurrentCode=SoundexDict[char] if (CurrentCode==”8”): pass # Don’t include, or separate used consonants elif (CurrentCode==”7”): LastCode=None # Include consonants after vowels elif (CurrentCode!=LastCode): # Skip doubled letters SoundexCode+=CurrentCode if len(SoundexCode)==4: break # limit to 4 characters # Pad with zeroes (e.g. Lee is L000): SoundexCode += “0”*(4-len(SoundexCode)) return SoundexCode # Create the EMPLOYEE table def CreateTable(Conn): NewCursor=Conn.cursor() try: NewCursor.execute(DROP_EMPLOYEE_SQL) NewCursor.execute(CREATE_EMPLOYEE_SQL) finally: NewCursor.close() # insert a new employee into the table def CreateEmployee(Conn,DataValues): NewCursor=Conn.cursor() try: NewCursor.execute(INSERT_SQL+DataValues) finally: NewCursor.close() # Do a sounds-like query on a name def PrintUsersLike(Conn,Name): 4807-7 ch14.F 5/24/01 8:59 AM Page 237 Chapter 14 ✦ Using Databases if (Name==None or Name==””): return print “Users with last name similar to”,Name+”:” SoundexName = SoundexEncoding(Name) QuerySQL = “SELECT EMPLOYEE_ID, FIRST_NAME, LAST_NAME FROM” QuerySQL+= “ EMPLOYEE WHERE LAST_NAME LIKE ‘“+Name[0]+”%’” NewCursor=Conn.cursor() try: NewCursor.execute(QuerySQL) for EmployeeRow in NewCursor.fetchall(): if (SoundexEncoding(EmployeeRow[2])==SoundexName): print EmployeeRow finally: NewCursor.close() if (__name__==”__main__”): # pass clear_auto_commit=0, because MySQL doesn’t support # transactions (yet) and can’t handle autocommit flag # Replace “MyDB” with your datasource name! Conn=ODBC.Windows.Connect(“MyDB”,clear_auto_commit=0) CreateTable(Conn) CreateEmployee(Conn,’(1,”Bob”,”Hilbert”,Null)’) CreateEmployee(Conn,’(2,”Sarah”,”Pfizer”,Null)’) CreateEmployee(Conn,’(3,”Sandy”,”Lee”,1)’) CreateEmployee(Conn,’(4,”Pat”,”Labor”,2)’) CreateEmployee(Conn,’(5,”Larry”,”Helper”,Null)’) PrintUsersLike(Conn,”Heilbronn”) PrintUsersLike(Conn,”Pfizer”) PrintUsersLike(Conn,”Washington”) PrintUsersLike(Conn,”Lieber”) Listing 14-4: Soundex output Users (1.0, (5.0, Users (2.0, Users Users (4.0, with last name similar ‘Bob’, ‘Hilbert’) ‘Larry’, ‘Helper’) with last name similar ‘Sarah’, ‘Pfizer’) with last name similar with last name similar ‘Pat’, ‘Labor’) to Heilbronn: to Pfizer: to Washington: to Lieber: Examining Relational Metadata When a cursor returns data, the cursor attribute description is metadata — definitions of the columns involved. A column’s definition is represented as a seven-item sequence; description is a sequence of such definitions. The items in the sequence are listed in Table 14-2. 237 4807-7 ch14.F 238 5/24/01 8:59 AM Page 238 Part II ✦ Files, Data Storage, and Operating System Services Table 14-2 Metadata Sequence Pieces Index Data 0 Column name 1 Type code 2 Display size (in columns) 3 Internal size (in characters or bytes) 4 Numeric scale 5 Numeric precision 6 Nullable (if 0, no nulls are allowed) For example, the following is metadata from the Employee table of the Soundex example: >>> mc.execute(“select FIRST_NAME, MANAGER_ID from EMPLOYEE”) >>> mc.description ((‘FIRST_NAME’, 12, None, None, 5, 0, 0), (‘MANAGER_ID’, 3, None, None, 1, 0, 1)) Note The mxODBC module does not return display size and internal size. Example: Creating Auditing Tables Sometimes, it is useful to view old versions of data. For example, you may want to know both someone’s current address and his or her old address. Or, a medical database may track who changed a patient’s record, and when. One way to capture this data is with a mirror table — whenever an insert or update or delete occurs in the main table, a corresponding row is written to the mirror table. The mirror rows contain data, a timestamp, and the ID of the editing user — therefore, they provide a full audit trail of all data changes. Ideally, mirror rows should be inserted in the same transaction as the data-manipulation, to ensure that the audit trail is accurate. The script shown in Listing 14-5 uses metadata to write SQL that creates a mirror table for a data table. Listing 14-6 shows a sample of the script’s output. 4807-7 ch14.F 5/24/01 8:59 AM Page 239 Chapter 14 ✦ Using Databases Listing 14-5: MirrorMaker.py import ODBC.Windows “”” MirrorMaker builds mirror tables, for purposes of auditing. For a table TABLEX, we create SQL to add a mirror table TABLEX_M. The mirror table tracks version numbers, update times, and updating users. “”” # Replace these constants with values for your database SERVER_NAME = “MyDB” USER_NAME = “eva” PASSWORD = “destruction” SAMPLE_TABLE = “EMPLOYEE” # Metadata for the mirror table’s special columns VERSION_NUMBER_COLUMN=(“VERSION_NUMBER”, ODBC.Windows.NUMERIC,None,None,0,0,0) LAST_UPDATE_COLUMN=(“LAST_UPDATE”, ODBC.Windows.TIMESTAMP,None,None,0,0,0) UPDATE_USER_COLUMN=(“UPDATE_USER_ID”, ODBC.Windows.NUMERIC,None,None,0,0,0) def CreateColumnDefSQL(ColumnTuple): ColumnSQL = ColumnTuple[0] #name ColumnSQL += “ “ # The mxODBC function sqltype returns the SQL name of a # (numeric) column type. (For a different database # module, you may need to code this translation yourself.) OracleColumnType = ODBC.Windows.sqltype[ColumnTuple[1]] ColumnSQL += OracleColumnType # width of character fields if (OracleColumnType == “VARCHAR2” or OracleColumnType == “VARCHAR”): # Internal size not returned by mxODBC; so, use scale ColumnSQL += “(“+ColumnTuple[4]+”)” # width if (OracleColumnType == “NUMBER”): if (ColumnTuple[4]): # precision+scale ColumnSQL += “(“ + ColumnTuple[4] + “,”+ColumnTuple[5]+”)” # if (ColumnTuple[6]): # nullable ColumnSQL += “ NULL” else: ColumnSQL += “ NOT NULL” return ColumnSQL def CreateMirrorTableDefSQL(MyConnection,TableName): MyCursor = MyConnection.cursor() # This query returns no rows (because 1!=2), but returns # metadata (the definitions of each column in the table). Continued 239 4807-7 ch14.F 240 5/24/01 8:59 AM Page 240 Part II ✦ Files, Data Storage, and Operating System Services Listing 14-5 (continued) # Analogous to the SQL command “describe TABLENAME”. MyCursor.execute(“SELECT * from “+TableName+” where 1=2”); SQLString = “CREATE TABLE “+TableName+”_M (“ # Loop through columns, and create DDL for each FirstColumn=1 for ColumnInfo in MyCursor.description: if (FirstColumn!=1): SQLString=SQLString+”,” FirstColumn=0 SQLString += “\n”+CreateColumnDefSQL(ColumnInfo) # Add SQL to create the special mirror-table columns SQLString += “,\n” + CreateColumnDefSQL(VERSION_NUMBER_COLUMN) SQLString += “,\n” + CreateColumnDefSQL(LAST_UPDATE_COLUMN) SQLString += “,\n” + CreateColumnDefSQL(UPDATE_USER_COLUMN) SQLString += “\n)\n” MyCursor.close() return SQLString if (__name__==”__main__”): MyConnection = ODBC.Windows.Connect(SERVER_NAME,USER_NAME,PASSWORD) print CreateMirrorTableDefSQL(MyConnection,SAMPLE_TABLE) Listing 14-6: MirrorMaker output CREATE TABLE EMPLOYEE_M ( EMPLOYEE_ID DECIMAL NOT NULL, FIRST_NAME VARCHAR(0) NOT NULL, LAST_NAME VARCHAR(0) NOT NULL, MANAGER_ID DECIMAL NULL, VERSION_NUMBER NUMERIC NOT NULL, LAST_UPDATE TIMESTAMP NOT NULL, UPDATE_USER_ID NUMERIC NOT NULL ) Advanced Features of the DB API Relational databases feature various column types, such as INT and VARCHAR. A database module should export constants describing these datatypes; these constants are used in description metadata. For example, the following code checks a column type (12) against a module-level constant (VARCHAR): 4807-7 ch14.F 5/24/01 8:59 AM Page 241 Chapter 14 ✦ Using Databases >>> MyCursor.execute(“SELECT EMPLOYEE_NAME from EMPLOYEE where FIRST_NAME=’Bob’”) >>> MyCursor.description[0] (‘FIRST_NAME’, 12, None, None, 3, 0, 0) >>> MyCursor.description[0][1]==ODBC.Windows.VARCHAR 1 Some column types, such as dates, demand a particular kind of data. A database module should export functions to construct date, time, and timestamp values. For example, the function Date(year,month,day) constructs a date value (suitable for insertion into the database) corresponding to the given year, month, and day. The module mxDateTime provides the preferred implementation of date and time objects. Input and output sizes The cursor attribute arraysize specifies how many rows, by default, to return in each call to fetchmany. It defaults to 1, but you can increase it if desired. Manipulating arraysize is more efficient than passing a size parameter to fetchmany: >>> MyCursor.execute(“SELECT FIRST_NAME FROM EMPLOYEE”) >>> MyCursor.rowcount # total fetchable rows 5 >>> MyCursor.fetchmany() # default arraysize is 1 [(‘Bob’,)] >>> MyCursor.arraysize=5 # get up to 5 rows at once >>> MyCursor.fetchmany() # (only 4 left, so I don’t get 5) [(‘Sarah’,), (‘Sandy’,), (‘Pat’,), (‘Larry’,)] The cursor methods setinputsizes(size) and setoutputsize(size [,columnindex]) let you set an “expected size” for columns before executing a SQL statement. These methods are optional, and exist to improve performance and memory usage. The size parameter for setinputsizes is a sequence. Each entry in size should specify the maximum length for each parameter. If an entry in size is None, then no block of memory will be set aside for the corresponding parameter value (this is the default behavior). The method setoutputsize sets a maximum buffer size for data read from large columns (LONG or BLOB). If columnindex is not specified, the buffer size is set for all large columns in the result sequence. For example, the following code limits the data read from the long DESCRIPTION column to 50 characters: >>> MyCursor.setoutputsizes(1,50) >>> MyCursor.execute(“select GAME_NAME, DESCRIPTION from GAME”) >>> MyCursor.fetchone() (‘005’, ‘ You play a spy who must take a briefcase and suc’) 241 4807-7 ch14.F 242 5/24/01 8:59 AM Page 242 Part II ✦ Files, Data Storage, and Operating System Services Reusable SQL statements Before a SQL statement can be executed, it must be parsed. Vendors such as Oracle cache recently parsed SQL commands so that the commands need not be re-parsed if they are used again. Therefore, you should build re-usable SQL statements with marked parameters, instead of hard-coded values. This way, the parameters can be passed into the execute method. The following example re-uses the same SQL statement to query a video game database twice: >>> SQLQuery = “select GAME_NAME from GAME where GAME_ID = ?” >>> MyCursor.execute(SQLQuery,(60,)) # tuple provides ID of 60 >>> MyCursor.fetchall() [(‘Air Combat 22’,)] >>> MyCursor.execute(SQLQuery,(200,)) # no need to re-parse SQL >>> MC.fetchall() [(‘Badlands’,)] The syntax for parameter marking is described by the module variable paramstyle (see the next section, “Database library information”). The cursor method executemany(command,parametersequence) runs the same SQL statement command many times, once for each collection of parameters in parametersequence. Database library information The module variable apilevel is a string describing the supported DB API level. It should be either 1.0 or 2.0; if it is not available, assume the supported API level is 1.0. The module variable threadsafety describes what level of concurrent access the module supports: 0 Threads may not share the module 1 Threads may share the module 2 Threads may share connections 3 Threads may share cursors The module variable paramstyle describes which style of parameter marking the module expects to see in SQL statements. Following are the legal values of paramstyle and an example of such a marked parameter: qmark WHERE NAME=? numeric WHERE NAME=.1 named WHERE NAME=.name format WHERE NAME=%s pyformat WHERE NAME=%(name)s 4807-7 ch14.F 5/24/01 8:59 AM Page 243 Chapter 14 ✦ Using Databases Error hierarchy Database warnings and errors are subclasses of the class StandardError from the module exceptions. You can catch the Error class to do general error handling, or catch more specific exceptions. Figure 14-1 shows the inheritance hierarchy of database exceptions. See Table 14-3 for a description of each exception. Database Exceptions exceptions.StandardError Error Warning InterfaceError DatabaseError NotSupportedError ProgrammingError OperationalError DataError IntegrityError Figure 14-1: Database exception class hierarchy Table 14-3 Database Exceptions Type Meaning Warning Significant warnings, such as data-value truncation during insertion. Error Base class for other errors. Not raised directly. InterfaceError Raised when the database module encounters an internal error. An InterfaceError stems from the database module, not the database itself. DatabaseError Errors relating to the database itself. Mostly used as a base class for other errors. DataError Errors due to invalid data, such as an out-of-range numeric value. Continued 243 4807-7 ch14.F 244 5/24/01 8:59 AM Page 244 Part II ✦ Files, Data Storage, and Operating System Services Table 14-3 (continued) Type Meaning OperationalError Operational errors, such as a failure to connect to the database. IntegrityError Data integrity errors, such as a missing foreign key. InternalError Internal database error, such as a cursor becoming disconnected. ProgrammingError Invalid call to the database module; for example, trying to use a cursor that has been closed, or calling fetch on a cursor before executing a command that returns data. NotSupportedError Some portions of the DB API are optional. A module that does not implement optional methods may raise NotSupportedError if you attempt to call them. Summary Python’s standard libraries include powerful tools for handling dictionaries on disk. Modules implementing the Python Database API permit easy access to relational databases. In this chapter, you: ✦ Learned about Python’s flavors of dbm. ✦ Stored and retrieved dictionary data on disk. ✦ Looked up employees with a “sounds-like” query. ✦ Used table metadata to easily build new relational tables. In the next chapter, you learn how to harness Python for networking. ✦ ✦ ✦ 4807-7 PO3.F 5/24/01 8:59 AM Page 245 P Networking and the Internet A R T III ✦ ✦ ✦ ✦ Chapter 15 Networking Chapter 16 Speaking Internet Protocols Chapter 17 Handling Internet Data Chapter 18 Parsing XML and Other Markup Languages ✦ ✦ ✦ ✦ 4807-7 PO3.F 5/24/01 8:59 AM Page 246 4807-7 ch15.F 5/24/01 8:59 AM Page 247 15 CHAPTER Networking T he modules covered in this chapter teach you everything you need to know to communicate between programs on a network. The networking topics covered here don’t require more than one computer, however; you can use networking for interprocess communication on a single machine. Networking Background ✦ ✦ ✦ ✦ In This Chapter Networking background Working with addresses and host names This section provides a brief introduction to some of the terms you’ll encounter in the rest of this chapter. Communicating with low-level sockets A socket is a network connection endpoint. When your Web browser requests the main Web page of www.python.org, for example, your Web browser creates a socket and instructs it to connect to the Web server hosting the Python Web site, where the Web server is also listening on a socket for incoming requests. The two sides use the sockets to send messages and other data back and forth. Example: a multicast chat application When in use, each socket is bound to a particular IP address and port. An IP address is a sequence of four numbers in the range of 0 to 255 (for example, 173.15.20.201); port numbers range from 0 to 65535. Port numbers less than 1024 are reserved for well-known networking services (a Web server, for example, uses port 80); the maximum reserved value is stored in the socket module’s IPPORT_RESERVED variable. You can use other port numbers for your own programs, although technically, ports 1024 to 5000 (socket.IPPORT_USERRESERVED) are used for officially registered applications (although nobody will yell at you for using them). Handling multiple requests without threads Not all IP addresses are visible to the rest of the world. Some, in fact, are specifically reserved for addresses that are never public (such as addresses of the form 192.168.y.z or 10.x.y.z). The address 127.0.0.1 is the localhost address; it always refers to the current computer. Programs can use this address to connect to other programs running on the same machine. Using SocketServers Processing Web browser requests ✦ ✦ ✦ ✦ 4807-7 ch15.F 248 5/24/01 8:59 AM Page 248 Part III ✦ Networking and the Internet Remembering more than a handful of IP addresses can be tedious, so you can also pay a small fee and register a host name or domain name for a particular address (not surprisingly, more people visit your Web site if they can point their Web browser at www.threemeat.com instead of 208.114.27.12). Domain Name Servers (DNS) handle the task of mapping the names to the IP addresses. Every computer can have a host name, even if it isn’t an officially registered one. Exactly how messages are transmitted through a network is based on many factors, one of which is the different protocols that are in use. Many protocols build upon simpler, lower-level protocols to form a protocol stack. HTTP, for example, is the protocol used to communicate between Web browsers and Web servers, and it is built upon the TCP protocol, which is in turn built upon a protocol named IP. When sending messages between two programs of your own, you usually choose between the TCP and UDP protocols. TCP creates a persistent connection between two endpoints, and the messages that you send are guaranteed to arrive at their destination and to arrive in order. UDP is connectionless, a bit faster, but less reliable. Messages you send may or may not make it to the other end; and if they do make it, they might arrive out of order. Occasionally, more than one copy of a message makes it to the receiver, even if you sent it only once. You can find volumes full of additional information on networking; this section doesn’t even scratch the surface. It does, however, give you a head start on understanding the following sections. Working with Addresses and Host Names The socket module provides several functions for working with host names and addresses. Note The socket module is a very close wrapper around the C socket library; and like the C version, it supports all sorts of options. This chapter covers the most common and useful features of sockets; consult the Winsock help file or the UNIX socket man pages for coverage of more arcane features. In many cases, the socket module defines variables that map directly to the C equivalent (for example, socket.IP_MAX_MEMBERSHIPS is equivalent to the C constant of the same name). gethostname() returns the host name for the computer on which the program is running: >>> import socket >>> socket.gethostname() ‘endor’ 4807-7 ch15.F 5/24/01 8:59 AM Page 249 Chapter 15 ✦ Networking gethostbyname(name) tries to resolve the given host name to an IP address. First a check is made to determine whether the current computer can do the translation. If it doesn’t know, a request is sent to a remote DNS server (which in turn may ask other DNS servers too). gethostbyname returns the name or raises an exception if the lookup fails: >>> socket.gethostbyname(‘endor’) ‘10.0.0.6’ >>> socket.gethostbyname(‘www.python.org’) ‘132.151.1.90’ An extended form, gethostbyname_ex(name), returns a 3-tuple consisting of the primary host name of the given address, a list of alternative host names for the same IP address, and a list of other IP addresses for the same interface on that same host (both lists may be empty): >>> socket.gethostbyname(‘www.yahoo.com’) ‘64.58.76.178’ >>> socket.gethostbyname_ex(‘www.yahoo.com’) (‘www.yahoo.akadns.net’, [‘www.yahoo.com’], [‘64.58.76.178’, ‘64.58.76.176’, ‘216.32.74.52’, ‘216.32.74.50’, ‘64.58.76.179’, ‘216.32.74.53’, ‘64.58.76.177’, ‘216.32.74.51’, ‘216.32.74.55’]) The gethostbyaddr(address) function does the same thing, except that you supply it an IP address string instead of a host name: >>> socket.gethostbyaddr(‘132.151.1.90’) (‘parrot.python.org’, [‘www.python.org’], [‘132.151.1.90’]) getservbyname(service, protocol) takes a service name (such as ‘telnet’ or ‘ftp’) and a protocol (such as ‘tcp’ or ‘udp’) and returns the port number used by that service: >>> socket.getservbyname(‘http’,’tcp’) 80 >>> socket.getservbyname(‘telnet’,’tcp’) 23 >>> socket.getservbyname(‘doom’,’udp’) 666 # id Software registered this for the game “Doom” Often, non-Python programs store and use IP addresses in their 32-bit packed form. The inet_aton(ip_addr) and inet_ntoa(packed) functions convert back and forth between this form and an IP address string: >>> socket.inet_aton(‘177.20.1.201’) ‘\261\024\001\311’ # A 4-byte string >>> socket.inet_ntoa(‘\x7F\x00\x00\x01’) ‘127.0.0.1’ 249 4807-7 ch15.F 250 5/24/01 8:59 AM Page 250 Part III ✦ Networking and the Internet socket also defines a few variables representing some reserved IP addresses. INADDR_ANY and INADDR_BROADCAST are reserved IP addresses referring to any IP address and the broadcast address, respectively; and INADDR_LOOPBACK refers to the loopback device, always at address 127.0.0.1. These variables are in the numeric 32-bit form. The getfqdn([name]) function returns the fully qualified domain name for the given hostname (if omitted, it returns the fully qualified domain name of the local host): >>> socket.getfqdn(‘’) ‘dialup84.lasal.net’ New Feature getfqdn was new in Python 2.0. Communicating with Low-Level Sockets Although Python provides some wrappers that make using sockets easier (you’ll see them later in this chapter), you can always work with sockets directly too. Creating and destroying sockets The socket(family, type[, proto]) function in the socket module creates a new socket object. The family is usually AF_INET, although others such as AF_IPX are sometimes available, depending on the platform. The type is most often SOCK_STREAM (for connection-oriented, reliable TCP connections) or SOCK_DGRAM (for connectionless UDP messages): >>> from socket import * >>> s = socket(AF_INET,SOCK_STREAM) The combination of family and type usually implies a protocol, but you can specify it using the optional third parameter to socket using values such as IPPROTO_TCP or IPPROTO_RAW. Instead of using the IPPROTO_ variables, you can use the getprotobyname(proto) function: >>> getprotobyname(‘tcp’) 6 >>> IPPROTO_TCP 6 fromfd(fd, family, type[, proto]) is a rarely used function for creating a socket object from an open file descriptor (returned from a file’s fileno() method). The descriptor should be connected to a real socket, and not to a file. The fileno() method of a socket object returns the file descriptor (an integer) for this socket. See the section “Handling Multiple Requests Without Threads” later in this chapter for an idea of where this might be useful. 4807-7 ch15.F 5/24/01 8:59 AM Page 251 Chapter 15 ✦ Networking When you are finished with a socket object, you call the close() method, after which no further operation on the object will succeed (sockets are automatically closed when they are garbage collected, but it’s a good idea to explicitly close them when possible, both to free up resources sooner and to make your program clearer). Alternatively, you can use the shutdown(how) method to close one or both halves of a connection. Passing a value of 0 prevents the socket from receiving any more data, 1 prevents any additional sends, and 2 prevents additional transmission in either direction. Connecting sockets When two sockets connect (via TCP, for example), one side listens for and accepts an incoming connection, and the other side initiates that connection. The listening side creates a socket, calls bind(address) to bind it to a particular address and port, calls listen(backlog) to listen for incoming connections, and finally calls accept() to accept the new, incoming connection: >>> >>> >>> >>> s = socket(AF_INET,SOCK_STREAM) s.bind((‘127.0.0.1’,44444)) s.listen(1) q,v = s.accept() # Returns socket q and address v Note that the preceding code will block or appear to hang until a connection is present to be accepted. No problem; just initiate a connection from another Python interpreter. The connecting side creates a socket and calls connect(address): >>> s = socket(AF_INET,SOCK_STREAM) >>> s.connect((‘127.0.0.1’,44444)) At this point, the first side of the connection uses socket q to communicate with the second side, using socket s. To verify that they are connected, enter the following line on the first, or server, side: >>> q.send(‘Hello from Python!’) 18 @code:# Number of bytes sent On the other side, enter the following: >>> s.recv(1024) # Receive up to 1024 bytes ‘Hello from Python!’ The addresses you pass to bind and connect are 2-tuples of (ipAddress,port) for AF_INET sockets. Instead of connect, you can also call the connect_ex(address) method. If the underlying call to the C connect returns an error, connect_ex will also return an error (or 0 for success), instead of raising an exception. 251 4807-7 ch15.F 252 5/24/01 8:59 AM Page 252 Part III ✦ Networking and the Internet When you call listen, you pass in a number specifying the maximum number of incoming connections that will be placed in a wait queue. If more connections arrive when the queue is full, the remote side is informed that the connection was refused. The SOMAXCONN variable in the socket module indicates the maximum size the wait queue can be. The accept() method returns an address of the same form used by bind and connect, indicating the address of the remote socket. The following uses the v variable from the preceding example: >>> v (‘127.0.0.1’, 1039) UDP sockets are not connection-oriented, but you can still call connect to associate a socket with a given destination address and port (see the next section for details). Sending and receiving data send(string[, flags]) sends the given string of bytes to the remote socket. sendto(string[, flags], address) sends the given string to a particular address. Generally, the send method is used with connection-oriented sockets, and sendto is used with non-connection–oriented sockets, but if you call connect on a UDP socket to associate it with a particular destination, you can then call send instead of sendto. Both send and sendto return the number of bytes that were actually sent. When sending large amounts of data quickly, you may want to ensure that the entire message was sent, using a function like the following: def safeSend(sock,msg): sent = 0 while msg: i = sock.send(msg) if i == -1: # Error return -1 sent += i msg = msg[i:] time.sleep(25) # Wait a little while the queue empties return sent This keeps resending part of the message as needed until the entire message has been sent. Tip An even better solution to this problem is to avoid sending data until you know at least some if it can be written. See “Handling Multiple Requests Without Threads” later in this chapter for details. 4807-7 ch15.F 5/24/01 8:59 AM Page 253 Chapter 15 ✦ Networking The recv(bufsize[,flags]) method receives an incoming message. If a lot of data is waiting, it returns only the first bufsize bytes that are waiting. recvfrom (bufsize[,flags]) does the same thing, except that with AF_INET sockets the return value is (data, (ipAddress,port)) so that you can see from where the message originated (this is useful for connectionless sockets). The send, sendto, recv, and recvfrom methods all take an optional flags parameter that defaults to 0. You can use a bitwise-OR on any of the socket.MSG_* variables to create a value for flags. The values available vary by platform, but some of the most common are listed in Table 15-1. Table 15-1 Flag Values for send and recv Flag Description MSG_OOB Process out-of-band data. MSG_DONTROUTE Don’t use routing tables; send directly to the interface. MSG_PEEK Return the waiting data without removing it from the queue. For example, if you have an open socket that has a message waiting to be received, you can take a peek at the message without actually removing it from the queue of incoming data: >>> q.recv(1024,MSG_PEEK) ‘Hello!’ >>> q.recv(1024,MSG_PEEK) # You could call this over and over. ‘Hello!’ The makefile([mode[, bufsize]]) method returns a file-like object wrapping this socket, so that you can then pass it to code that expects a file argument (or maybe you prefer to use file methods instead of send and recv). The optional mode and bufsize parameters take the same values as the built-in open function. CrossReference Chapter 8 explains the use of files and filelike objects. Using socket options A socket object’s getpeername() and getsockname() methods both return a 2tuple containing an IP address and a port (just as you’d pass to connect or bind). getpeername returns the address and port of the remote socket to which it is connected, and getsockname returns the same information for the local socket. By default, sockets are blocking, which means that socket method calls don’t return until the action completes. For example, if the outgoing buffer is full and you try to 253 4807-7 ch15.F 254 5/24/01 8:59 AM Page 254 Part III ✦ Networking and the Internet send more data, the call to send will try to block until it can put more data into the buffer. You can change this behavior by calling the setblocking(flag) method with a value of 0. When a socket is nonblocking, it will raise the error exception if the requested action would cause it to block One useful application of this behavior is that you can create servers that shut down gracefully: s = socket(AF_INET,SOCK_STREAM) s.bind((‘10.0.0.6’,55555)) s.listen(5) s.setblocking(0) while bKeepGoing: try: q,v = s.accept() except error: q = None if q: processRequest(q,v) else: time.sleep(0.25) This server continuously tries to accept a new connection and send it off to the fictional processRequest function. If a new connection isn’t available, it sleeps for a quarter of a second and tries again. This means that some other part of your program can set the bKeepGoing variable to 0, and the preceding loop will exit. Tip Another approach is to call select or poll on your listen socket to detect when a new connection has arrived. See “Handling Multiple Requests Without Threads” later in this chapter for more information. Other socket options can be set and retrieved with the setsockopt(level, name, value) and getsockopt(level, name[, buflen]) methods. Sockets represent several layers of a protocol stack, and the level parameter specifies at what level the option should be applied. (For example, the option may pertain to the socket itself, an intermediate protocol such as TCP, or a lower protocol such as IP.) The values for level start with SOL_ (SOL_SOCKET, SOL_TCP, and so on). The name of the option identifies exactly which option you’re talking about, and the socket module defines whatever option names are available on your platform. The C version of setsockopt requires that you pass in a buffer for the value parameter, but in Python you can just pass in a number if that particular option expects a numeric value. You can also pass in a buffer (a string), but it’s up to you to make sure you use the proper format. With getsockopt, not specifying the buflen parameter means you’re expecting a numeric value, and that’s what it returns. If you do supply buflen, getsockopt returns a string representing a buffer, and its maximum length will be buflen bytes. Although there’s a ton of options in existence, Table 15-2 lists some of the more common ones you’ll need, along with what type of data the value parameter is supposed to be. For example, use the following to set the send buffer size of a socket to about 64 KB: 4807-7 ch15.F 5/24/01 8:59 AM Page 255 Chapter 15 ✦ Networking >>> s = socket(AF_INET,SOCK_STREAM) >>> s.setsockopt(SOL_SOCKET, SO_SNDBUF, 65535) To get the time-to-live (TTL) value or number of hops a packet can make before being discarded by a router, use this: >>> s.getsockopt(SOL_IP, IP_TTL) 32 See the sample chat application in the next section for more examples of using setsockopt. Table 15-2 Common setsockopt and getsockopt Options Option Name Value Description SO_TYPE (Get only) Socket type (for example, SOCK_STREAM) SO_ERROR (Get only) Socket’s last error SO_LINGER Boolean Linger on close if data present SO_RCVBUF Number Input (receive) buffer size SO_SNDBUF Number Options for SOL_SOCKET SO_RCVTIMEO Output (send) buffer size 1 Input (receive) timeout delay 1 Time struct SO_SNDTIMEO Time struct Output (send) timeout delay SO_REUSEADDR Boolean Enable multiple users of a local address/port Boolean Send data immediately instead of waiting for minimum send amount IP_TTL 0–255 Maximum number of hops a packet can travel IP_MULTICAST_TTL 0–255 Maximum number of hops a packet can travel IP_MULTICAST_IF inet_aton(ip) Select interface over which to transmit IP_MULTICAST_LOOP Boolean Enable sender to receive a copy of multicast packets it sends out IP_ADD_MEMBERSHIP ip_mreq2 Join a multicast group Options for SOL_TCP TCP_NODELAY Options for SOL_IP IP_DROP_MEMBERSHIP 2 ip_mreq Leave a multicast group 1 The struct is two C long variables to hold seconds and microseconds. 2 The struct is the concatenation of two calls to inet_aton — one for multicast address and one for local address. 255 4807-7 ch15.F 256 5/24/01 8:59 AM Page 256 Part III ✦ Networking and the Internet Converting numbers Because the byte ordering can vary by platform, a network order specifies a standard ordering to use when transferring numbers across a network. The nthol(x) and ntohs(x) functions take a network number and convert it to the same number using the current host’s byte ordering, and the htonl(x) and htons(x) functions convert in the other direction (if the current host has the same byte ordering as network order, the functions do nothing): >>> import socket >>> socket.htons(20000) # Convert a 16-bit value 8270 >>> socket.htonl(20000) # Convert a 32-bit value 541982720 >>> socket.ntohl(541982720) 20000 Example: A Multicast Chat Application The example in this section combines material from several chapters to create a chat application that also enables you to draw on a shared whiteboard, as shown in Figure 15-1. Figure 15-1: The chat/whiteboard application in action Instead of using a client/server model, the program uses multicast sockets for its communication. When you send a message to a multicast address (those addresses in the range from 224.0.0.1 to 239.255.255.255, inclusive), the message is sent to all computers that have joined that particular multicast group. This provides a simple way to send messages to any number of other computers, without having to keep 4807-7 ch15.F 5/24/01 8:59 AM Page 257 Chapter 15 ✦ Networking track of which computers are listening. (This could also be considered a security hole — were this a “real-world” application, you’d want to encrypt the messages or use some other means to prevent eavesdropping.) Save the program in Listing 15-1 to a file named multichat.py. To start the application, specify on the command line your name or alias and your color. The color is passed to Tkinter (the module in charge of the user interface), so normal color names such as blue or red work, but you can also use any of Tkinter’s niftier colors: C:\temp> python multitest.py Bob SlateBlue4 You don’t need several computers to try this program out; just start multiple copies and watch them interact. CrossReference This application uses Tkinter for its user interface. To learn more about Tkinter, see Chapters 19 and 20. It also uses threads, which you can learn about in Chapter 26. Finally, read Chapter 12 to learn about serializing Python objects with pickle and cPickle. Listing 15-1: multichat – Multicast chat/ whiteboard application from Tkinter import * from socket import * import cPickle, threading, sys # Each message is a command + data CMD_JOINED,CMD_LEFT,CMD_MSG,CMD_LINE,CMD_JOINRESP = range(5) people = {} # key = (ipaddr,port), value = (name,color) def sendMsg(msg): sendSock.send(msg,0) def onQuit(): ‘User clicked Quit button’ sendMsg(chr(CMD_LEFT)) # Notify others that I’m leaving root.quit() def onMove(e): ‘Called when LButton is down and mouse moves’ global lastLine,mx,my canvas.delete(lastLine) # Erase temp line mx,my = e.x,e.y # Draw a new temp line lastLine = \ canvas.create_line(dx,dy,mx,my,width=2,fill=’Black’) Continued 257 4807-7 ch15.F 258 5/24/01 8:59 AM Page 258 Part III ✦ Networking and the Internet Listing 15-1 (continued) def onBDown(e): ‘User pressed left mouse button’ global lastLine,dx,dy,mx,my canvas.bind(‘<Motion>’,onMove) # Start receiving move msgs dx,dy = e.x,e.y mx,my = e.x,e.y # Draw a temporary line lastLine = \ canvas.create_line(dx,dy,mx,my,width=2,fill=’Black’) def onBUp(e): ‘User released left mouse button’ canvas.delete(lastLine) # Erase the temporary line canvas.unbind(‘<Motion>’) # No more move msgs, please! # Send out the draw-a-line command sendMsg(chr(CMD_LINE)+cPickle.dumps((dx,dy,e.x,e.y),1)) def onEnter(foo): ‘User hit the [Enter] key’ sendMsg(chr(CMD_MSG)+entry.get()) entry.delete(0,END) # Clear the entry widget def setup(root): ‘Creates the user interface’ global msgs,entry,canvas # The big window holding everybody’s messages msgs = Text(root,width=60,height=20) msgs.grid(row=0,col=0,columnspan=3) # Hook up a scrollbar to see old messages s = Scrollbar(root,orient=VERTICAL) s.config(command=msgs.yview) msgs.config(yscrollcommand=s.set) s.grid(row=0,col=3,sticky=N+S) # Where you type your message entry = Entry(root) entry.grid(row=1,col=0,columnspan=2,sticky=W+E) entry.bind(‘<Return>’,onEnter) entry.focus_set() b = Button(root,text=’Quit’,command=onQuit) b.grid(row=1,col=2) # A place to draw canvas = Canvas(root,bg=’White’) canvas.grid(row=0,col=5) # Notify me of button press and release messages 4807-7 ch15.F 5/24/01 8:59 AM Page 259 Chapter 15 ✦ Networking canvas.bind(‘<ButtonPress-1>’,onBDown) canvas.bind(‘<ButtonRelease-1>’,onBUp) def msgThread(addr,port,name): ‘Listens for and processes messages’ # Create a listen socket s = socket(AF_INET, SOCK_DGRAM) s.setsockopt(SOL_SOCKET,SO_REUSEADDR,1) s.bind((‘’,port)) # Join the multicast group s.setsockopt(SOL_IP,IP_ADD_MEMBERSHIP,\ inet_aton(addr)+inet_aton(‘’)) while 1: # Get a msg and strip off the command byte msg,msgFrom = s.recvfrom(2048) cmd,msg = ord(msg[0]),msg[1:] if cmd == CMD_JOINED: # New join msgs.insert(END,’(%s joined the chat)\n’ % msg) # Introduce myself sendMsg(chr(CMD_JOINRESP)+ \ cPickle.dumps((name,myColor),1)) elif cmd == CMD_LEFT: # Somebody left who = people[msgFrom][0] if who == name: # Hey, _I_ left, better quit break msgs.insert(END,’(%s left the chat)\n’ % \ who,’color_’+who) elif cmd == CMD_MSG: # New message to display who = people[msgFrom][0] msgs.insert(END,who,’color_%s’ % who) msgs.insert(END,’: %s\n’ % msg) elif cmd == CMD_LINE: # Draw a line dx,dy,ex,ey = cPickle.loads(msg) canvas.create_line(dx,dy,ex,ey,width=2,\ fill=people[msgFrom][1]) elif cmd == CMD_JOINRESP: # Introducing themselves people[msgFrom] = cPickle.loads(msg) who,color = people[msgFrom] # Create a tag to draw text in their color msgs.tag_configure(‘color_’ + who,foreground=color) Continued 259 4807-7 ch15.F 260 5/24/01 8:59 AM Page 260 Part III ✦ Networking and the Internet Listing 15-1 (continued) # Leave the multicast group s.setsockopt(SOL_IP,IP_DROP_MEMBERSHIP,\ inet_aton(addr)+inet_aton(‘’)) if __name__ == ‘__main__’: argv = sys.argv if len(argv) < 3: print ‘Usage:’,argv[0],’<name> <color> ‘\ ‘[addr=<multicast address>] [port=<port>]’ sys.exit(1) global name, addr, port, myColor addr = ‘235.0.50.5’ # Default IP address port = 54321 # Default port name,myColor = argv[1:3] for arg in argv[3:]: if arg.startswith(‘addr=’): addr = arg[len(‘addr=’):] elif arg.startswith(‘port=’): port = int(arg[len(‘port=’):]) # Start up a thread to process messages threading.Thread(target=msgThread,\ args=(addr,port,name)).start() # This is the socket over which we send out messages global sendSock sendSock = socket(AF_INET,SOCK_DGRAM) sendSock.setsockopt(SOL_SOCKET,SO_REUSEADDR,1) sendSock.connect((addr,port)) # Don’t let the packets die too soon sendSock.setsockopt(SOL_IP,IP_MULTICAST_TTL,2) # Create a Tk window and create the GUI root = Tk() root.title(‘%s chatting on channel %s:%d’ % \ (name,addr,port)) setup(root) # Join the chat! sendMsg(chr(CMD_JOINED)+name) root.mainloop() Note Although this application will work on a local network, it may have trouble working between computers on the Internet. Some routers are configured to ignore multicast data packets, and the time-to-live (TTL) setting for the packets must be high enough to make the necessary number of hops between each computer. 4807-7 ch15.F 5/24/01 8:59 AM Page 261 Chapter 15 ✦ Networking As with most Python programs, this one packs a lot of punch in very few lines of code (it weighs in at about 120 lines, ignoring comments). The first thing to note is the msgThread function, which creates a socket to listen for incoming multicast messages. It uses the SO_REUSEADDR socket option to enable you to run multiple copies on one computer (otherwise, bind would complain that someone else was already bound to that address and port). It also uses IP_ADD_MEMBERSHIP to join a multicast group, and IP_DROP_MEMBERSHIP to leave it. The first byte of each message is a predefined command character, which msgThread uses to determine what to do with the message. When you type a message into the text entry box at the bottom of the dialog box, onEnter sends the text from the entry box to the multicast channel. Likewise, pressing the left mouse button, dragging a line, and releasing it causes onBUp to send the message to draw a new line. Note that neither of these actually displays a message or draws a line — they just send a message to the multicast group, and all running copies, including the one that originated the message, receive the message and process it. The socket that sends these messages doesn’t need to join the multicast group; anyone can send to a group, but only members can receive messages. When msgThread calls recvFrom to get a new message, it also gets the IP address and port of the sender. The program uses this tuple as a dictionary key to map to the name and color of the sender (each line is drawn in the sender’s color, as is that user’s name when they send a text message). One final thing to note is how the listening thread decides when to shut down. When you click the Quit button, the application notifies everyone that you are leaving the chat group. Your listener also hears this message, and recognizing that the sender is itself, it stops waiting for more messages. Using SocketServers The SocketServer module defines a base class for a group of socket server classes — classes that wrap up and hide the details of listening for, accepting, and handling incoming socket connections. The SocketServer family TCPServer and UDPServer are SocketServer subclasses that handle TCP and UDP messages, respectively. Note SocketServer also provides UnixStreamServer (a child class of TCPServer) and UnixDatagramServer (a child of UDPServer), which are the same as their parent classes except that the listening socket is created with a family of AF_UNIX instead of AF_INET. 261 4807-7 ch15.F 262 5/24/01 8:59 AM Page 262 Part III ✦ Networking and the Internet By default, the socket servers handle connections one at a time, but you can use the ThreadingMixIn and ForkingMixIn classes to create threading or forking versions of any SocketServer. In fact, the SocketServer module helpfully provides the following classes to save you the trouble: ForkingUDPServer, ForkingTCPServer, ThreadingUDPServer, ThreadingTCPServer, ThreadingUnixStreamServer, and ThreadingUnixDatagramServer. Obviously, the threading versions work only on platforms that support threads, and the forking versions work on platforms that support os.fork. CrossReference See Chapter 7 for an overview of mix-in classes, Chapter 11 for forking, and Chapter 26 for threads. SocketServers handle incoming connections in a generic way; to make them useful, you provide your own request handler class to which it passes a socket to handle. The BaseRequestHandler class in the SocketServer module is the parent class of all request handlers. Suppose, for example, that you need to write a multithreaded e-mail server. First you create MailRequestHandler, a subclass of BaseRequestHandler, and then you pass it to a newly created SocketServer: import SocketServer ... # Create your MailRequestHandler class here addr = (‘175.15.30.2’, 25) # Listen address and port server = SocketServer.ThreadingTCPServer(addr, MailRequestHandler) server.serve_forever() Each time a new connection comes in, the server creates a new MailRequestHandler instance object and calls its handle() method so it can process the new request. Because the server is derived from ThreadingTCPServer, with each new request it starts a separate thread to handle the request, so that multiple requests will be processed simultaneously. Instead of calling server_forever, you can also call handle_request(), which waits for, accepts, and processes a single connection. server_forever merely calls handle_request in an infinite loop. Don’t worry too much about the details of the request handler just yet; the next section covers everything you need to know. Normally, you can use one of the socket servers as is, but if you need to create your own subclass, you can override any of the following methods to customize it. When the server is first created, the __init__ function calls the server_bind() method to bind the listen socket (self.socket) to the correct address (self.server_address). It then calls server_activate() to activate the server (by default, this calls the listen method of the socket). The socket server doesn’t do anything until the user calls either of the handle_request or serve_forever methods. handle_request calls get_request() to wait for and accept a new socket connection, and then calls 4807-7 ch15.F 5/24/01 8:59 AM Page 263 Chapter 15 ✦ Networking verify_request(request, client_address) to see if the server should process the connection (you can use this for access control — by default, verify_request always returns true). If it’s okay to process the request, handle_request then calls process_request(request, client_address), and then handle_error(request, client_address) if process_request raised an exception. By default, process_request simply calls finish_request(request, client_address); the forking and threading mix-in classes override this behavior to start a new process or thread, and then call finish_request. finish_request instantiates a new request handler, which in turn calls its handle() method. If you want to subclass a SocketServer, trace through this sequence of calls once or twice to make sure it makes sense to you, and review the source code of SocketServer for help. When a SocketServer creates a new request handler, it passes to the handler’s __init__ function the self variable, so that the handler can access information about the server. The SocketServer’s fileno() method returns the file descriptor of the listen socket. The address_family member variable specifies the socket family of the listen socket (for example, AF_INET), and server_address holds the address to which the listen socket is bound. The socket variable holds the listen socket itself. Request handlers Request handlers have setup(), handle(), and finish() methods (none of which do anything by default) that you can override to add your custom behavior. Normally, you need to override only the handle method. The BaseRequestHandler’s __init__ function calls setup() for initialization work, handle() to service the request, and finish() to perform any cleanup, although finish isn’t called if handle or setup raise an exception. Keep in mind that a new instance of your request handler is created for each request. The request member variable has the newly accepted socket for stream (TCP) servers; for datagram (UDP) servers, it is a tuple containing the incoming message and the listen socket. client_address holds the address of the sender, and server has a reference to the SocketServer (through which you can access its members, such as server_address). The following example implements EchoRequestHandler, a handler that repeats back to the remote side any data it sends: >>> import SocketServer >>> class EchoRequestHandler(SocketServer.BaseRequestHandler): ... def handle(self): ... print ‘Got new connection!’ ... while 1: ... msg = self.request.recv(1024) ... if not msg: ... break 263 4807-7 ch15.F 264 5/24/01 8:59 AM Page 264 Part III ✦ Networking and the Internet ... print ‘ Received :’,msg ... self.request.send(msg) ... print ‘Done with connection’ >>> server = SocketServer.ThreadingTCPServer(\ ... (‘127.0.0.1’,12321),EchoRequestHandler) >>> server.handle_request() # It’ll wait here for a connection Got new connection! Received : Hello! Received : I like Tuesdays! Done with connection In another Python interpreter, you can connect to the server and try it out: >>> from socket import * >>> s = socket(AF_INET,SOCK_STREAM) >>> s.connect((‘127.0.0.1’,12321)) >>> s.send(‘Hello!’) 6 >>> print s.recv(1024) Hello! >>> s.send(‘I like Tuesdays!’) 16 >>> print s.recv(1024) I like Tuesdays! >>> s.close() The SocketServer module also defines two subclasses of BaseRequestHandler: StreamRequestHandler and DatagramRequestHandler. These override the setup and finish methods and create two file objects, rfile and wfile, that you can use for reading and writing data to the client, instead of using the usual socket methods. Processing Web Browser Requests Now that you have a SocketServer, what do you do with it? Why, extend it, of course! The standard Python library comes with BaseHTTPServer, SimpleHTTPServer, and CGIHTTPServer modules that implement increasingly complex Web server request handlers. Most likely, you would use them as starting points on which to build, but to some extent they do work on their own as well. For example, how many lines does it take to implement a multithreaded Web server that supports running CGI scripts? Well, at a bare minimum, it takes the following: import SocketServer,CGIHTTPServer SocketServer.ThreadingTCPServer((‘127.0.0.1’,80),\ CGIHTTPServer.CGIHTTPRequestHandler).serve_forever() Point your Web browser to http://127.0.0.1/file (where file is the name of some text file in your current directory) and verify that it really does work. 4807-7 ch15.F 5/24/01 8:59 AM Page 265 Chapter 15 ✦ Networking BaseHTTPRequestHandler The starting class for a Web server request handler is BaseHTTPRequestHandler (in the BaseHTTPServer module), a child of StreamRequestHandler. This class accepts an HTTP connection (usually from a Web browser), reads and extracts the headers, and calls the appropriate method to handle the request. Subclasses of BaseHTTPRequestHandler should not override the __init__ or handle methods, but should instead implement a method for each HTTP command they need to handle. For each HTTP command (GET, POST, and so on), BaseHTTPRequestHandler calls its do_<command> method, if present. For example, if your subclass needs to support the HTTP PUT command, just add a do_PUT() method to your subclass and it will automatically be called for any HTTP PUT requests. The request handler stores the original request line in its raw_request instance variable, and its parts in command (GET, POST, and so on), path (for example, / index.html), and request_version (for example, HTTP/1.0). headers is an instance of mimetools.Message, and contains the parsed version of the request headers. CrossReference See Chapter 17 for more information about the mimetools.Message class. Alternatively, you can specify a different class to use for reading and parsing the headers by changing the value of the BaseHTTPRequestHandler. MessageClass class variable. Use the rfile and wfile objects to read and write data. If the request has additional data beyond the request headers, rfile will be positioned at the beginning of that data by the time the handler calls the appropriate do_<command> method. BaseHTTPRequestHandler uses the value in server_version when writing out a Server response header; you can customize this from its default of BaseHTTP/0.x. Additionally, the protocol_version variable defaults to HTTP/1.0, but you can set it to a different version if needed. In your do_<command> method, the first output you send should be via the send_response(code[, message]) method, where code is an HTTP code (such as 200) and message is an optional text message explaining the code. (If the request is invalid, you can instead call send_error(code[, message]), and then return from the command method.) When you call send_response, BaseHTTPRequestHandler adds in Date and Server headers. After a call to send_response, you can call send_header(key, value) as needed to write out MIME headers; call end_headers() when you’re done: def do_GET(self): self.send_response(200) self.send_header(‘Content-type’,’text/html’) self.send_header(‘Content-length’,len(data)) self.end_headers() # send the rest of the data 265 4807-7 ch15.F 266 5/24/01 8:59 AM Page 266 Part III ✦ Networking and the Internet Most Web servers generate logs for later analysis. Call the log_request([code[, size]]) method to log a successful request (including the size, if known, makes the logs more useful). log_message(format, arg0, arg1, ...) is a general-purpose logging method; the format and arguments are similar to normal Python string formatting: self.log_message(‘%s : %d’, ‘Time taken’,425) Each request is automatically logged to stdout using the NCSA httpd logging format. SimpleHTTPRequestHandler Whereas the BaseHTTPRequestHandler doesn’t actually handle any HTTP commands, SimpleHTTPRequestHandler (in the SimpleHTTPServer module) adds support for both HEAD and GET commands by sending back to the client requested files that reside in the current working directory or any of its subdirectories. If the requested file is actually a directory, SimpleHTTPRequestHandler generates, on the fly, a Web page containing a directory listing; and sends it back to the client. Try the following example to see this in action. This code starts a Web server on port 8000, and then opens a Web browser and begins browsing in the current working directory. Because the server continuously loops to serve requests, the example starts the server on a separate thread so you can still launch a Web browser: >>> import Webbrowser,threading,SimpleHTTPServer >>> def go(): ... t = SimpleHTTPServer.test ... threading.Thread(target=t).start() ... Webbrowser.open(‘http://127.0.0.1:8000’) >>> go() # Below is the output after browsing around a little Serving HTTP on port 8000 ... endor - - [28/Dec/2000 18:00:48] “GET /3dsmax3/ HTTP/1.1” 200 endor - - [28/Dec/2000 18:00:50] “GET /3dsmax3/Maxsdk/ HTTP/1.1” 200 endor - - [28/Dec/2000 18:00:53] “GET /3dsmax3/Maxsdk/Include/ HTTP/1.1” 200 - The test() function in the SimpleHTTPServer module simply starts a new server on port 8000. In addition to the variables inherited from BaseHTTPRequestHandler, this class has an extensions_map dictionary that maps file extensions to MIME data types, so that the user’s Web browser will correctly handle the file it receives. You can expand this list to add new types you want to support. 4807-7 ch15.F 5/24/01 8:59 AM Page 267 Chapter 15 ✦ Networking CGIHTTPRequestHandler The CGIHTTPRequestHandler (in the CGIHTTPServer module) takes SimpleHTTPRequestHandler one step further and adds support for executing CGI scripts. The CGI (Common Gateway Interface) is a standard for executing server-side programs that can process input from the user’s browser (saving data they entered in an HTML form, for example). Caution Before you ever make a Web server open to public use, take the time to learn about what security risks are involved. This warning is doubly strong for modules such as CGIHTTPRequestHandler that can execute arbitrary Python code; even the smallest security hole is an invitation for intruders. For each GET or POST command that comes in, CGIHTTPRequestHandler checks whether the specified file is actually a CGI program and, if so, launches it as an external program. If it is not, the file contents are sent back to the browser normally. Note that the POST method is supported for CGI programs only. To decide if a file is a valid CGI program, CGIHTTPRequestHandler checks the file’s path against the cgi_directories member list, which, by default, contains the directories /cgi-bin and htbin (you can add other directories if you want). If the file is in one of those directories or any of their subdirectories and is either a Python module or an executable file, the file is executed and its output returned to the client. Example: form handler CGI script The example in this section shows CGIHTTPRequestHandler at work. Follow these steps to try it out: 1. Listing 15-2 is a tiny HTML form that asks you to enter your name. Save the file to disk (anywhere you want) as form.html. I saved it to c:\temp, so in the following steps, replace c:\temp with the directory you chose. 2. In the same directory, create a subdirectory called cgi-bin: md c:\temp\cgi-bin (from an MS-DOS prompt) 3. Listing 15-3 is a small CGI script; save it to your new cgi-bin directory as handleForm.py. 4. Switch to your original directory (c:\temp), start up a Python interpreter, and enter the following lines to start a Web server: >>> import CGIHTTPServer >>> CGIHTTPServer.test() 5. Open a Web browser and point it to http://127.0.0.1:8000/form.html to display the simple Web page shown in Figure 15-2. 267 4807-7 ch15.F 268 5/24/01 8:59 AM Page 268 Part III ✦ Networking and the Internet Figure 15-2: The Python Web server returned this page; clicking Go executes the CGI script. 6. Enter your name in the text box and click Go. The Web server executes the Python CGI script and displays the results shown in Figure 15-3. Figure 15-3: The Python Web server ran the CGI script and returned the results. 4807-7 ch15.F 5/24/01 8:59 AM Page 269 Chapter 15 ✦ Networking Listing 15-2: form.html – A simple HTML form <html><body> <form method=GET action=”http://127.0.0.1:8000/cgi-bin/handleForm.py”> Your name:<input name=”User”> <input type=”Submit” value=”Go!”> </form> </body></html> Listing 15-3: handleForm.py – A Python CGI script import os print “Content-type: text/html\r\n<html><body>” name = os.environ.get(‘QUERY_STRING’,’’) print ‘Hello, %s!<p>’ % name[len(‘User=’):] print ‘</body></html>’ To make use of this functionality, you should read up on CGI (which is certainly not specific to Python). Although a complete discussion is outside the scope of this chapter, the following few hints will help get you started: ✦ CGIHTTPRequestHandler stores the user information (including form values) in environment variables. (Write a simple CGI script to print out all variables and their values to test this.) ✦ Anything you write to stdout (via print or sys.stdout.write) is returned to the client, and it can be text or binary data. ✦ CGIHTTPRequestHandler outputs some response headers for you, but you can add others if needed (such as the Content-type header in the example). ✦ After the headers, you must output a blank line before any data. ✦ On UNIX, external programs run with the nobody user ID. Handling Multiple Requests Without Threads Although threads can help the Web servers in the previous sections handle more than one connection simultaneously, the program usually sits around waiting for data to be transmitted across the network. (Instead of being CPU bound, the program is said to be I/O bound.) In situations where your program is I/O bound, a lot 269 4807-7 ch15.F 270 5/24/01 8:59 AM Page 270 Part III ✦ Networking and the Internet of CPU time is wasted switching between threads that are just waiting until they can read or write more data to a file or socket. In such cases, it may be better to use the select and asyncore modules. These modules still let you process multiple requests at a time, but avoid all the senseless thread switching. The select(inList, outList, errList[, timeout]) function in the select module takes three lists of objects that are waiting to perform input or output (or want to be notified of errors). select returns three lists, subsets of the originals, containing only those objects that can now perform I/O without blocking. If the timeout parameter is given (a floating-point number indicating the number of seconds to wait) and is non-zero, select returns when an object can perform I/O or when the time limit is reached (whereupon empty lists are returned). A timeout value of 0 does a quick check without blocking. The three lists hold input, output, and error objects, respectively (objects that are interested in reading data, writing data, or in being notified of errors that occurred). Any of the three lists can be empty, and the objects can be integer file descriptors or filelike objects with a fileno() method that returns a valid file descriptor. CrossReference See “Working with File Descriptors” in Chapter 10 for more information. By using select, you can start several read or write operations and, instead of blocking until you can read or write more, you can continue to do other work. This way, your I/O-bound program spends as much time as possible being driven by its performance-limiting factor (I/O), instead of a more artificial factor (switching between threads). With select, it is possible to write reasonably high-performance servers in Python. Note On Windows systems, select() works on socket objects only. On UNIX systems, however, it also works on other file descriptors, such as named pipes. A slightly more efficient alternative to select is the select.poll() function, which returns a polling object (available on UNIX platforms). After you create a polling object, you call the register(fd[, eventmask]) method to register a particular file descriptor (or object with a fileno() method). The optional eventmask is constructed by bitwise OR-ing together any of the following: select.POLLIN (for input), select.POLLPRI (urgent input), select.POLLOUT (for output), or select.POLLERR. You can register as many file descriptors as needed, and you can remove them from the object by calling the polling object’s unregister(fd) method. Call the polling object’s poll([timeout]) method to see which file descriptors, if any, are ready to perform I/O without blocking. poll returns a possibly empty list of tuples of the form (fd, event), an entry for each file descriptor whose state has changed. The event will be a bitwise-OR of any of the eventmask flags as well as POLLHUP (hang up) or POLLNVAL (an invalid file descriptor). 4807-7 ch15.F 5/24/01 8:59 AM Page 271 Chapter 15 ✦ Networking asyncore If you’ve never used select or poll before, it may seem complicated or confusing. To help in creating select-based socket clients and servers, the asyncore module takes care of a lot of the dirty work for you. asyncore defines the dispatcher class, a wrapper around a normal socket object that you subclass to handle messages about when the socket can be read or written without blocking. Because it is a wrapper around a socket, you can often treat a dispatcher object like a normal socket (it has the usual connect(addr), send(data), recv(bufsize), listen([backlog]), bind(addr), accept(), and close() methods). Although the dispatcher is a wrapper around a socket, you still need to create the underlying socket (either the caller needs to or you can create it in the dispatcher’s constructor) by calling the create_socket(family, type) method: d = myDispatcher() d.create_socket(AF_INET,SOCK_STREAM) create_socket creates the socket and sets it to nonblocking mode. asyncore calls methods of a dispatcher object when different events occur. When the socket can be written to without blocking, for example, the handle_write() method is called. When data is available for reading, handle_read() is called. You can also implement handle_connect() for when a socket connects successfully, handle_close() for when it closes, and handle_accept() for when a call to socket.accept will not block (because an incoming connection is available and waiting). asyncore calls the readable() and writable() methods of the dispatcher object to see if it is interested in reading or writing data, respectively (by default, both methods always return 1). You can override these so that, for example, asyncore doesn’t waste time checking for data if you’re not even trying to read any. In order for asyncore to fire events off to any dispatcher objects, you need to call asyncore.poll([timeout]) (on UNIX, you can also call asyncore.poll2 ([timeout]) to use poll instead of select) or asyncore.loop([timeout]). These functions use the select module to check for a change in I/O state and then fire off the appropriate events to the corresponding dispatcher objects. poll checks once (with a default timeout of 0 seconds), but loop checks until there are no more dispatcher objects that return true for either readable or writable, or until the timeout is reached (a default of 30 seconds). The best way to absorb all this is by looking at an example. Listing 15-4 is a very simple asynchronous Web page retrieval class that retrieves the index.html page from a Web site and writes it to disk (including the Web server’s response headers). 271 4807-7 ch15.F 272 5/24/01 8:59 AM Page 272 Part III ✦ Networking and the Internet Listing 15-4: asyncget.py – Asynchronous HTML page retriever import asyncore, socket class AsyncGet(asyncore.dispatcher): def __init__(self, host): asyncore.dispatcher.__init__(self) self.host = host self.create_socket(socket.AF_INET, socket.SOCK_STREAM) self.connect((host,80)) self.request = ‘GET /index.html HTTP/1.0\r\n\r\n’ self.outf = None print ‘Requesting index.html from’,host def handle_connect(self): print ‘Connect’,self.host def handle_read(self): if not self.outf: print ‘Creating’,self.host self.outf = open(self.host,’wt’) data = self.recv(8192) if data: self.outf.write(data) def writeable(self): return len(self.request) > 0 def handle_write(self): # Not all data might be sent, so track what did make it num_sent = self.send(self.request) self.request = self.request[num_sent:] def handle_close(self): asyncore.dispatcher.close(self) print ‘Socket closed for’,self.host if self.outf: self.outf.close() # Now retrieve some pages AsyncGet(‘www.yahoo.com’) AsyncGet(‘www.cnn.com’) AsyncGet(‘www.python.org’) asyncore.loop() # Wait until all are done 4807-7 ch15.F 5/24/01 8:59 AM Page 273 Chapter 15 ✦ Networking Here’s some sample output: C:\temp>asyncget.py Requesting index.html from www.yahoo.com Requesting index.html from www.cnn.com Requesting index.html from www.python.org Connect www.yahoo.com Connect www.cnn.com Creating www.yahoo.com Connect www.python.org Creating www.cnn.com Creating www.python.org Socket closed for www.yahoo.com Socket closed for www.python.org Socket closed for www.cnn.com Notice that the requests did not all finish in the same order they were started. Rather, they each made progress according to when data was available. By being event-driven, the I/O-bound program spends most of its time working on its greatest performance boundary (I/O), instead of wasting time with needless thread switching. Summary If you’ve done any networking programming in some other languages, you’ll find that doing the same thing in Python can be done with a lot less effort and bugs. Python has full support for standard networking functionality, as well as utility classes that do much of the work for you. In this chapter, you: ✦ Converted IP addresses to registered names and back. ✦ Created sockets and sent messages between them. ✦ Used SocketServers to quickly build custom servers. ✦ Built a working Web server in only a few lines of Python code. ✦ Used select to process multiple socket requests without threads. The next chapter looks at more of Python’s higher-level support for Internet protocols, including modules that hide the nasty details of “speaking” protocols such as HTTP, FTP, and telnet. ✦ ✦ ✦ 273 4807-7 ch15.F 5/24/01 8:59 AM Page 274 4807-7 ch16.F 5/24/01 8:59 AM Page 275 16 CHAPTER Speaking Internet Protocols O n the Internet, people use various protocols to transfer files, send e-mail, and request resources from the World Wide Web. Python provides libraries to help work with Internet protocols. This chapter shows how you can write Internet programs without having to handle lower-level TCP/IP details such as sockets. Supported protocols include HTTP, POP3, SMTP, FTP, and Telnet. Python also provides useful CGI scripting abilities. ✦ ✦ ✦ ✦ In This Chapter Python’s Internet protocol support Retrieving Internet resources Sending HTTP requests Sending and receiving e-mail Transferring files via FTP Python’s Internet Protocol Support Python’s standard libraries make it easy to use standard Internet protocols such as HTTP, FTP, and Telnet. These libraries are built on top of the socket library, and enable you to program networked programs with a minimum of low-level code. Each Internet protocol is documented in a numbered request for comment (RFC). The name is a bit misleading for established protocols such as POP and FTP, as these protocols are widely implemented, and are no longer under much discussion! These protocols are quite feature-rich — the RFCs for the protocols discussed here would fill several hundred printed pages. The standard Python modules provide a high-level client for each protocol. However, you may need to know more about the protocols’ syntax and meaning, and the RFCs are the best place to learn this information. One good online RFC repository is at http://www.rfc-editor.org/. CrossReference Refer to Chapter 15 for more information about the socket module and a quick overview of TCP/IP. Retrieving resources using Gopher Working with newsgroups Using the Telnet protocol Writing CGI scripts ✦ ✦ ✦ ✦ 4807-7 ch16.F 276 5/24/01 8:59 AM Page 276 Part III ✦ Networking and the Internet Retrieving Internet Resources The library urllib provides an easy mechanism for grabbing files from the Internet. It supports HTTP, FTP, and Gopher requests. Resource requests can take a long time to complete, so you may want to keep them out of the main thread in an interactive program. The simplest way to retrieve a URL is with one line: urlretrieve(url[,filename[,callback[,data]]]) The function urlretrieve retrieves the resource located at the address url and writes it to a file with name filename. For example: >>> MyURL=”http://www.pythonapocrypha.com” >>> urllib.urlretrieve(MyURL, “pample2.swf”) >>> urllib.urlcleanup() # clean the cache! If you do not pass a filename to urlretrieve, a temporary filename will be magically generated for you. The function urlcleanup frees up resources used in calls to urlretrieve. The optional parameter callback is a function to call after retrieving each block of a file. For example, you could use a callback function to update a progress bar showing download progress. The callback receives three arguments: the number of blocks already transferred, the size of each block (in bytes), and the total size of the file (in bytes). Some FTP servers do not return a file size; in this case, the third parameter is -1. Normally, HTTP requests are sent as GET requests. To send a POST request, pass a value for the optional parameter data. This string should be encoded using urlencode. To use a proxy on Windows or UNIX, set the environment variables http_proxy, ftp_proxy, and/or gopher_proxy to the URL of the proxy server. On a Macintosh, proxy information from Internet Config is used. Manipulating URLs Special characters are encoded in URLs to ensure they can be passed around easily. Encoded characters take the form %##, where ## is the ASCII value of the character in hexadecimal. Use the function quote to encode a string, and unquote to translate it back to normal, human-readable form: >>> print urllib.quote(“human:nature”) human%3anature >>> print urllib.unquote(“cello%23music”) cello#music 4807-7 ch16.F 5/24/01 8:59 AM Page 277 Chapter 16 ✦ Speaking Internet Protocols The function quote_plus does the encoding of quote, but also replaces spaces with plus signs, as required for form values. The corresponding function unquote_plus decodes such a string: >>> print urllib.quote_plus(“bob+alice forever”) bob%2balice+forever >>> print urllib.unquote_plus(“where+are+my+keys?”) where are my keys? Data for an HTTP POST request must be encoded in this way. The function urlencode takes a dictionary of names and values, and returns a properly encoded string, suitable for HTTP requests: >>> print urllib.urlencode( {“name”:”Eric”,”species”:”sea bass”}) species=sea+bass&name=Eric CrossReference See the module urlparse, covered in Chapter 17, for more functions to parse and process URLs. Treating a URL as a file The function urlopen(url[,data]) creates and returns a filelike object for the corresponding address url. The source can be read like an ordinary file. For example, the following code reads a Web page and checks the length of the file (the full HTML text of the page): >>> Page=urllib.urlopen(“http://www.python.org”) >>> print len(Page.read()) 339 The data parameter, as for urlretrieve, is used to pass urlencoded data for a POST request. The filelike object returned by urlopen provides two bonus methods. The method geturl returns the real URL — usually the same as the URL you passed in, but possibly different if a Web page redirected you to another URL. The method info returns a mimetools.Message object describing the file. CrossReference Refer to Chapter 17 for more information about mimetools. URLopeners The classes URLopener and FancyURLopener are what you actually build and use with calls to urlopen and urlretrieve. You may want to subclass them to handle new addressing schemes. You will probably always use FancyURLopener. It is a 277 4807-7 ch16.F 278 5/24/01 8:59 AM Page 278 Part III ✦ Networking and the Internet subclass of URLopener that handles HTTP redirections (response code 301 and 302) and basic authentication (response code 401). The opener constructor takes, as its first argument, a mapping of schemes (such as HTTP) to proxies. It also takes the keyword arguments key_file and cert_file, which, if supplied, allow you to request secure Web pages (using the HTTPS scheme). Note The default Python build does not currently include SSL support. You must edit Modules/Setup to include SSL, and then rebuild Python, in order to open https:// addresses with urllib. Openers provide a method, open(url[,data]), that opens the resource with address url. The data parameter works as in urllib.urlopen. To open new url types, override the method open_unknown(url[,data]) in your subclass. By default, this method returns an “unknown url type” IOError. Openers also provide a method retrieve(url[,filename[,hook[,data]]]), which functions like urllib.urlretrieve. The HTTP header user-agent identifies a piece of client software to a Web server. Normally, urllib tells the server that it is Python-urllib/1.13 (where 1.13 is the current version of urllib). If you subclass the openers, you can override this by setting the version attribute before calling the parent class’s constructor. Extended URL opening The module urllib2 is a new and improved version of urllib. urllib2 provides a wider array of features, and is easier to extend. The syntax for opening a URL is the same: urlopen(url[,data]). Here, url can be a string or a Request object. The Request class gathers HTTP request information (it is very similar to the class httplib.HTTP). Its constructor has syntax Request(url[,data[,headers]]). Here, headers must be a dictionary. After constructing a Request, you can call add_header(name,value) to send additional headers, and add_data(data) to send data for a POST request. For example: >>> # Request constructor is picky: “http://” and the >>> # trailing slash are both required here: >>> MyRequest=urllib2.Request(“http://www.python.org/”) >>> MyRequest.add_header(“user-agent”,”Testing 1 2 3”) >>> URL=urllib2.urlopen(MyRequest) >>> print URL.readline() # read just a little bit <HTML> The module urllib2 can handle some fancier HTTP requests, such as basic authentication. For further details, consult the module documentation. New Feature The module urllib2 is new in Python Version 2.1. 4807-7 ch16.F 5/24/01 8:59 AM Page 279 Chapter 16 ✦ Speaking Internet Protocols Sending HTTP Requests HyperText Transfer Protocol (HTTP) is a format for requests that a client (usually a browser) sends to a server on the World Wide Web. An HTTP request includes various headers. Headers include information such as the URL of a requested resource, file formats accepted by the client, and cookies, parameters used to cache userspecific information (see RFC 2616 for details). The httplib module lets you build and send HTTP requests and receive server responses. Normally, you retrieve Web pages using the urllib module, which is simpler. However, httplib enables you to control headers, and it can handle POST requests. Building and using request objects The module method HTTP([host[,port]]) constructs and returns an HTTP request object. The parameter host is the name of a host (such as www.yahoo.com). The port number can be passed via the port parameter, or parsed from the host name; otherwise, it defaults to 80. If you construct an HTTP object without providing a host, you must call its connect(host[,port]) method to connect to a server before sending a request. To start a Web request, call the method putrequest(action,URL). Here, action is the request method, such as GET or POST, and URL is the requested resource, such as /stuff/junk/index.html. After starting the request, you can (and usually will) send one or more headers, by calling putheader(name, value[, anothervalue,...]). Then, whether you sent headers or not, you call the endheaders method. For example, the following code informs the server that HTML files are accepted (something most Web servers will assume anyway), and then finishes off the headers: MyHTTP.putheader(‘Accept’, ‘text/html’) MyHTTP.endheaders() You can pass multiple values for a header in one call to putheader. After setting up any headers, you may (usually on a POST request) send additional data to the server by calling send(data). Now that you have built the request, you can get the server’s reply. The method getreply returns the server’s response in a 3-tuple: (replycode, message, headers). Here, replycode is the HTTP status code (200 for success, or perhaps the infamous 404 for “resource not found”). The body of the server’s reply is returned (as a file object with read and close methods) by the method getfile. This is where the request object finally receives what it asks for. 279 4807-7 ch16.F 280 5/24/01 8:59 AM Page 280 Part III ✦ Networking and the Internet For example, the following code retrieves the front page from www.yahoo.com: >>> Request=httplib.HTTP(“www.yahoo.com”) >>> Request.putrequest(“GET”,”/”) >>> Request.endheaders() >>> Request.getreply() (200, ‘OK’, <mimetools.Message instance at 0085EBD4>) >>> ThePage=Request.getfile() >>> print ThePage.readline()[:50] <html><head><title>Yahoo!</title><base href=http:/ This example performs a Web search by sending a POST request. Data in a POST request must be properly encoded using urllib.urlencode (see Listing 16-1). This code uses an HTMLParser (from htmllib) to extract all links from the search results. CrossReference See Chapter 18 for complete information about htmllib. Listing 16-1: WebSearch.py import httplib import htmllib import urllib import formatter # Encode our search terms as a URL, by # passing a dictionary to urlencode SearchDict={“q”:”Charles Dikkins”, “kl”:”XX”,”pg”:”q”,”Translate”:”on”} SearchString=urllib.urlencode(SearchDict) print “search:”,SearchString Request=httplib.HTTP(“www.altavista.com”) Request.putrequest(“POST”,”/cgi-bin/query”) Request.putheader(‘Accept’, ‘text/plain’) Request.putheader(‘Accept’, ‘text/html’) Request.putheader(‘Host’, ‘www.alta-vista.com’) Request.putheader(“Content-length”,len(SearchString)) Request.endheaders() Request.send(SearchString) print Request.getreply() # Read and parse the resulting HTML HTML=Request.getfile().read() MyParser=htmllib.HTMLParser(formatter.NullFormatter()) MyParser.feed(HTML) # Print all the anchors from the results page print MyParser.anchorlist 4807-7 ch16.F 5/24/01 8:59 AM Page 281 Chapter 16 ✦ Speaking Internet Protocols Sending and Receiving E-Mail Python provides libraries that receive mail from, and send mail to, a mail server. Electronic mail is transmitted via various protocols. The most common mail protocols are POP3 (for receiving mail), SMTP (for sending mail), and IMAP4 (for reading mail and managing mail folders). They are supported by the Python modules poplib, smtplib, and imaplib, respectively. Accessing POP3 accounts To access a POP3 mail account, you construct a POP3 object. The POP3 object offers various methods to send and retrieve mail. It raises the exception poplib.error_proto if it encounters problems. See RFC 1939 for the full POP3 protocol. Many of its methods return output as a 3-tuple: a server response string, response lines (as a list), and total response length (in bytes). In general, you can access the second tuple element and ignore the others. Connecting and logging in The POP3 constructor takes two arguments: host and port number. The port parameter is optional, and defaults to 110. For example: Mailbox=poplib.POP3(“mail.gianth.com”) # connect to mail server After connecting, you can access the mail server’s greeting by calling getwelcome. You normally sign in by calling user(name) and then pass(password). To sign on using APOP authentication, call apop(username, secret). To sign in using RPOP, call rpop(username). (Currently, rpop is not supported.) Once you log in, the mailbox is locked until you call quit (or the session times out). To keep a session from timing out, you can call the method noop, which simply keeps the session alive. Checking mail The method stat checks the mailbox’s status. It returns a tuple of two numbers: the number of messages and the total size of your messages (in bytes). The method list([index]) lists the messages in your inbox. It returns a 3-tuple, where the second element is a list of message entries. A message entry is the message number, followed by its size in bytes. Passing a message index to list makes it return just that message’s entry: >>> Mailbox.list() (‘+OK 2 messages (10012 octets)’, [‘1 9003’, ‘2 1009’], 16) >>> Mailbox.list(2) +OK 2 1009 281 4807-7 ch16.F 282 5/24/01 8:59 AM Page 282 Part III ✦ Networking and the Internet The method uidl([index]) retrieves unique identifiers for the messages in a mailbox. Unique identifiers are unchanged by the addition and deletion of messages, and they are unique across sessions. The method returns a list of message indexes and corresponding unique IDs: >>> Mailbox.uidl() (‘+OK 2 messages (10012 octets)’, [‘1 2’, ‘2 3’], 10) >>> Mailbox.uidl(2) +OK 2 3 Retrieving mail The method retr(index) retrieves and returns message number index from your mailbox. What you get back is actually a tuple: the server response, a list of message lines (including headers), and the total response length (in bytes). To retrieve part of a message, call the method top(index, lines) — top is the same as retr, but stops after lines lines. Deleting mail Use the method dele(index) to delete message number index. If you change your mind, use the method rset to cancel all deletions you have done in the current session. Signing off When you finish accessing a mailbox, call the quit method to sign off. Example: retrieving mail The code in Listing 16-2 signs on to a mail server and retrieves the full text of the first message in the mailbox. It does no fancy error handling. It strips off all the message headers, printing only the body of the message. Listing 16-2: popmail.py import poplib # Replace server, user, and password with your # mail server, user name, and password! Mailbox=poplib.POP3(“mail.seanbaby.com”) Mailbox.user(“dumplechan@seanbaby.com”) Mailbox.pass_(“secretpassword”) MyMessage=Mailbox.retr(1) FullText=”” # Build up the message body in FullText PastHeaders=0 4807-7 ch16.F 5/24/01 8:59 AM Page 283 Chapter 16 ✦ Speaking Internet Protocols for MessageLine in MyMessage[1]: if PastHeaders==0: # A blank line marks the end of headers: if (len(MessageLine)==0): PastHeaders=1 else: FullText+=MessageLine+”\n” Mailbox.quit() print FullText Accessing SMTP accounts The module smtplib defines an object, SMTP, that you use to send mail using the Simple Mail Transport Protocol (SMTP). An enhanced version of SMTP, called ESMTP, is also supported. See RFC 821 for the SMTP protocol, and RFC 1869 for information about extensions. Connecting and disconnecting You can pass a host name and a port number to the SMTP constructor. This connects you to the server immediately. The port number defaults to 25: Outbox=smtplib.SMTP(“mail.gianth.com”) If you do not supply a host name when you construct an SMTP object, you must call its connect method, passing it a host name and (optionally) a port number. The host name can specify a port number after a colon: Outbox=smtplib.SMTP() Outbox.connect(“mail.gianth.com:25”) After you finish sending mail, you should call the quit method to close the connection. Sending mail The method sendmail(sender, recipients, message[,options, rcpt_options]) sends e-mail. The parameter sender is the message author (usually your e-mail address!). The parameter recipients is a list of addresses that should receive the message. The parameter message is the message as one long string, including all its headers. For example: >>> >>> >>> >>> >>> MyAddress=bob@myserver.com TargetAddress=”earl@otherserver.com” HeaderText=”From: “+MyAddress+”\r\n” HeaderText+=”To: “+TargetAddress+”\r\n\r\n” Outbox.sendmail(MyAddress,[TargetAddress],HeaderText+”Hi!”) 283 4807-7 ch16.F 284 5/24/01 8:59 AM Page 284 Part III ✦ Networking and the Internet To use extended options, pass a list of ESMTP options in the options parameter. You can pass RCPT options in the rcpt_options parameter. The method sendmail raises an exception if it could not send mail to any recipient. If at least one address succeeded, it returns a dictionary explaining any failures. In this dictionary, each key is an address. The corresponding value is a tuple: result code and error message. Other methods The method verify(address) checks an e-mail address address for validity. It returns a tuple: the first entry is the response code, the second is the server’s response string. A response code of 250 is success; anything above 400 is failure: >>> Outbox.verify(“dumplechan@seanbaby.com”) (250, ‘ok its for <dumplechan@seanbaby.com>’) >>> Outbox.verify(“dimplechin@seanbaby.com”) (550, ‘unknown user <dimplechin@seanbaby.com>’) An ESMTP server may support various extensions to SMTP, such as delivery service notification. The method has_extn(name) returns true if the server supports a particular extension: >>> Outbox.has_extn(“DSN”) # is status-notification available? 1 To identify yourself to a server, you can call helo([host]) for an SMTP server; or ehlo ([host]) for an ESMTP server. The optional parameter host defaults to the fully qualified domain name of the local host. The methods return a tuple: result code (250 for success) and server response string. Because the sendmail method can handle the HELO command, you do not normally need to call these methods directly. Handling errors Methods of an SMTP object may raise the following exceptions if they encounter an error: SMTPException Base exception class for all smtplib exceptions. SMTPServerDisconnected The server unexpectedly disconnected, or no connection has been made yet. SMTPResponseException Base class for all exceptions that include an SMTP error code. An SMTPResponseException has two attributes: smtp_code (the response code of the error, such as 550 for an invalid address) and smtp_error (the error message). SMTPSenderRefused Sender address refused. The exception attribute sender is the invalid sender. 4807-7 ch16.F 5/24/01 8:59 AM Page 285 Chapter 16 ✦ Speaking Internet Protocols SMTPRecipientsRefused All recipient addresses refused. The errors for each recipient are accessible through the attribute recipients, which is a dictionary of exactly the same sort as SMTP.sendmail() returns. SMTPDataError The SMTP server refused to accept the message data. SMTPConnectError An error occurred during establishment of a connection with the server. SMTPHeloError The server refused a “HELO” message. Accessing IMAP accounts IMAP is a protocol for accessing mail. Like POP, it enables you to read and delete messages. IMAP offers additional features, such as searching for message text and organizing messages in separate mailboxes. However, IMAP is harder to use than POP, and is far less commonly used. CrossReference See RFC 2060 for the full description of IMAP4rev1. The module imaplib provides a class, IMAP4, to serve as an IMAP client. The names of IMAP4 methods correspond to the commands of the IMAP protocol. Most methods return a tuple (code, data), where code is “OK” (good) or “NO” (bad), and data is the text of the server response. The IMAP protocol includes various magical behaviors. For example, you can move all the messages from INBOX into a new mailbox by attempting to rename INBOX. (The INBOX folder isn’t actually renamed, but its contents are moved to the other mailbox!) Not all the features of the protocol are covered here; consult RFC 2060 for more information. Connection, logon, and logoff The IMAP4 constructor takes host and port arguments, which function here just as they do for a POP3 object. If you construct an IMAP4 object without specifying a host, you must call open(host,port) to connect to a server before you can use other methods. The port number defaults to 143. To log in, call the method login(user,password). Call logout to log off. The method noop keeps an existing session alive. For example: >>> imap=imaplib.IMAP4(“mail.mundomail.net”) >>> imap.login(“dumplechan”,”tacos”) (‘OK’, [‘LOGIN completed’]) >>> imap.noop() (‘OK’, [‘NOOP completed’]) 285 4807-7 ch16.F 286 5/24/01 8:59 AM Page 286 Part III ✦ Networking and the Internet An IMAP server may use more advanced authentication methods. To authenticate in fancier ways, call the method authenticate(machanism,handler). Here, mechanism is the name of the authentication mechanism, and handler is a function that receives challenge strings from the server and returns response strings. (Base64 encoding is handled internally.) Checking, reading, and deleting mail Before you can do anything with messages, you must choose a mailbox. The mailbox INBOX is always available. To select a mailbox, call select([mailbox[, readonly]]). The parameter mailbox is the mailbox name, which defaults to INBOX. If readonly is present and true, then modifications to the mailbox are forbidden. The return value includes the number of messages in the mailbox. For example: >>> imap.select(“INBOX”) (‘OK’, [‘2’]) When finished with a mailbox, call close to close it. The method search(charset,criteria...) searches the current mailbox for messages satisfying one or more criteria. The parameter charset, if not None, specifies a particular character set to use. One or more values can be passed as criteria; these are concatenated into one search string. A list of matching message indexes is returned. Note that text (other than keywords) in criteria should be quoted. For example, the following code checks for messages from the president (none today), and then checks for messages whose subject contains “Howdy!” (and finds message number 2): >>> imap.search(None,”ALL”,”FROM”,’”president@whitehouse.gov”’) (‘OK’, [None]) >>> imap.search(None,”ALL”,”SUBJECT”,’”Howdy!”’) (‘OK’, [‘2’]) To retrieve a message, call fetch(messages,parts). Here, messages is a string listing messages, such as “2”, or “2,7”, or “3:5” (for messages 3 through 5). The parameter parts should be a parenthesized list of what parts of the message(s) to retrieve — for instance, FULL for the entire message, BODY for just the body. For example: >>> imap.fetch(“2”,”(BODY[text])”) (‘OK’, [(‘2 (BODY[text] {13}’, ‘Howdy cowboy!’), ‘)’, ‘2 (FLAGS (\\SEEN))’]) To change a message’s status, call store(messages,command,flags). Here, command is the command to perform, such as “+FLAGS” or “-FLAGS”. The parameter flags is a list of flags to set or remove. For example, the following line of code deletes message 2: >>> imap.store(“2”,”+FLAGS”,[“\Deleted”]) (‘OK’, [‘2 (FLAGS (\\SEEN \\DELETED))’]) 4807-7 ch16.F 5/24/01 8:59 AM Page 287 Chapter 16 ✦ Speaking Internet Protocols The method expunge permanently removes all messages marked as deleted by a \Deleted flag. Such messages are automatically expunged when you close the current mailbox. The method copy(messages,newmailbox) copies a set of messages to the mailbox named newmailbox. The method check does a mailbox “checkpoint” operation; what this means depends on the server. You normally operate on messages by index number. However, messages also have a unique identifier, or uid. To use uids to name messages, call the method uid (commandname, [args...]). This carries out the command commandname using uids instead of message indices. Administering mailboxes To create a new mailbox, call create(name). To delete a mailbox, call delete(name). Call rename(oldname,newname) to rename mailbox oldname to the name newname. Mailboxes can contain other mailboxes. For example, the name “nudgenudge/ winkwink” indicates a sub-box named “winkwink” inside a master mailbox “nudgenudge.” The hierarchy separator character varies by server; some servers would name the mailbox “nudgenudge.winkwink.” A mailbox can be marked as subscribed. The effects of subscribing vary by server, but generally subscriptions are a way of flagging mailboxes of particular interest. Use subscribe(name) and unsubscribe(name) to toggle subscription status for the mailbox name. The command list([root[,pattern]]) finds mailbox names. The parameter root is the base of a mailbox hierarchy to list. It defaults to “”(not a blank string, but a string of two double-quotes) for the root level. The parameter pattern is a string to search for; pattern may contain the wildcards * (matching anything) and % (matching anything but a hierarchy delimiter). The output of list is a list of 3-tuples. Each tuple corresponds to a mailbox. The first element is a list of flags, such as \Noselect. The second element is the server’s hierarchy separator character. The third is the mailbox name. To list only subscribed mailboxes, use the command lsub([root[,pattern]]). For example, the following code creates and lists some mailboxes: >>> print imap.list() (‘OK’, [‘() “/” “INBOX”’]) >>> imap.create(“x1”) (‘OK’, [‘CREATE completed’]) >>> imap.create(“x1/y1”) (‘OK’, [‘CREATE completed’]) 287 4807-7 ch16.F 288 5/24/01 8:59 AM Page 288 Part III ✦ Networking and the Internet >>> imap.create(“x1/y2”) (‘OK’, [‘CREATE completed’]) >>> imap.rename(“x1/y2”,”x1/y3”) (‘OK’, [‘RENAME completed’]) >>> imap.list() (‘OK’, [‘() “/” “INBOX”’, ‘() “/” “x1”’, ‘() “/” “x1/y1”’, ‘() “/” “x1/y3”’]) >>> print imap.list(‘“”’,”*y*”) # string “” for root (‘OK’, [‘() “/” “x1/y1”’, ‘() “/” “x1/y3”’]) >>> imap.list(‘“”’,”*foo*”) # Nothing found: get list of “None” (‘OK’, [None]) >>> imap.list(“x1”,”*3”) (‘OK’, [‘() “/” “x1/y3”’]) You can check the status of a mailbox by calling status(mailbox,names). The parameter mailbox is the name of a mailbox. The parameter names is a parenthesized string of status items to check. For example: >>> imap.status(“INBOX”,”(MESSAGES UIDNEXT)”) (‘OK’, [‘“INBOX” (MESSAGES 1 UIDNEXT 3)’]) Other functions You can add a message to a mailbox by calling the method append(mailbox, flags, datetime, message). Here, mailbox is the name of the mailbox, flags is an optional list of message flags, datetime is a timestamp for the message, and message is the message text, including headers. IMAP uses an INTERNALDATE representation for dates and times. Use the module function Internaldate2tuple(date) to translate an INTERNALDATE to a TimeTuple, and the function Time2Internaldate(tuple) to go from TimeTuple to INTERNALDATE. CrossReference See Chapter 13 for more information about the time module’s tuple representation of time. The function ParseFlags(str) splits an IMAP4 FLAGS response into a tuple of flags. Handling errors The class IMAP4.error is the exception raised by any errors using an IMAP4 object. The error argument is an error message string. It has subclasses IMAP4.abort (raised for server errors) and IMAP4.readonly (raised if the server changed a mailbox while you were reading mail, and you must re-open the mailbox). 4807-7 ch16.F 5/24/01 8:59 AM Page 289 Chapter 16 ✦ Speaking Internet Protocols Transferring Files via FTP The module ftplib provides the class FTP, which serves as an FTP client. The Python source distribution includes a script, Tools/script/ftpmirror.py, that uses ftplib to mirror an FTP site. CrossReference See RFC 959 for more on the FTP protocol. Logging in and out The FTP constructor takes several optional parameters. A call to FTP([host[, user[,password[,acct]]]]) constructs and returns an FTP object. The constructor also connects to the specified host if host is supplied. If user is supplied, the constructor logs in using the user user, the password password, and the account acct. You can also connect to a host by calling the FTP method connect(hostname [,port]). The port number defaults to 21; you will probably never need to set it manually. You can log in by calling login([user[,password[,acct]]]). If user is not specified, anonymous login is performed. The following two examples demonstrate the long and short way to log on to a server: >>> # long way: >>> session=ftplib.FTP() >>> session.connect(“gianth.com”) ‘220 gianth Microsoft FTP Service (Version 5.0).’ >>> session.login() # anonymous login (login string returned) ‘230-Niao! Greetings from Giant H Laboratories!\015\012230 Anonymous user logged in.’ >>> # short way: >>> session2=ftplib.FTP(“gianth.com”,”anonymous”,”bob@aol.com”) The method getwelcome returns the server welcome string (the same string returned by connect). When finished with an FTP connection, call quit or close. (The only difference between the two is that quit sends a “polite” response to the server.) Navigating The method pwd returns the current path on the server. The method cwd(path) sets the path on the server. You can call mkd(path) to create a new directory; call rmd(dirname) to delete an empty directory. 289 4807-7 ch16.F 290 5/24/01 8:59 AM Page 290 Part III ✦ Networking and the Internet The method nlst([dir[,args]]) returns directory contents as a list of file names. By default, both functions list the current directory; pass a different path in dir to list a different one. Extra string arguments are passed along to the server. The function dir([dir[,args]]) gets a list of files for processing. If the last argument to dir is a function, that function is used as a callback when retrieving each line (see retrlines, in the next section); the default processor simply prints each line. The method size(filename) returns the size of a particular file. You can delete a file with delete(filename), and rename a file by calling rename(oldname, newname). Transferring files To store (upload) a file, call storbinary(command,file,blocksize) for binary files, or storlines(command,file) for plain text files. The parameter command is the command passed to the server. The parameter file should be an opened file object. The storbinary parameter blocksize is the block size for data transfer. For example, the following code uploads a sound file to a server in 8K blocks, and then verifies that the file exists on the server: >>> Source=open(“c:\\SummerRain.mp3”) >>> Session.storbinary(“STOR SummerRain.mp3”,Source,8192) ‘226 Transfer complete.’ >>> Session.nlst().index(“SummerRain.mp3”) To retrieve (download) a file, call retrbinary(command,callback[,blocksize [,rest]]) or retrlines(command[,callback]). The parameter command is the command passed to the server. The parameter callback is a function to be called once for each block of data received. Python passes the block of data to the callback function. (The default callback for retrlines simply prints each line.) The parameter blocksize is the maximum size of each block. Supply a byte position for rest to continue a download part way through a file. For example, the following code retrieves a file from the server to a file: >>> destination=open(“foo.mp3”,”w”) >>> session.retrbinary(“RETR SummerRain.mp3”,dest.write) ‘226 Transfer complete.’ >>> destination.close() A lower-level method for file transfer is ntransfercmd(command[,rest]), which returns a 2-tuple: a socket object and the expected file size in bytes. The method transfercmd(command[,rest]) is the same as ntransfercmd, but returns only a socket object. The method abort cancels a transfer in progress. Other methods The method set_pasv(value) sets passive mode to value. If value is true, the PASV command is sent to the server for file transfers; otherwise, the PORT 4807-7 ch16.F 5/24/01 8:59 AM Page 291 Chapter 16 ✦ Speaking Internet Protocols command is used. (As of Python Version 2.1, passive mode is on by default; in previous versions, passive mode was not on by default.) The method set_debuglevel(level) sets the level of debug output from ftplib — 0 (the default level) produces no debug output; 2 is the most verbose. Handling errors The module defines several exceptions: error_reply is raised when the server unexpectedly sends a response; error_temp is raised for “temporary errors” (with error codes in the range 400–499); error_perm is raised for “permanent errors” (with error codes in the range 500–599); and error_proto is raised for errors with unknown error codes. Using netrc files The supporting module netrc is used to parse .netrc files. These files cache user information for various FTP servers, so that you don’t need to send it to the host by hand each time. They can also store macros. The module provides a class, netrc, for accessing netrc contents. The constructor netrc([filename]) builds a netrc object by parsing the specified file. If filename is not provided, it defaults to the file .netrc in your home directory. The attribute hosts is a dictionary mapping from host names to authentication information of the form (username, account, password). If the parsed .netrc file includes a default entry, it is stored in hosts[“default”]. The attribute macros is a dictionary, mapping macro names to string lists. The method authenticators(hostname) returns either the authentication tuple for hostname, the default tuple (if there is no tuple for hostname), or (if there is no default either) None. The netrc class implements a __retr__ method that returns .netrc file contents. This means that you can edit an existing file. For example, the following code adds (or overrides) an entry on disk: MyNetrc=netrc.netrc(“.netrc”) MyNetrc.hosts[“ftp.oracle.com”]=(“stanner”,””,”weeble”) NetrcFile=open(“.netrc”) NetrcFile.write(repr(MyNetrc)) NetrcFile.close() Retrieving Resources Using Gopher Gopher is a protocol for transferring hypertext and multimedia over the Internet. With the rise of the World Wide Web, Gopher is no longer widely used. However, the urllib module supports it, and the gopherlib module supports gopher requests. 291 4807-7 ch16.F 292 5/24/01 8:59 AM Page 292 Part III ✦ Networking and the Internet CrossReference See RFC 1436 for the definition of the Gopher protocol. The function send_selector(selector,host[,port]) sends a selector (analogous to a URL) to the specified host. It returns an open file object that you can read from. The port-number parameter, port, defaults to 70. For example, the following code retrieves and prints the Gopher Manifesto: Manifesto=gopherlib.send_selector( “0/the gopher manifesto.txt”,”gopher.heatdeath.org”) print Manifesto.read() The function send_query(selector,query,host[,port]) is similar to send_selector, but sends the query string query to the server along with the selector. Working with Newsgroups Network News Transport Protocol, or NNTP, is used to carry the traffic of newsgroups such as comp.lang.python. The module nntplib provides a class, NNTP, which is a simple NNTP client. It can connect to a news server and search, retrieve, and post articles. CrossReference See RFC 977 for the full definition of NNTP. Most methods of an NNTP object return a tuple, of which the first element is the server response string. The string begins with a three-digit status code. Dates in nntplib are handled as strings of the form yymmdd, and times are handled as strings of the form hhmmss. The two-digit year is assumed to be the year closest to the present, and the time zone assumed is that of the news server. Articles are identified in two ways. Articles are assigned numeric article numbers within a group in ascending order. Each article also has a unique message-id, a magic bracketed string unique across all articles in all newsgroups. For instance: An article cross-posted to rec.org.mensa and alt.religion.kibology might be article number 200 in rec.org.mensa, article number 500 in alt.religion.kibology, and have message-id <mwb06.162488e5.131709@newsfeeds.bigpond.com>. Some methods are not available on all news servers — the names of these methods begin with x (for “extension”). Connecting and logging in The constructor syntax is NNTP(host[,port[,user[,password [,readermode]]]]). Here, host is the news server’s host name. The port number, port, defaults to 119. If the server requires authentication, pass a username and 4807-7 ch16.F 5/24/01 8:59 AM Page 293 Chapter 16 ✦ Speaking Internet Protocols password in the user and password parameters. If you are connecting to a news server on the local host, pass a non-null value for readermode. Once connected, the getwelcome method returns the server’s welcome message. When you are finished with the connection, call the quit method to disconnect from the server. Browsing groups To select a particular newsgroup, call the method group(name). The method returns a tuple of strings (response,count,first,last,name). Here, count is the approximate number of messages in the group, first and last are the first and last article numbers, and name is the group name. The method list examines the newsgroups available on the server. It returns a tuple (response,grouplist), where response is the server response. The list grouplist has one element per newsgroup. Each entry is a tuple of the form (name,last,first,postable). Here, name is the name of the newsgroup, last is the last article number, and first is the first article number. The flag postable is either “y” if posting is allowed, “n” if posting is forbidden, or “m” if the group is moderated. Caution There are thousands of newsgroups out there. Retrieving a list usually takes several minutes. You may want to take a snack break when you call the list method! The following code finds all newsgroups with “fish” in their name: GroupList=news.list()[1] print filter(lambda x:x[0].find(“fish”)!=-1,GroupList) New newsgroups appear on USENET constantly. The method newgroups (date,time) returns all newsgroups created since the specified date and time, in the same format as the listing from list. Browsing articles New news is good news. The method newnews(name,date,time) finds articles posted after the specified moment on the group name. It returns a tuple of the form (response, idlist), where idlist is a list of message-ids. Once you have entered a group by calling group, you are “pointing at” the first article. You can move through the articles in the group by calling the methods next and last. These navigate to the next and the previous article, respectively. They then return a tuple of the form (response,number,id), where number is the current article number, and id is its message-id. The method stat(id) checks the status of an article. Here, id is either an article number (as a string) or a message-id. It returns the same output as next or last. 293 4807-7 ch16.F 294 5/24/01 8:59 AM Page 294 Part III ✦ Networking and the Internet On most news servers, you can scan article headers to find the messages you want. Call the method xhdr(header, articles) to retrieve the values of a header specified by header. The parameter articles should specify an article range of the form first-last. The returned value is a tuple (response, headerlist). The entries in headerlist have the form (id, text), where id is the message-id of an article, and text is its value for the specified header. For instance, the following code retrieves subjects for articles 319000 through 319005, inclusive: >>> news.xhdr(“subject”,”319000-319005”) (‘221 subject fields follow’, [(‘319000’, ‘Re: I heartily endorse: Sinfest!’), (‘319001’, ‘Re: Dr. Teg’), (‘319002’, ‘Re: If you be my bodyguard’), (‘319003’, ‘Re: Culture shock’), (‘319004’, ‘Re: Dr. Teg’), (‘319005’, ‘Todays lesson’)]) The method xover(start,end) gathers more detailed header information for articles in the range [start,end]. It returns a tuple of the form (response, articlelist). There is one element in the list articlelist for each article. Each such entry contains header values in a tuple of the form (article number, subject, poster, date, messageid, references, size, lines). The method xgtitle(name) finds all the newsgroups matching the specified name name, which can include wildcards. It returns a tuple of the form (response, grouplist). Each element of grouplist takes the form (name, description). For example, here is another (much faster) way to search for groups that talk about fish: print news.xgtitle(“*fish*”) Reading articles The method article(id) retrieves the article with the specified id. It returns a tuple of the form (response, number, id, linelist), where number is the article number, id is its message-id, and linelist is a list whose elements are the lines of text of the article. The text in linelist includes all its headers. The method head(id) and body(id) retrieve head and body, respectively. For example, the simple code in Listing 16-3 dumps all articles by a particular poster on a newsgroup into one long file: Listing 16-3: NewsSlurp.py import nntplib import sys def dump_articles(news,TargetGroup,TargetPoster): GroupInfo=news.group(TargetGroup) ArticleList=news.xhdr(“from”,GroupInfo[2]+”-”+GroupInfo[3]) dumpfile = open(“newsfeed.txt”,”w”) for ArticleTuple in ArticleList: (MessageID,Poster)=ArticleTuple 4807-7 ch16.F 5/24/01 8:59 AM Page 295 Chapter 16 ✦ Speaking Internet Protocols if (Poster.find(TargetPoster)!=-1): ArticleText=news.body(MessageID)[3] for ArticleLine in ArticleText: dumpfile.write(ArticleLine+”\n”) dumpfile.flush() dumpfile.close() news=nntplib.NNTP(“news.fastpointcom.com”) dump_articles(news,”alt.religion.kibology”,”kibo@world.std.com” ) Posting articles The method post(file) posts, as a new article, the text read from the file object file. The file text should include the appropriate headers. The method ihave(id,file) informs the server that you have an article whose message-id is id. If the server requests the article, it is posted from the specified file. Other functions The helper method date returns a tuple of the form (response, date, time), where date and time are of the form yymmdd and mmhhss, respectively. It is not available on all news servers. Call set_debug(level) to set the logging level for an NNTP object. The default, 0, is silent; 2 is the most verbose. The method help returns a tuple of the form (response, helplines), where helplines is the server help text in the form of a list of strings. Server help is generally not especially helpful, but may list the extended commands that are available. Call the slave method to inform the news server that your session is a helper (or “slave”) news server, and return the response. This notification generally has no special effect. Handling errors An NNTP object raises various exceptions when things go horribly wrong. NNTPError is the base class for all exceptions raised by nntplib. NNTPReply is raised if the server unexpectedly sends a reply. For error codes in the range of 400–499 (for example, calling next without selecting a newsgroup), NNTPTemporaryError is raised. For error codes in the range of 500–599 (for example, passing a bogus header to xhdr), NNTPPermanentError is raised. For unknown error codes, NNTPProtocolError is raised. Finally, NNTPDataError is raised for bogus response data. 295 4807-7 ch16.F 296 5/24/01 8:59 AM Page 296 Part III ✦ Networking and the Internet Using the Telnet Protocol The Telnet protocol is used for remote access to a server. Telnet is quite low-level, only a little more abstract than using socket directly. For example, you can (if you are a masochistic) read USENET by telnetting to port 119 and entering NNTP commands by hand. CrossReference See RFC 854 for a definition of the Telnet protocol. The module telnetlib defines a class, Telnet, which you can use to handle a Telnet connection to a remote host. Connecting The Telnet constructor has the syntax Telnet([host[,port]]). If you pass a host name in the parameter host, a session will be opened to the host. The port number, optionally passed via the parameter port, defaults to 23. If you don’t connect when constructing the object, you can connect by calling open(host[,port]). Once you are finished with a session, call the close method to terminate it. Note After establishing a connection, do not call the open method again for the same Telnet object. Reading and writing You can run a simple Telnet client (reading from stdin and printing server responses to stdout) by calling the interact method. The method mtinteract is a multithreaded version of interact. For example, the following lines would connect you to an online MUD (Multi-User Dungeon) game: >>> link=telnetlib.Telnet(“materiamagica.com”,4000) >>> link.interact() Writing data is simple: To send data to the server, call the method write(string). Special IAC (Interpret As Command) characters such as chr(255) are escaped (doubled). Reading data from the server is a bit more complicated. The Telnet object keeps a buffer of data read so far from the server; each read method accesses buffered (or “cooked”) data before reading more from the server. Each returns data read as a (possibly empty) string. The following read methods are available: ✦ read_all — Read until EOF. Block until the server closes the connection. ✦ read_some — Read at least one character (unless EOF is reached). Block if data is not immediately available. 4807-7 ch16.F 5/24/01 8:59 AM Page 297 Chapter 16 ✦ Speaking Internet Protocols ✦ read_very_eager — Read all available data, without blocking unless in the middle of a command sequence. ✦ read_eager — Same as read_very_eager, but does not read more from the server if cooked data is available. ✦ read_lazy — Reads all cooked data. Does not block unless in the middle of a command sequence. ✦ read_very_lazy — Reads all cooked data. Never blocks. The read methods, except read_all and read_some, raise an EOFError if the connection is closed and no data is buffered. For example, if you use read_very_lazy exclusively for reading, the only way to be certain the server is finished is if an EOFError is raised. For most purposes, you can just call read_some and ignore the other methods. For example, the following code connects to port 7 (the echo port) and talks to itself: echo=telnetlib.Telnet(“gianth.com”,7) echo.write(“Hello!”) print echo.read_very_eager() Watching and waiting The method read_until(expected[,timeout]) reads from the server until it encounters the string expected, or until timeout seconds have passed. If timeout is not supplied, it waits indefinitely. The method returns whatever data was read, possibly the empty string. It raises EOFError if the connection is closed and no data is buffered. A more powerful method expect(targets[,timeout]) watches for a list of strings or regular expression objects, provided in the parameter targets. It returns a tuple of the form (matchindex, match, text), where matchindex is the index (in targets) of the first matched item, match is a match object, and text is the text read up to and including the match. If no match was found, matchindex is -1, match is None, and text is the text read, if any. Other methods The method set_debug(level) sets the level of debug logging. A level of 0 (the default) is silent; level 2 is the most verbose. The method get_socket returns the socket object used internally by a Telnet object. The method fileno returns the file descriptor of the socket object. 297 4807-7 ch16.F 298 5/24/01 8:59 AM Page 298 Part III ✦ Networking and the Internet Writing CGI Scripts Many Web pages respond to input from the user — these pages range from simple feedback forms to sophisticated shopping Web sites. Common Gateway Interface (CGI) is a standard way for the Web server to pass user input into a script. The module cgi enables you to build Python modules to handle user requests to your Web site. Your CGI script should output headers, a blank line, and then content. The one required header is Content-type, and its usual value is “text/html.” For example, Listing 16-4 is a very simple CGI script, which returns a static Web page: Listing 16-4: HelloWorld.py # (add #! line here under UNIX, or if using Apache on Windows) import cgi # Part 1: Content-Type header, followed by a blank line # to indicate the end of the headers. print “Content-Type: text/html\n” # Part 2: A simple HTML page print “<title>Gumby</title>” print “<html><body>My brain hurts!</body></html> Setting up CGI scripts Making your Web server run a script is half the battle. In general, you must do the following: 1. Put the script in the right place. 2. Make it executable. 3. Make it execute properly. Configuration details vary by Web server and operating system, but the following sections provide information for some common cases. Windows Internet Information Server (IIS) First, create a directory (below your root Web directory) for CGI files. A common name is cgi-bin. Next, bring up the Internet Services Manager — in Windows 2000, go to Start ➪ Control Panel ➪ Administrative Tools ➪ Internet Services Manager. In Internet Services Manager, edit the properties of the CGI directory. In the Application section, click Configuration... (if Configuration is disabled, click 4807-7 ch16.F 5/24/01 8:59 AM Page 299 Chapter 16 ✦ Speaking Internet Protocols Add first). This brings up the Application Configuration dialog. On the App Mappings tab, add an entry mapping the extension .py to python.exe -u %s %s. The -u setting makes Python run in unbuffered binary mode. The %s %s ensures that IIS runs your script (and not just an instance of the interpreter!). UNIX Put your scripts in the appropriate CGI directory, probably cgi-bin. Make sure the script is executable by everyone (chmod 077 script.py). In addition, make sure any files it reads or writes are accessible by everyone. To make sure the script is executed as a python script, add a “pound-bang” line to the very top of the script, as follows: #!/usr/local/bin/python Apache (any operating system) To set up a CGI directory under Apache, add a ScriptAlias line to httpd.conf that points at the directory. In addition, make sure there is a <Directory> entry for that folder, and that it permits execution. For example, my configuration file includes the following lines: ScriptAlias /cgi-bin/ “C:/Webroot/cgi-bin/” <Directory “C:/Webroot/cgi-bin”> AllowOverride None Options None </Directory> Apache uses the “pound-bang hack” to decide how to execute CGI scripts, even on Windows. For example, I use the following simple test script to test CGI under Apache: #!python import cgi cgi.test() # the test function exercises many CGI features Accessing form fields To access form fields, instantiate one (and only one) cgi.FieldStorage object. The master FieldStorage object can be used like a dictionary. Its keys are the submitted field names. Its values are also FieldStorage objects. (Actually, if there are multiple values for a field, then its corresponding value is a list of FieldStorage objects.) The FieldStorage object for an individual field has a value attribute containing the field’s value as a string. It also has a name attribute containing the field name (possibly None). For example, the script in Listing 16-5 (and its corresponding Web page) gathers and e-mails site feedback. Listing 16-6 is a Web page that uses the script to handle form input. 299 4807-7 ch16.F 300 5/24/01 8:59 AM Page 300 Part III ✦ Networking and the Internet Listing 16-5: Feedback.py #!python import cgi import smtplib import sys import traceback # Set these e-mail addresses appropriately SOURCE_ADDRESS=”robot_form@gianth.com” FEEDBACK_ADDRESS=”dumplechan@seanbaby.com” sys.stderr = sys.stdout print “Content-Type: text/html\n” try: fields=cgi.FieldStorage() if (fields.has_key(“name”) and fields.has_key(“comments”)): UserName=fields[“name”].value Comments=fields[“comments”].value # Mail the feedback: Mailbox=smtplib.SMTP(“mail.seanbaby.com”) MessageText=”From: <”+SOURCE_ADDRESS+”>\r\n” MessageText+=”To: “+FEEDBACK_ADDRESS+”\r\n” MessageText+=”Subject: Feedback\r\n\r\n” MessageText+=”Feedback from “+UserName+”:\r\n”+Comments Mailbox.sendmail(SOURCE_ADDRESS, FEEDBACK_ADDRESS, MessageText) # Print a simple thank-you page: print “<h1>Thanks!</h1>Thank you for your feedback!” else: # They must have left “name” and/or “comments” blank: print “<h1>Sorry...</h1>” print “You must provide a name and some comments too!” except: # Print the traceback to the response page, for debugging! print “\n\n<PRE>” traceback.print_exc() Listing 16-6: Feedback.html <html> <title>Feedback form</title> <h1>Submit your comments</h1> <form action=”cgi-bin/Feedback.py” method=”POST”> Your name: <input type=”text” size=”35” name=”name”> <br> 4807-7 ch16.F 5/24/01 8:59 AM Page 301 Chapter 16 ✦ Speaking Internet Protocols Comments: <br> <textarea name=”comments” rows=”5” cols=”35”></textarea> <input type=”submit” value=”Send!”> <form> </html> Advanced CGI functions You can retrieve field values directly from the master FieldStorage object by calling the method getvalue(fieldname[,default]). It returns the value of field fieldname, or (if no value is available) the value default. If not supplied, default is None. If there are multiple values for a field, getvalue returns a list of strings. If a field value is actually a file, accessing the value attribute of the corresponding FieldStorage object returns the file’s contents as one long string. In this case, the filename attribute is set to the file’s name (as given by the client), and the file attribute is an opened file object. A FieldStorage object provides some other attributes: ✦ type — Content-type as a string (or None if unspecified) ✦ type_options — Dictionary of options passed with the content-type header ✦ disposition — Content-disposition as a string (or None if unspecified) ✦ disposition_options — Dictionary of options passed with the contentdisposition header ✦ headers — Map of all headers and their values A note on debugging Debugging CGI scripts can be difficult, because the traceback from a crashed script may be buried deep in the bowels of the Web server’s logging. Listing 16-7 uses a trick to make debugging easier. Listing 16-7: CGIDebug.py import sys import traceback sys.stderr = sys.stdout print “Content-Type: text/html\n” try: # The script body goes here! except: print “\n\n<PRE>” traceback.print_exc() 301 4807-7 ch16.F 302 5/24/01 8:59 AM Page 302 Part III ✦ Networking and the Internet Pointing stderr at stdout means that the output of print_exc goes to the resulting Web page. The <PRE> tag ensures that the text is shown exactly as printed. A note on security Internet security is crucial, even for casual users and simple sites. A common vulnerability is a CGI script that executes a command string passed from a Web request. Therefore, avoid passing user-supplied values to os.system, or accessing file names derived from user data. Remember that hidden fields on forms are hidden for presentation purposes only — enterprising users can see and manipulate their values. For a good introduction to Web security, see the World Wide Web Consortium’s security FAQ at http://www.w3.org/Security/Faq/www-security-faq.html. Summary Python provides simple client implementations of many Internet protocols. Python also makes a great CGI scripting language. In this chapter, you: ✦ Sent and received e-mail. ✦ Retrieved Web pages and files in various ways. ✦ Created a Web page with a simple feedback form. In the next chapter, you will meet various modules that help handle many flavors of Internet data. ✦ ✦ ✦ 4807-7 ch17.F 5/24/01 8:59 AM Page 303 17 CHAPTER Handling Internet Data ✦ ✦ ✦ ✦ In This Chapter I nternet data takes many forms. You may find yourself working with e-mail messages, mailboxes, cookies, URLs, and more. Python’s libraries include helper modules for handling this data. This chapter introduces modules to help handle several common tasks in Internet programming — handling URLs, sending e-mail, handling cookies from the World Wide Web, and more. Manipulating URLs A Uniform Resource Locator (URL) is a string that serves as the address of a resource on the Internet. The module urlparse provides functions to make it easier to manipulate URLs. The function urlparse(url[,default_scheme[,allow_fragments]]) parses the string url, splitting the URL into a tuple of the form (scheme, host, path, parameters, query, fragment). For example: >>> URLString=”http://finance.yahoo.com/q?s=MWT&d=v1” >>> print urlparse.urlparse(URLString) (‘http’, ‘finance.yahoo.com’, ‘/q’, ‘’, ‘s=MWT&d=v1’, ‘’) The optional parameter default_scheme specifies an addressing scheme to use if none is specified. For example, the following code parses a URL with and without a default scheme: >>> URLString=”//gianth.com/stuff/junk/DestroyTheWorld.exe” >>> print urlparse.urlparse(URLString) # no scheme! (‘’, ‘gianth.com’, ‘ /stuff/junk/DestroyTheWorld.exe’, ‘’, ‘’, ‘’) >>> print urlparse.urlparse(URLString,”ftp”) (‘ftp’, ‘gianth.com’, ‘/stuff/junk/DestroyTheWorld.exe’, ‘’, ‘’, ‘’) Manipulating URLs Formatting text Reading Web spider robot files Viewing files in a Web browser Dissecting e-mail messages Working with MIME encoding Encoding and decoding message data Working with UNIX mailboxes Using Web cookies ✦ ✦ ✦ ✦ 4807-7 ch17.F 304 5/24/01 8:59 AM Page 304 Part III ✦ Networking and the Internet The parameter allow_fragments defaults to true. If set to false, no fragments are permitted in the parsed URL: >>> URLString=”http://www.penny-arcade.com/#food” >>> print urlparse.urlparse(“URLString”) (‘http’, ‘www.penny-arcade.com’, ‘/’, ‘’, ‘’, ‘food’) >>> print urlparse.urlparse(“URLString”,None,0) (‘http’, ‘www.penny-arcade.com’, ‘/#food’, ‘’, ‘’, ‘’) The function urlunparse(tuple) unparses a tuple back into a URL string. Parsing and then unparsing yields a URL string that is equivalent (and quite possibly identical) to the original. The function urljoin(base, url[,allow_fragments]) merges a base URL (base) with a new URL (url) to create a new URL string. It is useful for processing anchors when parsing HTML. For example: >>> CurrentPage=”http://gianth.com/stuff/junk/index.html” >>> print urlparse.urljoin(CurrentPage,”../../foo.html”) http://gianth.com/foo.html The parameter allow_fragments has the same usage as urlparse. CrossReference The module urllib includes functions to encode strings as valid URL components. See “Manipulating URLs” in Chapter 16. Formatting Text The formatter module defines interfaces for formatters and writers. A formatter handles requests for various kinds of text formatting, such as fonts and margins. It passes formatting requests along to a writer. In particular, it keeps a stack of fonts and margins, so that they know which settings to revert to after turning off the “current” font or margins. Formatters and writers are useful for translating text between formats, or for displaying formatted text. They are used by htmllib.HTMLParser. Formatter interface The formatter attribute writer is the writer object corresponding to the formatter. Writing text The methods add_flowing_data(text) and add_literal_data(text) both send text to the writer. The difference between the two is that add_flowing_data collapses extra whitespace; whitespace is held in the formatter before being passed to the writer. The method flush_softspace clears buffered whitespace from the formatter. 4807-7 ch17.F 5/24/01 8:59 AM Page 305 Chapter 17 ✦ Handling Internet Data The method add_label_data(format, counter) sends label text (as used in a list) to the writer. If format is a string, it is used to format the numeric value counter (in a numbered list). Otherwise, format is passed along to the writer directly. If you manipulate the writer directly, call flush_softspace beforehand, and call assert_line_data([flag]) after adding any text. The parameter flag, which defaults to 1, should be true if the added data finished with a line break. Spacing, margins, and alignment The method set_spacing(spaces) sets the desired line spacing to lines. The methods push_alignment(align) and pop_alignment set and restore alignment. Here, align is normally left, right, center, justify (full), or None (default). The methods push_margin(name) and pop_margin increase and decrease the current level of indentation; the parameter name is a name for the new indentation level. The initial margin level is 0; all other margin levels must have names that evaluate to true. The method add_line_break adds a line break (at most, one in succession), but does not finish the current paragraph. The method end_paragraph(lines) ends the current paragraph and inserts at least lines blank lines. Finally, the method add_hor_rule adds a horizontal rule; its parameters are formatter- and writerdependent, and are passed along to the writer’s method send_line_break. Fonts and styles The method push_font(font) pushes a new font definition, font, of the form (size,italics,bold,teletype). Values set to formatter.AS_IS are left unchanged. The new font is passed to the writer’s new_font method. The method pop_font restores the previous font. The method push_style(*styles) passes any number of style definitions. A tuple of all style definitions is passed to the writer’s method new_styles. The method pop_style([count]) pops count styles (by default, 1), and passes the revised stack to new_styles. Writer interface Writers provide various methods to print or display text. Normally, the formatter calls these methods, but a caller can access the writer directly. Writing text The methods send_flowing_data(text) and send_literal_data(text) both output text. The difference between the two is that send_literal_data sends 305 4807-7 ch17.F 306 5/24/01 8:59 AM Page 306 Part III ✦ Networking and the Internet pre-formatted text, whereas send_flowing_data sends text with redundant whitespace collapsed. The method send_label_data(text) sends text intended for a list label; it is called only at the beginning of a line. The method flush is called to flush any buffered output. Spacing, margins, and alignment The method send_line_break breaks the current line. The method send_ paragraph(lines) is called to end the current paragraph and send at least lines blank lines. The method set_spacing(lines) sets the level of line spacing to lines. The method send_hor_rule is called to add a horizontal rule; its arguments are formatter- and writer-dependent. The method new_margin(name,level) sets the margin level to level, where the indentation level’s name is name. The method new_alignment(align) sets line alignment. Here, align is normally left, right, center, justify (full), or None (default). Fonts and styles The method new_font(font) sets the current font to font, where font is either None (indicating default font), or a tuple of the form (size,italic,bold,teletype). The method new_styles(styles) is called to set new style(s); pass a tuple of new style values in styles. Other module resources The AbstractFormatter is a simple formatter that you can use for most applications. The NullFormatter is a trivial implementation of the formatter interface — it has all the available methods, but they do nothing. It is useful for creating an HTTPParser that does not format Web pages. The NullWriter is a writer that does nothing. The AbstractWriter is useful for debugging formatters; method calls are simply logged. The DumbWriter is a simple writer that outputs word-wrapped text. Its constructor has the syntax DumbWriter ([file[,maxcol]]). Here, file is an open filelike object for output (if none is specified, text is written to standard output); and maxcol (which defaults to 72) is the maximum width, in characters, of a line. For example, this function prints a text-only version of a Web page: import htmllib import urllib import formatter def PrintTextPage(URL): URLFile = urllib.urlopen(URL) HTML = URLFile.read() 4807-7 ch17.F 5/24/01 8:59 AM Page 307 Chapter 17 ✦ Handling Internet Data URLFile.close() parser=htmllib.HTMLParser( formatter.AbstractFormatter(formatter.DumbWriter())) parser.feed(HTML) Reading Web Spider Robot Files A robot is a program that automatically browses the Web. For example, a script could programmatically check CD prices at several online sites in order to find the best price. Some Webmasters would prefer that robots not visit their systems. Therefore, a well-behaved robot should check a host’s Web root for a file named robots.txt, which specifies any URLs that are off-limits. The module robotparser provides a class, RobotFileParser, which makes it easy to parse robots.txt. Once you instantiate a RobotFileParser, call its set_url(url) to point it at the robots.txt file at the specified URL url. Then, call its read method to parse the file. Before retrieving a URL, call can_fetch(useragent, url) to determine whether the specified URL is allowed. The parameter useragent should be the name of your robot program. For example, Listing 17-1 tests a “polite get” of a URL: Listing 17-1: PoliteGet.py import robotparser import urlparse import urllib def PoliteGet(url): “””Return an open url-file, or None if URL is forbidden””” RoboBuddy=robotparser.RobotFileParser() # Grab the host-name from the URL: URLTuple=urlparse.urlparse(url) RobotURL=”http://”+URLTuple[1]+”/robots.txt” RoboBuddy.set_url(RobotURL) RoboBuddy.read() if RoboBuddy.can_fetch(“I,Robot”,url): return urllib.urlopen(url) else: return None if (__name__==”__main__”): URL=”http://www.nexor.com/cgi-bin/rfcsearch/location?2449” print “Forbidden:”,(PoliteGet(URL)==None) URL=”http://www.yahoo.com/r/sq” print “Allowed:”,(PoliteGet(URL)==None) 307 4807-7 ch17.F 308 5/24/01 8:59 AM Page 308 Part III ✦ Networking and the Internet You can manually pass a list of robots.txt lines to a RobotFileParser by calling the method parse(lines). If your parser runs for many days or weeks, you may want to re-read robots.txt periodically. RobotFileParser keeps a “last updated” timestamp. Call the method modified to set the timestamp to the current time. (This is done automatically when you call read or parse.) Call mtime to retrieve the timestamp, in ticks. Viewing Files in a Web Browser The module webbrowser provides a handy interface for opening URLs in a browser. The function open(url[,new]) opens the specified URL using the default browser. If the parameter new is true, a new browser window is opened if possible. The function open_new(url) is a synonym for open(url,1). Normally, pages are displayed in their own window. However, on UNIX systems for which no graphical browser is available, a text browser will be opened (and the program will block until the browser session is closed). If you want to open a particular browser, call the function register(name, class[,instance]). Here, name is one of the names shown in Table 17-1, and either class is the corresponding class, or instance is an instance of the corresponding class. Table 17-1 Available Browsers Name Class Platform netscape Netscape All kfm Konquerer UNIX grail Grail All windows-default WindowsDefault Windows internet-config InternetConfig Macintosh command-line CommandLineBrowser All Once a browser is registered, you can call get(name) to retrieve a controller for it. The controller provides open and open_new methods similar to the functions of the same names. For example, the following code asks for the Grail browser by name, and then uses it to view a page: >>> Webbrowser.register(“grail”,Webbrowser.Grail) >>> Controller=Webbrowser.get(“grail”) >>> Controller.open(“www.python.org”) 4807-7 ch17.F 5/24/01 8:59 AM Page 309 Chapter 17 ✦ Handling Internet Data Dissecting E-Mail Messages E-mail messages have headers with a standard syntax. The syntax, described in RFC 822, is a bit complicated. Fortunately, the module rfc822 can parse these headers for you. It also provides a class to help handle lists of addresses. Parsing a message To parse a message, call the constructor Message(file[,seekable]). Here, file is an open file. The file is parsed, and all headers are matched case-insensitively. The file parameter can be any filelike object with a readlines method; it must also have seek and tell methods in order for Message.rewindbody to work. If file is unseekable (for example, it wraps a socket), set seekable to 0 for maximum portability. Retrieving header values The method get(name[,default]) returns the last value of header name, or default (by default, None) if no value was found. Leading and trailing whitespace is trimmed from the header; newlines are removed if the header takes up multiple lines. The method getheader is a synonym for get. The method getrawheader(name) returns the first header name with whitespace (including trailing linefeed) intact, or None if the header was not found. If a header can have multiple values, you can use getallmatchingheaders(name) to retrieve a (raw) list of all header lines matching name. The method getfirstmatchingheader(name) returns a list of lines for the first match: >>> MessageFile=open(“msg1.txt”) >>> msg=rfc822.Message(MessageFile) >>> msg.get(“received”) # The last value ‘from 216.20.160.186 by lw8fd.law8.hotmail.msn.com with HTTP;\011Thu, 28 Dec 2000 23:37:18 GMT’ >>> msg.getrawheader(“RECEIVED”) # the first value: ‘ from hotmail.com [216.33.241.22] by mail3.oldmanmurray.com with ESMTP\012 (SMTPD32-6.05) id AB8884C01EE; Thu, 28 Dec 2000 18:23:52 -0500\012’ >>> msg.getallmatchingheaders(“Received”) # ALL values: [‘Received: from hotmail.com [216.33.241.22] by mail3.oldmanmurray.com with ESMTP\012’, ‘ (SMTPD32-6.05) id AB8884C01EE; Thu, 28 Dec 2000 18:23:52 -0500\012’, ‘Received: from mail pickup service by hotmail.com with Microsoft SMTPSVC;\012’, ‘\011 Thu, 28 Dec 2000 15:37:19 -0800\012’, ‘Received: from 216.20.160.186 by lw8fd.law8.hotmail.msn.com with HTTP;\011Thu, 28 Dec 2000 23:37:18 GMT\012’] 309 4807-7 ch17.F 310 5/24/01 8:59 AM Page 310 Part III ✦ Networking and the Internet Some headers are dates. Call getdate(name) to retrieve the value of header name as a TimeTuple. Alternatively, call getdate_tz(name) to retrieve a 10-tuple; its first nine entries form a TimeTuple, and the tenth is the time zone’s offset (in ticks) from UTC. (Entries 6, 7, and 8 are unusable in each case.) For example: >>> msg.getdate(“date”) (2000, 12, 28, 16, 37, 18, 0, 0, 0) >>> msg.getdate_tz(“date”) (2000, 12, 28, 16, 37, 18, 0, 0, 0, -25200) The method getaddr(name) helps parse To: and From: headers, returning their values in the form (full name, e-mail address). If the header name is not found, it returns (None,None). For example: >>> msg.getaddr(“From”) (‘Stephen Tanner’, ‘dumplechan@hotmail.com’) >>> msg.getaddr(“PurpleHairySpiders”) (None, None) Other members The method rewindbody seeks to the start of the message body (if the filelike object parsed supports seeking). A Message object supports the methods of a dictionary — for example, keys returns a list of headers found. The attribute fp is the original file parsed, and the attribute headers is a list of all header lines. If you need to subclass Message, you may want to override some of its parsing methods. The method islast(line) returns true if line marks the end of header lines. By default, islast returns true when passed a blank line. The method iscomment(line) returns true if line is a comment that should be skipped. Finally, the method isheader(line) returns the header name if line is a valid header line, or None if it is not. Address lists The class AddressList holds a list of e-mail addresses. Its constructor takes a list of address strings; passing None results in an AddressList with no entries. You can take the length of an AddressList, add (merge) two AddressLists, remove (subtract) one of AddressList’s elements from another AddressList, and retrieve a canonical string representation: >>> >>> >>> >>> 2 List1=rfc822.AddressList(msg.getheader(“To”)) List2=rfc822.AddressList(msg.getheader(“From”)) MergedList=List1+List2 # Merge lists len(MergedList) # access list length 4807-7 ch17.F 5/24/01 8:59 AM Page 311 Chapter 17 ✦ Handling Internet Data >>> str(MergedList) # canonical representation ‘dumplechan@seanbaby.com, “Stephen Tanner” <dumplechan@hotmail.com>’ >>> str(MergedList-List1) # remove one list’s elements ‘“Stephen Tanner” <dumplechan@hotmail.com>’ An AddressList also provides the attribute addresslist, a list of tuples of the form (full name, e-mail address): >>> MergedList.addresslist [(‘’, ‘dumplechan@seanbaby.com’), (‘Stephen Tanner’, ‘dumplechan@hotmail.com’)] rfc822 utility functions The functions parsedata(str) and parsedata_tz(str) parse the string str, in the manner of the Message methods getdate and getdate_tz. The function mktime_tz(tuple) does the reverse — it converts a TimeTuple into a UTC timestamp. MIME messages The class mimetools.Message is a subclass of rfc822.Message. It provides some extra methods to help parse content-type and content-transfer-encoding headers. The method gettype returns the message type (in lowercase) from the contenttype header, or text/plain if no content-type header exists. The methods getmaintype and getsubtype get the main type and subtype, respectively. The method getplist returns the parameters of the content-type header as a list of strings. For parameters of the form name=value, name is converted to lowercase but value is unchanged. The method getparam(name) gets the first value (from the content-type header) for a given name; any quotes or brackets surrounding the value are removed. The method getencoding returns the value of the content-transfer-encoding header, converted to lowercase. If not specified, it returns 7bit. This example scrutinizes some headers from an e-mail message: >>> MessageFile=open(“message.txt”,”r”) >>> msg=mimetools.Message(MessageFile) >>> msg.gettype() ‘text/plain’ >>> msg.getmaintype() ‘text’ >>> msg.getsubtype() ‘plain’ 311 4807-7 ch17.F 312 5/24/01 8:59 AM Page 312 Part III ✦ Networking and the Internet >>> msg.getplist() [‘format=flowed’] >>> msg.get(“content-type”) ‘text/plain; format=flowed’ >>> msg.getparam(“format”) ‘flowed’ >>> msg.getencoding() ‘7bit’ Working with MIME Encoding Multipurpose Internet Mail Extensions (MIME) are a mechanism for tagging the document type of a message — or for several parts of one message. (See RFC 1521 for a full description of MIME.) Several Python modules help handle MIME messages — most functions you need are there, though they may be spread across libraries. The module mimetools provides functions to handle MIME encoding. The function decode(input,output,encoding) decodes from the filelike object input to output, using the specified encoding. The function encode(input,output,encoding) encodes. Legal values for encoding are base64, quoted-printable, and uuencode. These encodings use the modules base64, quopri, and uu, discussed in the section “Encoding and Decoding Message Data.” The function choose_boundary returns a unique string for use as a boundary between MIME message parts. Encoding and decoding MIME messages The module mimify provides functions to encode and decode messages in MIME format. The function mimify(input, output) encodes from the filelike object input into output. Non-ASCII characters are encoded using quoted-printable encoding, and MIME headers are added as necessary. The function unmimify(input, output[,decode_base64) decodes from input into output; if decode_base64 is true, then any portions of input encoded using base64 are also decoded. You can pass file names (instead of files) for input and output. The functions mime_encode_header(line) and mime_decode_header(line) encode and decode a single string. The mimify module assumes that any line longer than mimify.MAXLEN (by default, 200) characters needs to be encoded. Also, the variable mimify.CHARSET is a default character set to fill in if not specified in the content-type header; it defaults to ISO-8859-1 (Latin1). 4807-7 ch17.F 5/24/01 8:59 AM Page 313 Chapter 17 ✦ Handling Internet Data Parsing multipart MIME messages A MIME message can have several sections, each with a different content-type. The sections of a MIME message, in turn, can be divided into smaller subsections. The multifile module provides a class, MultiFile, to wrap multi-part messages. A MultiFile behaves like a file, and can treat section boundaries like an EOF. The constructor has syntax MultiFile(file[,seekable]). Here, file is a filelike object, and seekable should be set to false for nonseekable objects such as sockets. Call the method push(str) to set str as the current boundary string; call pop to remove the current boundary string from the stack. The MultiFile will raise an error if it encounters an invalid section boundary — for example, if you call push(X), and then push(Y), and the MultiFile encounters the string X before seeing Y. A call to next jumps to the next occurrence of the current boundary string. The attribute level is the current nesting depth. The read, readline, readlines, seek, and tell methods of a MultiFile operate on only the current section. For example, seek indices are relative to the start of the current section, and readlines returns only the lines in the current section. When you read to the end of a section, the attribute last is set to 1. At this point, it is not possible to read further, unless you call next or pop. The method is_data(str) returns false if str might be a section boundary. It is used as a fast test for section boundaries. The method section_divider(str) converts str into a section-divider line, by prepending “--”. The method end_marker(str) converts str into an end-marker line, by adding “--” at the beginning and end of str. Writing out multipart MIME messages The module MimeWriter provides the class MimeWriter to help write multipart MIME messages. The constructor takes one argument, an open file (or filelike object) to write the message to. To add headers, call addheader(header, value[,prefix]). Here, header is the header to add, and value is its value. Set the parameter prefix to true to add the new header at the beginning of the message headers, or false (the default) to append it to the end. The method flushheaders writes out all accumulated headers; you should only call it for message parts with an empty body (which, in turn, shouldn’t happen). To write a single-part message, call startbody(content[,plist[,prefix]]) to construct a filelike object to hold the message body. Here, content is a value for the content-type header, and plist is a list of additional content-type parameter tuples of the form (name,value). The parameter prefix defaults to true, and functions as in addheader. 313 4807-7 ch17.F 314 5/24/01 8:59 AM Page 314 Part III ✦ Networking and the Internet To write a multipart message, first call startmultipartbody(subtype [,boundary[,plist[,prefix]]]). The content-type header has main type “multipart,” subtype subtype, and any extra parameters you pass in plist. For each part of the message, call nextpart to get a MimeWriter for that part. After finishing each part of the message, call lastpart to finish the message off. The call to startmultipartbody also returns a filelike object; it can be used to store a message for non-MIME-capable software. Note You should not close the filelike objects provided by the MimeWriter, as each one is a wrapper for the same file. For example, Listing 17-2 writes out a multipart message and then parses it back again. Listing 17-2: MimeTest.py import import import import MimeWriter mimetools base64 multifile def TestWriting(): # Write out a multi-part MIME message. The first part is # some plain text. The second part is an embedded # multi-part message; its two parts are an HTML document # and an image. MessageFile=open(“BigMessage.txt”,”w”) msg=MimeWriter.MimeWriter(MessageFile) msg.addheader(“From”,”dumplechan@hotmail.com”) msg.addheader(“To”,”dave_brueck@hotmail.com”) msg.addheader(“Subject”,”Pen-pal greetings (good times!)”) # Generate a unique section boundary: OuterBoundary=mimetools.choose_boundary() # Start the main message body. Write a brief message # for non-MIME-capable readers: DummyFile=msg.startmultipartbody(“mixed”,OuterBoundary) DummyFile.write(“If you can read this, your mailreader\n”) DummyFile.write(“can’t handle multi-part messages!\n”) # Sub-part 1: Simple plain-text message submsg=msg.nextpart() FirstPartFile=submsg.startbody(“text/plain”) FirstPartFile.write(“Hello!\nThis is a text part.\n”) FirstPartFile.write(“It was a dark and stormy night...\n”) FirstPartFile.write(“ * * TO BE CONTINUED * *\n”) # Sub-part 2: Message with parallel html and image submsg2=msg.nextpart() # Generate boundary for sub-parts: InnerBoundary=mimetools.choose_boundary() submsg2.startmultipartbody(“mixed”,InnerBoundary) 4807-7 ch17.F 5/24/01 8:59 AM Page 315 Chapter 17 ✦ Handling Internet Data submsg2part1=submsg2.nextpart() # Sub-part 2.1: HTML page SubTextFile=submsg2part1.startbody(“text/html”) SubTextFile.write(“<html><title>Hello!</title>\n”) SubTextFile.write(“<body>Hello world!</body></html>\n”) # Sub-part 2.2: Picture, encoded with base64 encoding submsg2part2=submsg2.nextpart() submsg2part2.addheader(“Content-Transfer-Encoding”, “base64”) ImageFile=submsg2part2.startbody(“image/gif”) SourceImage=open(“pic.gif”,”rb”) base64.encode(SourceImage,ImageFile) # Finish off the sub-message and the main message: submsg2.lastpart() msg.lastpart() MessageFile.close() # all done! def TestReading(): MessageFile=open(“BigMessage.txt”,”r”) # Parse the message boundary using mimetools: msg=mimetools.Message(MessageFile) OuterBoundary=msg.getparam(“boundary”) reader=multifile.MultiFile(MessageFile) reader.push(OuterBoundary) print “**Text for non-MIME-capable readers:” print reader.read() reader.next() print “**Text message:” print reader.read() reader.next() # Parse the inner boundary: msg=mimetools.Message(reader) InnerBoundary=msg.getparam(“boundary”) reader.seek(0) # rewind! reader.push(InnerBoundary) reader.next() # seek to part 2.1 print “**HTML page:” print reader.read() reader.next() print “**Writing image to pic2.gif...” # seek to start of (encoded) body: msg=mimetools.Message(reader) msg.rewindbody() # decode the image: ImageFile=open(“pic2.gif”,”wb”) base64.decode(reader,ImageFile) if (__name__==”__main__”): TestWriting() TestReading() 315 4807-7 ch17.F 316 5/24/01 8:59 AM Page 316 Part III ✦ Networking and the Internet Handling document types There is no official mapping between MIME types and file extensions. However, the module mimetypes can make reasonable guesses. The function guess_extension (type) returns a reasonable extension for files of content-type type, or None if it has no idea. The function guess_type(filename) returns a tuple of the form (type, encoding). Here, type is a content-type that is probably valid, based on the file’s extension. If guess_type doesn’t have a good guess for type, it returns None. The value encoding is the name of the encoding program used on the file, or None: >>> mimetypes.guess_extension(“text/plain”) ‘.txt’ >>> mimetypes.guess_type(“fred.txt”) (‘text/plain’, None) >>> mimetypes.guess_type(“Spam.mp3”) (None, None) You can customize the mapping between extensions and types. Many systems store files named mime.types to hold this mapping; the mimetools module keeps a list of common UNIX paths to such files in knownfiles. The function read_mime_types (filename) reads mappings from the specified file. Each line of the file should include a mime-type and then one or more extensions, separated by whitespace. Listing 17-3 shows a sample mime.types file: Listing 17-3: sample mime.types file plain/text txt application/mp3 mp3 mp2 The function init([files]) reads mappings from the files in the list files, which defaults to knownfiles. Files later in the list override earlier files in the case of a conflict. The module variable inited is true if init has been called; calling init multiple times is allowed. The following shows an easy way to customize the mapping: >>> MyPath=”c:\\python20\\mime.types” # (customize this) >>> mimetools.init([MyPath]) # old settings may be overridden You can also directly access the mapping from extensions to encodings (encodings_map), and the mapping from extensions to MIME-types (types_map). The mapping suffix_map is used to map the extensions .tgz, .taz, and .tz to .tar.gz. 4807-7 ch17.F 5/24/01 8:59 AM Page 317 Chapter 17 ✦ Handling Internet Data Parsing mailcap files A mailcap (for “mail capability”) file maps document MIME-types to commands appropriate for each type of document. Mailcap files are commonly used on UNIX systems. (On Windows, file associations are normally stored in the registry.) CrossReference See RFC 1524 for a definition of the file format. The module mailcap provides functions to help retrieve information from mailcap files. The function getcaps returns a dictionary of mailcap information. You use it by passing it to findmatch(caps,MIMEType[,key[,filename[,plist]]]). Here, caps is the dictionary returned by getcaps, and MIMEType is the type of document to access. The parameter key is the type of access (such as view, compose, or edit); it defaults to view. The return value of findmatch is the command line to execute (through os.system, for example). You can pass a list of extra parameters in plist. Each entry should take the form name=value — for example, colors=256. The function getcaps parses /etc/mailcap, /usr/etc/mailcap, /usr/local/etc/mailcap, andHOME/mailcap. The user mailcap file, if any, overrides the system mailcap settings. Encoding and Decoding Message Data E-mail messages must pass through various systems on their way from one person to another. Different computers handle data in different (sometimes incompatible) ways. Therefore, most e-mail programs encode binary data as 7-bit ASCII text. The encoded file is larger than the original, but is less likely to be mangled in transit. Python provides modules to help use three such encoding schemes — uuencode, base64, and quoted-printable. Uuencode The module uu provides functions to encode (binary-to-ASCII) and decode (ASCII-to-binary) binary files using uuencoding. The function encode(input, output[,name[,mode]]) uuencodes the file input, writing the resulting output to the file output. If passed, name and mode are put into the file header as the file name and permissions. The function decode(input,output) decodes from the file input to the file output. For example, the following lines encode a Flash animation file.>>> source=open(“pample2.swf”,”rb”) >>> destination=open(“pample2.uu”,”w”) >>> uu.encode(source,destination) 317 4807-7 ch17.F 318 5/24/01 8:59 AM Page 318 Part III ✦ Networking and the Internet Note In this case, the file must be opened in binary mode (“rb”) under Windows or Macintosh; this is not necessary on UNIX. These lines decode the file, and then launch it in a browser window: >>> >>> >>> >>> >>> Note source=open(“pample2.uu”,”r”) destination=open(“pample.swf”,”wb”) uu.decode(source,destination) destination.close() Webbrowser.open(“pample.swf”) It is possible to pass file names (instead of open files) to encode or decode. However, this usage is deprecated. Base64 Base64 is another algorithm for encoding binary data as ASCII. The module base64 provides functions for working with MIME base64 encoding. The function encodestring(data) encodes a string of binary data, data, and returns a string of base64-encoded data. The function encode(input, output) reads data from the filelike object input, and writes an encoded base64 string to the filelike object output. To decode a base64 string, call decodestring(data). To decode from one filelike object to another, call decode(input,output). Base64 is sometimes used to hide data from prying eyes. It is no substitute for encryption, but is better than nothing. The code in Listing 17-4 uses base64 to hide the files from one directory in another directory: Listing 17-4: Conceal.py import base64 import string import os “”” Hide files by base64-encoding them. Use Conceal to hide files, and Reveal to un-hide them. “”” # not ok for filenames: EvilChars=”/\n” # not Base64 characters, ok for filenames: GoodChars=”_ “ TranslateEvil = string.maketrans(EvilChars,GoodChars) UnTranslateEvil = string.maketrans(GoodChars,EvilChars) 4807-7 ch17.F 5/24/01 8:59 AM Page 319 Chapter 17 ✦ Handling Internet Data def GetEncodedName(OldName): MagicName = base64.encodestring(OldName) MagicName = string.translate(MagicName,TranslateEvil) return MagicName def GetDecodedName(OldName): MagicName = string.translate(OldName,UnTranslateEvil) MagicName = base64.decodestring(OldName) return MagicName def Conceal(SourceDir,DestDir): “”” Encode the files in sourcedir as files in destdir “”” for FileName in os.listdir(SourceDir): FilePath = os.path.join(SourceDir,FileName) # Note: need “rb” here! (on UNIX, just “r” is ok) InFile=open(FilePath,”rb”) OutputFilePath=os.path.join( DestDir,GetEncodedName(FileName)) OutFile=open(OutputFilePath,”w”) base64.encode(InFile,OutFile) InFile.close() OutFile.close() def Reveal(SourceDir,DestDir): “”” Decode the files in sourcedir into destdir “”” for FileName in os.listdir(SourceDir): FilePath = os.path.join(SourceDir,FileName) InFile=open(FilePath,”r”) OutputFilePath=os.path.join(DestDir,GetDecodedName(FileName)) OutFile=open(OutputFilePath,”wb”) base64.decode(InFile,OutFile) InFile.close() OutFile.close() Quoted-printable Quoted-printable encoding is another scheme for encoding binary data as ASCII text. It works best for strings with relatively few non-ASCII characters (such as German text, with occasional umlauts); for binary files such as images, base64 is more appropriate. The module quopri provides functions to handle quoted-printable encoding. The function decode(input,output) decodes from the filelike object input to the filelike object output. The function encode(input,output,quotetabs) encodes from input to output. The parameter quotetabs indicates whether tabs should be quoted. 319 4807-7 ch17.F 320 5/24/01 8:59 AM Page 320 Part III ✦ Networking and the Internet Working with UNIX Mailboxes Many UNIX mail programs store all e-mail in one file or directory called a mailbox. The module mailbox provides utility classes for parsing such a mailbox. Each class provides a single method, next, which returns the next rfc822.Message object. Mailbox parser constructors each take either a file object or directory name as their only argument. Table 17-2 lists the available mailbox parser classes. Table 17-2 Mailbox Parsers Class Mailbox Type UnixMailbox Classic UNIX-style mailbox, as used by elm or pine MmdfMailbox MMDF mailbox MHMailbox MH mailbox (directory) Maildir Qmail mailbox (directory) BabylMailbox Babyl mailbox Working with MH mailboxes The module mhlib provides advanced features for managing MH mailboxes. It includes three classes: MH represents a collection of mail folders, Folder represents a single mail folder, and Message represents a single message. MH objects The constructor has the syntax MH([path[,profile]]). You can pass path and/or profile to override the default mailbox directory and profile. The method openfolder(name) returns a Folder object for the folder name. The method setcontext(name) sets the current folder to name; getcontext retrieves the current folder (initially “inbox”). The method listfolders returns a sorted list of top-level folder names; listallfolders returns a list of all folder names. listsubfolders(name) returns a list of immediate child folders of the folder name; listallsubfolders(name) returns a list of all subfolders of the folder name. The methods makefolder(name) and deletefolder(name) create and destroy a folder with the given name. 4807-7 ch17.F 5/24/01 8:59 AM Page 321 Chapter 17 ✦ Handling Internet Data The method getpath returns the path to the mailbox. The method getprofile(key) returns the profile entry for key (or None, if none is set). And the method error(format,arguments) prints the error message (format % arguments) to stderr. Folder objects The methods getcurrent and setcurrent(index) are accessors for the current message number. getlast returns the index of the last message (or 0 if there are no messages). listmessages returns a list of message indices. The method getsequences returns a dictionary of sequences, where each key is a sequence name and the corresponding value is a list of the sequence’s message numbers. putsequences(dict) writes such a dictionary of sequences back to the sequence files. The method parsesequence(str) parses the string str into a list of message numbers. You can delete messages with removemessages(list), or move them to a new folder with refilemessages(list, newfolder). Here, list is a list of message numbers on which to operate. You can move one message by calling movemessage(index, newfolder,newindex), or copy one message by calling copymessage(index,newfolder,newindex). Here, newindex is the desired message number in the new folder newfolder. The path to the folder is accessible through getfullname, while getsequencesfilename returns the path to the sequences file, and getmessagefilename(index) returns the full path to message index. The method error(format,arguments) prints the error message (format % arguments) to stderr. Message objects The class mh.Message is a subclass of mimetools.Message. It provides one extra method, openmessage(index), which returns a new Message object for message number index. Using Web Cookies A cookie is a token used to manage sessions on the World Wide Web. Web servers send cookie values to a browser; the browser then regurgitates cookie values when it sends a Web request. The module Cookie provides classes to handle cookies. It is especially useful for making a robot, as many Web sites require cookies to function properly. 321 4807-7 ch17.F 322 5/24/01 8:59 AM Page 322 Part III ✦ Networking and the Internet Cookies The class SimpleCookie is a dictionary mapping cookie names to cookie values. Each cookie value is stored as a Cookie.Morsel. You can pass a cookie string (as received from the Web server) to SimpleCookie’s constructor, or to its load method. To retrieve cookie values in a format suitable for inclusion in an HTTP request, call the method output([attributes[,header[,separator]]]). To retrieve only some cookie attributes, pass a list of desired attributes in attributes. The parameter header is the header to use (by default, “Set-Cookie:”). Finally, separator is the separator to place between cookies (by default, a newline). For example, the following lines capture cookies as returned from a Web request: >>> Request=httplib.HTTP(“www.mp3.com”) >>> Request.putrequest(“GET”,URLString) >>> Request.endheaders() >>> Response=Request.getreply() >>> # Response[2] is the header dictionary >>> CookieString=Response[2][“set-cookie”] >>> print CookieString LANG=eng; path=/; domain=.mp3.com >>> CookieJar=Cookie.SimpleCookie() >>> CookieJar.load(CookieString) >>> print CookieJar.output() ‘Set-Cookie: LANG=eng; Path=/; Domain=.mp3.com;’ >>> print CookieJar.output([“domain”]) ‘Set-Cookie: LANG=eng; Domain=.mp3.com;’ The method js_output([attributes]) also outputs cookies, this time in the form of a JavaScript snippet to set their values. Morsels A morsel stores a cookie name in the attribute key, its value in the attribute value, and its coded value (suitable for sending) in the attribute coded_value. The convenience function set(key, value, coded_value) sets all three attributes. Morsels provide output and js_output methods mirroring those of their owning cookie; they also provide an OutputString([attributes]) method that returns the morsel as a human-readable string. A morsel also functions as a dictionary, whose keys are cookie attributes (expires, path, comment, domain, max-age, secure, and version). The method isReservedKey(key) tests whether key is one of the reserved cookie attributes. 4807-7 ch17.F 5/24/01 8:59 AM Page 323 Chapter 17 ✦ Handling Internet Data Caution When sending cookies in an HTTP request, you should only send cookies whose domain is a substring of the host’s name. Otherwise, you might confuse the host. Or, you may send it information it shouldn’t know about, such as passwords for an unrelated site. Moreover, be aware that the Cookie class only handles one value for a given name; setting a new value for that name overwrites the old one. Example: a cookie importer The code in Listing 17-5 provides functions to import cookies from Internet Explorer 5.0 or Netscape. Listing 17-5: CookieMonster.py import Cookie import os def AddMorsel(CookieJar,CookieName,CookieValue,HostString): # Cookie set expects a string, so CookieJar[“name”]=”value” # is ok, but CookieJar[“name”]=Morsel is not ok. # But, cookie get returns a Morsel: CookieJar[CookieName]=CookieValue CookieJar[CookieName][“domain”]=HostString def ParseNetscapeCookies(filename): # Netscape stores cookies in one tab-delimited file, # starting on the fourth line CookieFile=open(filename) CookieLines=CookieFile.readlines()[4:] CookieFile.close() CookieJar=Cookie.SimpleCookie() for CookieLine in CookieLines: CookieParts = CookieLine.strip().split(‘\t’) AddMorsel(CookieJar,CookieParts[-2], CookieParts[-1],CookieParts[0]) return CookieJar def ParseIECookies(dir): CookieJar=Cookie.SimpleCookie() for FileName in os.listdir(dir): # Skip non-cookie files: if len(FileName)<3 or FileName[-3:].upper()!=”TXT”: continue CookieFile=open(os.path.join(dir,FileName)) CookieLines=CookieFile.readlines() CookieFile.close() LineIndex=0 Continued 323 4807-7 ch17.F 324 5/24/01 8:59 AM Page 324 Part III ✦ Networking and the Internet Listing 17-5 (continued) while (LineIndex+2)<len(CookieLines): # :-1 removes trailing newline CookieName=CookieLines[LineIndex][:-1] CookieValue=CookieLines[LineIndex+1][:-1] HostString=CookieLines[LineIndex+2][:-1] AddMorsel(CookieJar,CookieName, CookieValue,HostString) LineIndex+=9 return CookieJar def OutputForHost(CookieJar,Host,attr=None, header=”Set-Cookie:”,sep=”\n”): # Return only cookie values matching the specified host. CookieHeader=”” for OneMorsel in CookieJar.values(): MorselHost=OneMorsel.get(“domain”,None) if (MorselHost==None or Host.find(MorselHost)!=-1): CookieHeader+=OneMorsel.output(attr,header)+sep return CookieHeader if (__name__==”__main__”): Cookies=ParseIECookies( “C:\\Documents and Settings\\Administrator\\Cookies\\”) print OutputForHost(Cookies,”www.thestreet.com/”) Summary Python’s standard libraries help with many common tasks in Internet programming. In this chapter, you: ✦ Parsed robots.txt to create a well-behaved robo-browser. ✦ Handled various e-mail headers. ✦ Imported cookies from a browser cache. In the next chapter, you learn simple, powerful ways to make your Python programs parse HTML and XML. ✦ ✦ ✦ 4807-7 ch18.F 5/24/01 8:59 AM Page 325 18 CHAPTER Parsing XML and Other Markup Languages ✦ ✦ ✦ ✦ In This Chapter Markup language basics Parsing HTML files Example: bold only M arkup languages are a powerful way to store text, complete with formatting and metadata. HTML is the format for about half a billion pages on the World Wide Web. Extensible Markup Language (XML) promises to facilitate data exchange of all types. Python includes standard libraries to parse HTML and XML. This chapter shows you how to use these libraries to create a Web robot, a data importer/exporter, and more. Markup Language Basics HyperText Markup Language, or HTML, is used for nearly all the pages on the World Wide Web. It defines tags to control the formatting of text, graphics, and so forth, by a browser. Extensible Markup Language, or XML, is a tool for data exchange. It includes metadata tags to explain what text items mean. For instance, a person (or program) reading the number “120/80” might not know that it represents a blood pressure, but XML can include tags to make this clear: <blood-pressure>120/80</blood-pressure> Standard general markup language, or SGML, is very general and rarely used. Example: Web robot Parsing XML with SAX Parsing XML with DOM Parsing XML with xmllib ✦ ✦ ✦ ✦ 4807-7 ch18.F 326 5/24/01 8:59 AM Page 326 Part III ✦ Networking and the Internet Tags are for metatext Markup languages are a way to store text together with tags. Tags are metatext that govern the text’s formatting or describe its meaning. Tags are enclosed in brackets <like this>. An opening tag has a corresponding closing tag, which includes a backslash </like this>. The text between (inside) the tags is the text they describe or modify. For example, the following HTML fragment formats a sentence: Presentation tags can set <b>bold</b> type or <i>italics</i> Tags may have attributes to refine their meanings. For example, in HTML, the font tag sets the font, and the color attribute specifies the desired font color: <FONT COLOR=#FFFFFF>white text</FONT> In XML, the information contained between a start tag and its end tag is called an element. Elements store data, and may contain sub-elements. Start and end tags may be collapsed into a single tag for the element: <blood type=”A” color=”red” /> XML data can be stored in the element attributes, or in text. For example, these lines are both reasonable ways to store a person’s name: <Person name=”Bob Hope” /> <Person>Bob Hope</Person> Tag rules In XML, each start tag must have a corresponding end tag. This is a good idea in HTML as well. Many HTML documents do not close all their tags; however, the World Wide Web Consortium (W3C) has proposed a new standard, XHTML, that requires an end tag for each start tag. Tags may be nested within other tags. It is best to close a child tag before closing its parent tag. This is mandatory in XML. It is recommended in HTML, as bad testing may make a Web page render badly: <b>I’m not dead <i>yet</b></i> <b>I’m not dead <i>yet</i></b> Bad! Good! The available tags in HTML are described in the HTML standard. The available tags in XML vary from file to file — because XML is Extensible Markup Language, one extends it by adding new tags. A Document Type Descriptor, or DTD, lists available tags for an XML document. A DTD also includes rules for tag placement — which tags are parents of other tags, and so on. 4807-7 ch18.F 5/24/01 8:59 AM Page 327 Chapter 18 ✦ Parsing XML and Other Markup Languages Namespaces XML files can organize tag and attribute names into namespaces. A name within a namespace takes the form NamespacePrefix:Name. For example, this tag’s local name is Name, and its namespace prefix is Patient: <Patient:Name>Alfred</Patient:Name> A namespace prefix maps to a particular URI, which is often the URL of a Web page explaining the namespace. In general, when parsing XML, you can ignore namespaces. But, they are a handy tool for designing a good XML DTD. Processing XML There are two main ways of processing XML. You can parse the entire document into memory, and navigate the tree of tags and attributes at your leisure. The Document Object Model (DOM) API is an interface for such a parser. Or, you can perform event-driven parsing, handling each tag as you read it from the file. The Simple API for XML (SAX) is an interface for such a parser. (The module xmllib is also an event-driven parser.) Of the two interfaces, I find DOM to be the easiest. Also, DOM can change an XML file without doing direct string manipulation, which gives it big points in my book. One disadvantage of DOM is that it must read the entire XML file into memory upfront, so SAX may be a better choice if you must parse mammoth XML files. Both interfaces are very rich, offering more features than you are likely to need or want; this chapter covers only the core of the two parsing APIs. In order to process XML with Python, you will need a third-party XML parser. The Python distribution for Windows currently includes the Expat non-validating parser. But on UNIX, you will need to build the Expat library, and make sure that the pyexpat module is built as well. Parsing HTML Files The module htmllib defines the HTMLParser class. You create a subclass of HTMLParser to build your own HTML parser. The HTMLParser class is itself a subclass of sgmllib.SGMLParser, but you will probably never use the superclass directly. The HTMLParser constructor takes a formatter, as defined in the formatter module. (See Chapter 17 for information about formatter.) The formatter is used to output the text in the HTML stream. The member formatter is a reference to the parser’s formatter. If you don’t need to use a formatter, you can use a null formatter, as the following subclass does: 327 4807-7 ch18.F 328 5/24/01 8:59 AM Page 328 Part III ✦ Networking and the Internet class SimpleHTMLParser(htmllib.HTMLParser): def __init__(self): # initialize the superclass htmllib.HTMLParser.__init__(self, formatter.NullFormatter()) # ... override other methods here ... HTMLParser methods Call the method feed(text) to send the HTML string text into the parser. You can feed the parser an entire file at one time, or one piece at a time; its behavior is the same. The reset method causes the parser to forget everything it was doing and start over. The close method finishes off the current file; it has the same effect as feeding an end-of-file marker to the parser. If you override close, your subclass’s close method should call the close method of the superclass. The method get_starttag_text returns the text of the most recently opened tag. The method setnomoretags tells the parser to stop processing tags. Similarly, the method setliteral tells the parser to treat the following text literally (ignoring tags). Handling tags To handle a particular tag, define start_xxx and end_xxx methods in your class, where xxx is the tag (in lowercase). A start_xxx method takes one parameter — a list of name-value pairs corresponding to the HTML tag’s arguments. An end_xxx method takes no arguments. You can also handle a tag with a method of the form do_xxx(arguments). The do method is called only if start and end methods are not defined. For example, the following method prints the name of any background image for the page, as defined in a <BODY> tag: def do_body(self,args): for ValTuple in args: # convert arg-name to upper-case if string.upper(ValTuple[0])==”BACKGROUND”: print “Page background image:”,ValTuple[1] Other parsing methods The method handle_data(data) is called to handle standard text that is not part of a tag. Note that handle_data may be called one or several times for one contiguous “block” of data. The method anchor_bgn(href, name, type) is called for the start of an anchor tag, <a>. The method anchor_end is called at the end of an anchor. By default, these methods build up a list of links in the member anchorlist. 4807-7 ch18.F 5/24/01 8:59 AM Page 329 Chapter 18 ✦ Parsing XML and Other Markup Languages The method handle_image(source,alt[,ismap[,align[,width[,height]]]]) is called when an image is encountered. The default implementation simply hands the string alt over to handle_data. The method save_bgn starts storing data, instead of sending it to the formatter via handle_data. The method save_end returns all the data buffered since the call to save_bgn. These calls may not be nested, and save_end may not be called before save_bgn. If a tag handler (of the form start_xxx or do_xxx) is defined for a tag, the method handle_starttag(tag,method,arguments) is called. The parameter tag is the tag name (in lowercase), and method is the start or do method for the tag. By default, handle_starttag calls method, passing arguments. Similarly, the method handle_endtag(tag,method) is called for a tag if you have defined an end method for that tag. The method handle_charref(ref) processes character references of the form &#ref. By default, ref is interpreted as an ASCII character value from 0 to 255, and handed over to handle_data. The method handle_entityref(ref) processes entity references of the form &ref. By default, it looks at the attribute entitydefs, which should be a dictionary mapping from entity names to meanings. The variable htmlentitydefs. entitydefs defines the default entity definitions for HTMLParser. For example, the codes &amp, &apos, &gt, &lt, and &quot translate into the characters & ‘ > < “. The method handle_comment(commenttext) is called when a comment of the form <!-commenttext-> is encountered. The attribute nofill is a flag governing the handling of whitespace. Normally, nofill is false, which causes whitespace to be collapsed. It affects the behavior of handle_data and save_end. Handling unknown or bogus elements The HTMLParser defines methods to handle unknown HTML elements. By default, these methods do nothing; you may want to override them (to report an error, for example). The method unknown_starttag(tag, attributes) is called when a tag with no start method is encountered. (For a given tag, either handle_starttag or unknown_starttag is called.) The method unknown_endtag(tag) is called for unknown end tags. The methods unknown_charref(ref) and unknown_entityref(ref) handle unknown character and entity references, respectively. The method report_unbalanced(tag) is called if the parser encounters a closing tag tag with no corresponding opening tag. 329 4807-7 ch18.F 330 5/24/01 8:59 AM Page 330 Part III ✦ Networking and the Internet Example: Bold Only Listing 18-1 illustrates a simple subclass of HTMLParser that filters out only bold text from an HTML stream. Listing 18-2 shows sample output from the parser. Listing 18-1: BoldOnly.py import htmllib import formatter TEST_HMTL_STRING=”””<html> <title>A poem</title> There once was a <b>poet named Dan</b><br> Who could not make <b>limericks</b> scan<br> He’d be doing just fine<br> Till the <b>very last line</b> Then he’d squeeze in <b>too many syllables</b> and it wouldn’t even rhyme<br> </html>””” class PrintBoldOnly(htmllib.HTMLParser): def __init__(self): # AbstractFormatter hands off text to the writer. htmllib.HTMLParser.__init__(self, formatter.AbstractFormatter(formatter.DumbWriter())) self.Printing=0 # don’t print until we see bold # Note: The bold tag <b> takes no attributes, so the # attributes parameter for start_b will always be an # empty list) def start_b(self,attributes): self.Printing=1 def end_b(self): self.Printing=0 def handle_data(self,text): if (self.Printing): # Call superclass method, pass text to formatter: htmllib.HTMLParser.handle_data(self,text) if (__name__==”__main__”): Test=PrintBoldOnly() Test.feed(TEST_HMTL_STRING) Test.close() 4807-7 ch18.F 5/24/01 8:59 AM Page 331 Chapter 18 ✦ Parsing XML and Other Markup Languages Listing 18-2: BoldOnly output poet named Dan limericks very last line too many syllables Example: Web Robot A robot is a program that browses the World Wide Web automatically. Listing 18-3 is a simple robot. It follows links between pages, and saves pages to the local disk. It overrides several methods of the HTMLParser in order to follow various links. Listing 18-3: Robot.py import import import import import import import htmllib formatter urlparse re os string urllib # Redefine this to a directory where you want to put files ROOT_DIR = “c:\\python20\\robotfiles\\” # Web page file extensions that usually return HTML HTML_EXTENSION_DICT={“”:1,”HTM”:1,”HTML”:1,”PHTML”:1,”SHTML”:1, ”PHP”:1,”PHP3”:1,”HTS”:1,”ASP”:1,”PL”:1,”JSP”:1,”CGI”:1} # Use this string to limit the robot to one site — only URLs # that contain this string will be retrieved. If this is null, # the robot will attempt to pull down the whole WWW. REQUIRED_URL_STRING=”kibo.com” # Compile a regular expression for case-insensitive matching of # the required string RequiredUrlRE = re.compile(re.escape(REQUIRED_URL_STRING), re.IGNORECASE) # Keep track of all the pages we have visited in a dictionary, # so that we don’t hit the same page repeatedly. VisitedURLs={} # Queue of target URLs TargetURLList=[“http://www.kibo.com/index.html”] Continued 331 4807-7 ch18.F 332 5/24/01 8:59 AM Page 332 Part III ✦ Networking and the Internet Listing 18-3 (continued) def AddURLToList(NewURL): # Skip duplicate URLs if (VisitedURLs.has_key(NewURL)): return # Skip URLs that don’t contain the proper substring if (not RequiredUrlRE.search(NewURL)): return # Add URL to the target list TargetURLList.append(NewURL) # Chop file-extension from the end of a URL def GetExtensionFromString(FileString): DotChunks=string.split(FileString,”.”) if len(DotChunks)==1: return “” LastBlock=DotChunks[-1] # Take stuff after the last . if string.find(LastBlock,”/”)!=-1: return “” if string.find(LastBlock,”\\”)!=-1: return “” return string.upper(LastBlock) class HTMLRobot(htmllib.HTMLParser): def StartNewPage(self,BaseURL): self.BaseURL=BaseURL def __init__(self): # Initialize the master class htmllib.HTMLParser.__init__( self,formatter.NullFormatter()) def do_body(self,args): # Retrieve background image, if any for ValTuple in args: if string.upper(ValTuple[0])==”BACKGROUND”: ImageURL = urlparse.urljoin( self.BaseURL, ValTuple[1]) AddURLToList(ImageURL) def do_embed(self,args): # Handle embedded content for ValTuple in args: if string.upper(ValTuple[0])==”SRC”: self.HandleAnchor(ValTuple[1]) def do_area(self,args): # Handle areas inside an imagemap for ValTuple in args: if string.upper(ValTuple[0])==”HREF”: self.HandleAnchor(ValTuple[1]) def handle_image(self, source, alt, ismap, align, width, height): # Retrieve images ImageURL = urlparse.urljoin(self.BaseURL, source) AddURLToList(ImageURL) def anchor_bgn(self,TempURL,name,type): # Anchors (links). Skip mailto links. 4807-7 ch18.F 5/24/01 8:59 AM Page 333 Chapter 18 ✦ Parsing XML and Other Markup Languages if TempURL[0:7].upper() == “MAILTO:”: return NewURL=urlparse.urljoin(self.BaseURL,TempURL) AddURLToList(NewURL) def do_frame(self,args): # Handle a sub-frame as a link for ValTuple in args: if string.upper(ValTuple[0])==”SRC”: self.anchor_bgn(ValTuple[1],””,””) def do_option(self,args): for ValTuple in args: if string.upper(ValTuple[0])==”VALUE”: # This might be a Webpage... TheExtension = \ GetExtensionFromString(ValTuple[1]) if HTML_EXTENSION_DICT.has_key(TheExtension): self.anchor_bgn(ValTuple[1],””,””) if (__name__==”__main__”): Parser = HTMLRobot() while (len(TargetURLList)>0): # Take the next URL off the list NextURL = TargetURLList[0] del TargetURLList[0] VisitedURLs[NextURL]=1 # flag as visited print “Retrieving:”,NextURL # Parse the URL, and decide whether # we think it’s HTML or not: URLTuple=urlparse.urlparse(NextURL,”http”,0) TheExtension=GetExtensionFromString(URLTuple[2]) # Get a local filename; make directories as needed TargetPath=os.path.normpath(ROOT_DIR+URLTuple[2]) # If no extension, assume it’s a directory and # retrieve index.html. if (TheExtension==””): TargetDir=TargetPath TargetPath=os.path.normpath( TargetPath+”/index.html”) else: (TargetDir,TargetFile)=os.path.split(TargetPath) try: os.makedirs(TargetDir) except: pass # Ignore exception if directory exists if HTML_EXTENSION_DICT.has_key(TheExtension): # This is HTML - retrieve it to disk and then # feed it to the parser URLFile=urllib.urlopen(NextURL) HTMLText = URLFile.read() URLFile.close() HTMLFile=open(TargetPath,”w”) HTMLFile.write(HTMLText) Continued 333 4807-7 ch18.F 334 5/24/01 8:59 AM Page 334 Part III ✦ Networking and the Internet Listing 18-3 (continued) HTMLFile.close() Parser.StartNewPage(NextURL) Parser.feed(HTMLText) Parser.close() else: # This isn’t HTML - save to disk urllib.urlretrieve(NextURL,TargetPath) Parsing XML with SAX SAX is a standard interface for event-driven XML parsing. Parsers that implement SAX are available in Java, C++, and (of course) Python. The module xml.sax is the overseer of SAX parsers. The method xml.sax.parse(xmlfile,contenthandler[,errorhandler]) creates a SAX parser and parses the specified XML. The parameter xmlfile can be either a file or the name of a file to read from. The parameter contenthandler must be a ContentHandler object. If specified, errorhandler must be a SAX ErrorHandler object. If no error handler is provided and an error occurs, the parser will raise a SAXParseException if it encounters errors. Similarly, the method parseString(xmlstring,contenthandler[,errorhandler]) parses XML from the supplied string xmlstring. Parsing XML with SAX generally requires you to create your own ContentHandler, by subclassing xml.sax.ContentHandler. Your ContentHandler handles the particular tags and attributes of your flavor(s) of XML. Using a ContentHandler A ContentHandler object provides methods to handle various parsing events. Its owning parser calls ContentHandler methods as it parses the XML file. The method setDocumentLocator(locator) is normally called first. The methods startDocument and endDocument are called at the start and the end of the XML file. The method characters(text) is passed character data of the XML file via the parameter text. The ContentHandler is called at the start and end of each element. If the parser is not in namespace mode, the methods startElement(tag, attributes) and endElement(tag) are called; otherwise, the corresponding methods startElementNS and endElementNS are called. Here, tag is the element tag, and attributes is an Attributes object. 4807-7 ch18.F 5/24/01 8:59 AM Page 335 Chapter 18 ✦ Parsing XML and Other Markup Languages The methods startPrefixMapping(prefix,URI) and endPrefixMapping(prefix) are called for each namespace mapping; normally, namespace processing is handled by the XMLReader itself. For a given prefix, endPrefixMethod will be called after the corresponding call to startPrefixMapping, but otherwise the order of calls is not guaranteed. The method ignorableWhitespace(spaces) is called for a string spaces of whitespace. The method processingInstruction(target,text) is called when a processing instruction (other than an XML declaration) is encountered. The method skippedEntity(entityname) is called when the parser skips any entity. A ContentHandler receives an Attributes object in calls to the startElement method. The Attributes object wraps a dictionary of attributes (keys) and their values. The method getLength returns the number of attributes. The methods items, keys, kas_key, and values wrap the corresponding dictionary methods. The method getValue(name) returns the value for an attribute name; if namespaces are active, the method getValueByQName(name) returns the value for a qualified attribute name. Example: blood-type extractor Listing 18-4 uses a SAX parser to extract a patient’s blood type from the same exam data XML uses in Listing 18-5 and Listing 18-6. Listing 18-4: BloodTypeSax.py import xml.sax import cStringIO SAMPLE_DATA = “””<?xml version=”1.0”?> <exam date=”12/11/99”> <patient>Pat</patient> <bloodtype>B</bloodtype> </exam >””” class ExamHandler(xml.sax.ContentHandler): def __init__(self): self.CurrentData=”” self.BloodType=”” def characters(self,text): if self.CurrentData==”bloodtype”: self.BloodType+=text # We use the non-namespace-aware element handlers: def startElement(self,tag,attributes): self.CurrentData=tag def endElement(self,tag): Continued 335 4807-7 ch18.F 336 5/24/01 8:59 AM Page 336 Part III ✦ Networking and the Internet Listing 18-4 (continued) if self.CurrentData==”bloodtype”: print “Blood type:”,self.BloodType self.CurrentData=”” if (__name__==”__main__”): # create an XMLReader MyParser = xml.sax.make_parser() # turn off namepsaces MyParser.setFeature(xml.sax.handler.feature_namespaces, 0) # override the default ContextHandler Handler=ExamHandler() MyParser.setContentHandler(Handler) # Build and parse an InputSource StringFile=cStringIO.StringIO(SAMPLE_DATA) MySource = xml.sax.InputSource(“1”) MySource.setByteStream(StringFile) MyParser.parse(MySource) Using parser (XMLReader) objects The base parser class is xml.sax.xmlreader.XMLReader. It is normally not necessary to instantiate parser objects directly. However, you can access a parser to exercise tighter control on XML parsing. The method xml.sax.make_parser([parserlist]) creates and returns an XML parser. If you want to use a specific SAX parser (such as Expat), pass the name of its module in the parserlist sequence. The module in question must define a create_parser function. Once you have an XML parser, you can call its method parse(source), where source is a filelike object, a URL, or a file name. An XML parser has properties and features, which can be set and queried by name. For example, the following lines check and toggle namespace mode for a parser: >>> MyParser=xml.sax.make_parser() >>> MyParser.getFeature(\ “http://xml.org/sax/features/namespaces”) 0 >>> # Activate namespace processing >>> MyParser.setFeature(\ “http://xml.org/sax/features/namespaces”,1) The features and properties available vary from parser to parser. 4807-7 ch18.F 5/24/01 8:59 AM Page 337 Chapter 18 ✦ Parsing XML and Other Markup Languages An XMLReader has several helper classes. You can access the parser’s ContentHandler with the methods getContentHandler and setContentHandler(Handler). Similarly, you can access the parser’s ErrorHandler (with getErrorHandler and setErrorHandler), its EntityResolver, and its DTDHandler. The helper classes let you customize the parser’s behavior further. ErrorHandler An ErrorHandler implements three methods to handle errors: error, fatalError, and warning. Each method takes a SAXParseException as its single parameter. DTDHandler A DTDHandler handles only notation declarations and unparsed entity declarations. The method notationDecl(name,PublicID,SystemID) is called when a notation declaration is encountered. The method unparsedEntityDecl(name,PublicID,SystemID,text) is called when an unparsed entity declaration is encountered. EntityResolver The XMLReader calls the EntityResolver to handle external entity references. The method resolveEntity(PublicID,SystemID) is called for each such reference — it returns either the system identifier (as a string), or an InputSource. Locator Most XMLReaders supply a locator to their ContentHandler by calling its setDocumentLocator method. The locator should only be called by the ContentHandler in the context of a parsing method (such as characters). The locator provides the current location, via methods getColumnNumber, getLineNumber, getPublicId, and getSystemId. SAX exceptions The base exception is SAXException. It is extended by SAXParseException, SAXNotRecognizedException, and SAXNotSupportedException. The constructors for SAXNotSupportedException and SAXNotRecognizedException take two parameters: an error string and (optionally) an additional exception object. The SAXParseException constructor requires these parameters, as well as a locator. The message and exception associated with a SAXException can be retrieved by the methods getMessage and getException, respectively. 337 4807-7 ch18.F 338 5/24/01 8:59 AM Page 338 Part III ✦ Networking and the Internet Parsing XML with DOM The DOM API parses an entire XML document, and stores a DOM (a tree representation of the document) in memory. It is a very convenient way to parse, although it does require more memory than SAX. In addition, you can manipulate the DOM itself, and then write out the new XML document. This is a relatively painless way to make changes to XML documents. A DOM is made up of nodes. Each element, each attribute, and even each comment is a node. The most important node is the document node, which represents the document as a whole. The module xml.dom.minidom provides a simple version of the DOM interface. It provides two functions, parse(file[,parser]) or parseString(XML[,parser]), to parse XML and return a DOM. (Here parser, if supplied, must be a SAX parser object — minidom uses SAX internally to generate its DOM.) DOM nodes A node object has a type, represented by the integer attribute nodeType. The valid node types are available as members of xml.dom.minidom.Node, and include DOCUMENT_NODE, ELEMENT_NODE, ATTRIBUTE_NODE, and TEXT_NODE. A node can have a parent (given by its parentNode member), and a list of children (stored in its childNodes member). You can add child nodes by calling appendChild(NewChild), or insertBefore(NewChild,OldChild). You can also remove children by calling removeChild(OldChild). For example: >>> DOM=xml.dom.minidom.parse(“Mystic Mafia.xml”) # Build DOM >>> print DOM.parentNode # The document node has no parent None >>> print DOM.childNodes [<DOM Element: rdf at 10070740>] >>> print DOM.childNodes[0].childNodes [<DOM Text node “\n”>, <DOM Text node “\n”>, <DOM Text node “ “>, <DOM Element: rdf:Description at 10052084>, <DOM Text node “\n”>] Elements, attributes, and text An element has a name, given by its member tagName. If the element is part of a namespace, prefix holds its namespace’s name, localName within the namespace, and namespaceURI is the URL of the namespace definition. You can retrieve an 4807-7 ch18.F 5/24/01 8:59 AM Page 339 Chapter 18 ✦ Parsing XML and Other Markup Languages element’s attribute values with the method getAttribute(AttributeName), set attribute values with setAttribute(AttributeName, Value), and remove attributes with the method removeAttribute(AttributeName). The text of an element is stored in a child node of type TEXT_NODE. A text node has an attribute, data, containing its text as a string. For example, this code examines and edits an element: >>> print TagNode.tagName,TagNode.prefix rdf:Description rdf >>> print TagNode.localName,TagNode.namespaceURI Description http://www.w3.org/1999/02/22-rdf-syntax-ns# >>> TagNode.getAttribute(“type”) # Value is Unicode u’catalog’ >>> CNode.setAttribute(“arglebargle”,”test”) >>> CNode.getAttribute(“arglebargle”) ‘test’ >>> CNode.removeAttribute(“arglebargle”) >>> # Getting a nonexistent attribute returns “” >>> CNode.getAttribute(“arglebargle”) ‘’ The document node (DOM) A document node, or DOM, provides a handy method, getElementsByTagName(Name), which returns a list of all the element nodes with the specified name. This is a quick way to find the elements you care about, without ever iterating through the other nodes in the document. A DOM also provides methods to create new nodes. The method createElement(TagName) creates a new element node, createTextNode(Text) creates a new text node, etc. The method toxml returns the DOM as an XML string. When you are finished with a DOM, call its method unlink to clean it up. Otherwise, the memory used by the DOM may not get garbage-collected until your program terminates. Example: data import and export with DOM XML is great for data interchange. Listing 18-5 is an example of XML’s power: It exports data from a relational database to an XML file, and imports XML back into the database. It uses the mxODBC module for database access. This test code assumes the existence of an EMPLOYEE table (see Chapter 14 for the table’s definition, and more information on the Python DB API). 339 4807-7 ch18.F 340 5/24/01 8:59 AM Page 340 Part III ✦ Networking and the Internet Listing 18-5: XMLDB.py import xml.dom.minidom import ODBC.Windows # Replace for your OS as needed import sys import traceback IMPORTABLE_XML = “””<?xml version=”1.0”?><tabledata><row> <EMPLOYEE_ID>55</EMPLOYEE_ID><FIRST_NAME>Bertie</FIRST_NAME> <LAST_NAME>Jenkins</LAST_NAME><MANAGER_ID></MANAGER_ID> </row></tabledata>””” def ExportXMLFromTable(Cursor): # We build up a DOM tree programatically, then # convert the DOM to XML. We never have to process # the XML string directly (Hooray for DOM!) DOM=xml.dom.minidom.Document() TableElement=DOM.createElement(“tabledata”) DOM.appendChild(TableElement) while (1): DataRow=Cursor.fetchone() if DataRow==None: break # There is no more data RowElement=DOM.createElement(“row”) TableElement.appendChild(RowElement) for Index in range(len(Cursor.description)): ColumnName=Cursor.description[Index][0] ColumnElement=DOM.createElement(ColumnName) RowElement.appendChild(ColumnElement) ColumnValue=DataRow[Index] if (ColumnValue): TextNode=DOM.createTextNode(\ str(DataRow[Index])) ColumnElement.appendChild(TextNode) print DOM.toxml() def ImportXMLToTable(Cursor,XML,TableName): # Build up the SQL statement corresponding to the XML DOM=xml.dom.minidom.parseString(XML) DataRows=DOM.getElementsByTagName(“row”) for RowElement in DataRows: InsertSQL=”INSERT INTO %s (“%TableName for ChildNode in RowElement.childNodes: if ChildNode.nodeType==\ xml.dom.minidom.Node.ELEMENT_NODE: InsertSQL+=”%s,”%ChildNode.tagName InsertSQL=InsertSQL[:-1] # Remove trailing comma InsertSQL+=”) values (“ for ChildNode in RowElement.childNodes: if ChildNode.nodeType==\ xml.dom.minidom.Node.ELEMENT_NODE: ColumnValue=GetNodeText(ChildNode) InsertSQL+=”%s,”%SQLEscape(ColumnValue) 4807-7 ch18.F 5/24/01 8:59 AM Page 341 Chapter 18 ✦ Parsing XML and Other Markup Languages InsertSQL=InsertSQL[:-1] # Remove trailing comma InsertSQL+=”)” Cursor.execute(str(InsertSQL)) def SQLEscape(Value): if (Value in [None,””]): return “Null” else: return “‘%s’”%Value.replace(“‘“,”’’”) def GetNodeText(ElementNode): # Concatenate all text child-nodes into one large string. # (The normalize() method, available in version 2.1, makes # this a little easier by conglomerating adjacent # text nodes for us) NodeText=”” for ChildNode in ElementNode.childNodes: if ChildNode.nodeType==xml.dom.minidom.Node.TEXT_NODE: NodeText+=ChildNode.data return NodeText if (__name__==”__main__”): print “Testing XML export...” # Replace this line with your database connection info: Conn=ODBC.Windows.connect(“AQUA”,”aqua”,”aqua”) Cursor=Conn.cursor() Cursor.execute(“select * from EMPLOYEE”) print ExportXMLFromTable(Cursor) # Delete employee 55 so that we can import him again Cursor.execute(“DELETE FROM EMPLOYEE WHERE\ EMPLOYEE_ID = 55”) print “Testing XML import...” ImportXMLToTable(Cursor,IMPORTABLE_XML,”EMPLOYEE”) # Remove this line if your database does not have # transaction support: Conn.commit() Parsing XML with xmllib The module xmllib defines a single class, XMLParser, whose methods are similar to that of htmllib.HTMLParser. You can define start and end handlers for any tag. Listing 18-6 is a simple example that parses a patient’s blood type from examination data. Caution Unlike xml.sax and xml.dom, xmllib doesn’t require any extra modules to be built. Also, it is quite simple, and similar to htmllib. However, it is not a fast parser, and is deprecated as of Version 2.0. 341 4807-7 ch18.F 342 5/24/01 8:59 AM Page 342 Part III ✦ Networking and the Internet Note This example stores the blood type using one or more calls to handle_data. Strings may be passed to handle_data all at once or in several pieces. Listing 18-6: BloodType.py import xmllib SAMPLE_DATA = “””<?xml version=”1.0”?> <exam date=”5/13/99”> <patient>Pat</patient> <bloodtype>B</bloodtype> </exam >””” class ExamParser(xmllib.XMLParser): def __init__(self): xmllib.XMLParser.__init__(self) self.CurrentData=”” # Track current data item self.BloodType=”” def start_bloodtype(self,args): self.CurrentData=”blood” def end_bloodtype(self): if (self.CurrentData==”blood”): print “Blood type:”,self.BloodType self.CurrentData=”” def handle_data(self,text): if (self.CurrentData==”blood”): self.BloodType+=text if (__name__==”__main__”): MyParser = ExamParser() MyParser.feed(SAMPLE_DATA) MyParser.close() Elements and attributes The XMLParser attribute elements is a dictionary of known tags. If you subclass XMLParser with a parser that handles a particular tag, then that tag should exist as a key in elements. The corresponding value is a tuple (StartHandler,EndHandler), where StartHandler and EndHandler are functions for handling the start and end of that tag. Normally, you don’t need to access elements directly, as handlers of the form start_xxx and end_xxx are inserted automatically. The attribute attributes is a dictionary tracking the valid attributes for tags. The keys in attributes are known tags. The values are dictionaries that map all valid attributes for the tag to a default value (or to None, if there is no default value). If any other attribute is encountered in parsing, the method syntax_error is called. By default, attributes is an empty dictionary, and any attributes are permitted for any tag. 4807-7 ch18.F 5/24/01 8:59 AM Page 343 Chapter 18 ✦ Parsing XML and Other Markup Languages XML handlers XMLParser defines various methods to handle XML elements. These methods do nothing by default, and are intended to be overridden in a subclass. The method handle_xml(encoding,standalone) is called when the <?xml?> tag is parsed. The parameters encoding and standalone equal the corresponding attributes in the tag. The method handle_doctype(root_tag,public_id,sys_id,data) is called when the <!DOCTYPE> tag is parsed. The parameters root_tag, public_id, sys_id, and data are the root tag name, the DTD public identifier, the system identifier, and the unparsed DTD contents, respectively. The method handle_cdata(text) is called when a CDATA tag of the form <!CDATA[text]> is encountered. (Normal data is passed to handle_data.) The method handle_proc(name,text) is called when a processing instruction of the form <?name text?> is encountered. The method handle_special(text) is called for declarations of the form <!text>. Other XMLParser members The method syntax_error(errormessage) is called when unparsable XML is encountered. By default, this method raises a RuntimeError exception. The method translate_references(text) translates all entity and character references in text, and returns the resulting string. The method getnamespace returns a dictionary mapping abbreviation from the current namespace to URIs. Summary You can easily parse HTML by subclassing the standard parser. There are several varieties of parsers for XML, which you can customize to handle any kind of document. In this chapter, you: ✦ Parsed HTML with and without an output-formatter. ✦ Built a robot to automatically retrieve Web pages. ✦ Parsed and generated XML files for data exchange. In the next chapter, you’ll meet Tkinter, Python’s de facto standard library for user interfaces. ✦ ✦ ✦ 343 4807-7 ch18.F 5/24/01 8:59 AM Page 344 4807-7 PO4.F 5/24/01 9:00 AM Page 345 P User Interfaces and Multimedia A R T IV ✦ ✦ ✦ ✦ Chapter 19 Tinkering with Tkinter Chapter 20 Using Advanced Tkinter Widgets Chapter 21 Building User Interfaces with wxPython Chapter 22 Using Curses Chapter 23 Building Simple Command Interpreters Chapter 24 Playing Sound ✦ ✦ ✦ ✦ 4807-7 PO4.F 5/24/01 9:00 AM Page 346 4807-7 ch19.F 5/24/01 9:00 AM Page 347 19 CHAPTER Tinkering with Tkinter ✦ ✦ ✦ ✦ In This Chapter T kinter is a package used for building a graphical user interface (GUI) in Python. It runs on many operating systems, including UNIX, Windows, and Macintosh. Tkinter is the de-facto standard GUI library for Python, and is often bundled with it. Tkinter is very easy to use; it is built on top of the high-level scripting language Tcl. Getting Your Feet Wet If you’re dying to see Tkinter in action, the program shown in Listing 19-1 should provide some instant gratification. It displays some text in a window. Notice how little code it takes — such are the joys of Tkinter! Creating a GUI Using common options Gathering user input Using text widgets Building menus Using Tkinter dialogs Handling colors and fonts Drawing graphics Listing 19-1: HelloWorld.py Using timers import Tkinter # Create the root window: root=Tkinter.Tk() # Put a label widget in the window: LabelText=”Ekky-ekky-ekky-ekky-z’Bang, zoomBoing,\ z’nourrrwringmm” LabelWidget=Tkinter.Label(RootWindow,text=Labe lText) # Pack the label (position and display it): LabelWidget.pack() # Start the event loop. This call won’t return # until the program ends: RootWindow.mainloop() ✦ Run the code, and you’ll see something resembling the screenshot shown in Figure 19-1. ✦ ✦ ✦ 4807-7 ch19.F 348 5/24/01 9:00 AM Page 348 Part IV ✦ User Interfaces and Multimedia Figure 19-1: Greetings from Tkinter Note On Windows, Tkinter applications look more professional when you run them with pythonw.exe instead of python.exe. Giving a script a .pyw extension sends it to pythonw instead of python. Pythonw does not create a console window; the disadvantage of this is that you can’t see anything printed to sys.stdout and sys.stderr. Creating a GUI To use Tkinter, import the Tkinter module. Many programmers import it into the local namespace (from Tkinter import *); this is less explicit, but it does save some typing. This chapter’s examples don’t import Tkinter into the local namespace, in order to make it obvious when they use Tkinter. Building an interface with widgets A user interface contains various widgets. A widget is an object displayed onscreen with which the user can interact. (Java calls such things components, and Microsoft calls them controls.) Tkinter provides a button widget (Tkinter.Button), a label widget (Tkinter.Label), and so on. Most widgets are displayed on a parent widget, or owner. The first argument to a widget’s constructor is its parent widget. 4807-7 ch19.F 5/24/01 9:00 AM Page 349 Chapter 19 ✦ Tinkering with Tkinter A Toplevel widget is a special widget with no parent; it is a top-level window in its own right. Most applications need only one Toplevel widget — the root widget created when you call Tkinter.Tk(). For example, a frame is a widget whose purpose in life is to contain other widgets. Putting related widgets in one frame is a great way to group them onscreen: MainWindow=Tkinter.Tk() # Create a top-level window UpperFrame=Tkinter.Frame(MainWindow) # The label and the button both live inside UpperFrame: UpperLabel=Tkinter.Label(Frame) UpperButton=Tkinter.Button(Frame) Widget options Widgets have options (or attributes) that control their look and behavior. Some options are used by many widgets. For example, most widgets have a background option, specifying the widget’s normal background color. Other options are specific to a particular kind of widget. For example, a button widget has a command option, whose value is a function to call (without arguments) when the button is clicked. You can access options in various ways: # You can set options in the constructor: NewLabel=Tkinter.Label(ParentFrame,background=”gray50”) # You can access options dictionary-style (my favorite!) NewLabel[“background”]=”#FFFFFF” # You can set options with the config method: NewLabel.config(background=”blue”) # You can retrieve an option’s current value: CurrentColor=NewLabel[“background”] # Another way to get the current value: CurrentColor=NewLabel.cget(“background”) A few option names are, coincidentally, reserved words in Python. When necessary, append an underscore to such option names: # “from” is a reserved word. Use from_ in code: VolumeWidget=Tkinter.Scale(ParentFrame,from_=0,to=200) # Use “from” when passing the option name as a string: VolumeWidget[“from”]=20 # “from_” is *not* ok here See “Using Common Options” for an overview of the most useful widget options. Laying Out Widgets The geometry manager is responsible for positioning widgets onscreen. The simplest geometry manager is the packer. The packer can position a widget on the left 349 4807-7 ch19.F 350 5/24/01 9:00 AM Page 350 Part IV ✦ User Interfaces and Multimedia (Tkinter.LEFT), right, top, or bottom side of its parents. You invoke the packer by calling the pack method on a widget. The grid geometry manager divides the parent widget into a grid, and places each child widget on a square of the grid. You invoke the grid geometry manager by calling the grid(row=x,column=y) method on a widget. Grid square numbering starts with 0. You can also position a widget precisely using place. However, using place is recommended only for perfectionists and masochists! If you use the placer, then whenever you add a widget to your design, you’ll need to reposition all the other widgets. Different geometry managers don’t get along well — if you pack one child widget and grid another, Tkinter may enter a catatonic state. You can use pack and grid in the same program, but not within the same parent widget! Remember to call pack, grid, or place on every widget. Otherwise, the widget will never be displayed, making it rather difficult to click on! Note Packer options Following are options you can pass to the pack method. These options override the default packing. The default packing lays widgets out from top to bottom within their parent (side=TOP). Each widget is centered within the available space (anchor=CENTER). It does not expand to fill its space (expand=NO), and it has no extra padding on the sides (padx=pady=0). side Passing a side option to pack places the widget on the specified side of its parent. Valid values are LEFT, RIGHT, TOP, and BOTTOM. The default is TOP. If two widgets are both packed on one side of a parent, the first widget packed is the closest to the edge: Label1=Tkinter.Label(root,text=”PackedLast”) Label2=Tkinter.Label(root,text=”PackedFirst”) Label2.pack(side=Tkinter.LEFT) # leftmost! Label1.pack(side=Tkinter.LEFT) # Placed to the right of label2 Mixing LEFT/RIGHT with TOP/BOTTOM in one parent widget often yields creepylooking results. When packing many widgets, it’s generally best to use intermediate frame widgets, or use the grid geometry manager. fill, expand Pass a value of YES for expand to let a widget expand to fill all available space. Pass either X, Y, or BOTH for fill to specify which dimensions will expand. These options are especially useful when a user resizes the window. For example, the following code creates a canvas that stretches to the edges of the window, and a status bar (at the bottom) that stretches horizontally: 4807-7 ch19.F 5/24/01 9:00 AM Page 351 Chapter 19 ✦ Tinkering with Tkinter DrawingArea=Tkinter.Canvas(root) DrawingArea.pack(expand=Tkinter.YES,fill=Tkinter.BOTH) StatusBar=Tkinter.Label(root,text=”Ready.”) StatusBar.pack(side=Tkinter.BOTTOM,expand=\ Tkinter.YES,fill=Tkinter.X) anchor If the widget has more screen space than it needs, the anchor option determines where the widget sits, within its allotted space. This does not affect widgets with fill=BOTH. Valid values are compass directions (N, NW, W, SW, S, SE, E, NE) and CENTER. padx,pady These options give a widget some additional horizontal or vertical “elbow room.” Putting a little space between buttons makes them more readable, and makes it harder to click the wrong one: Button1=Tkinter.Button(root,text=”Fire death ray”, command=FireDeathRay) # 10 empty pixels on both sides: Button1.pack(side=Tkinter.LEFT,padx=10) Button2=Tkinter.Button(root,text=”Send flowers”, command=PatTheBunny) # 10+10=20 pixels between buttons: Button2.pack(side=Tkinter.LEFT,padx=10) Grid options Following are options to pass to the grid method. You should specify a row and a column for every widget; otherwise, things get confusing. row, column Pass row and column options to specify which grid square your widget should live in. The numbering starts at 0; you can always add new rows and columns. For example, the following code lays out some buttons to look like a telephone’s dial pad: for Digit in range(9): Tkinter.Button(root,text= Digit+1).grid(row=Digit/3,\ column=Digit%3) sticky This option specifies which side of the square the widget should “stick to.” It is similar to anchor (for the packer). Valid values are compass directions and CENTER. You can combine values to stretch the widget within its cell. For example, the following button fills its grid cell: 351 4807-7 ch19.F 352 5/24/01 9:00 AM Page 352 Part IV ✦ User Interfaces and Multimedia BigButton=Tkinter.Button(root,text=”X”) # Using “from Tkinter import *” would let this next line # be much less messy: BigButton.grid(row=0,column=0,sticky=Tkinter.W+Tkinter.E+\ Tkinter.N+Tkinter.S) columnspan,rowspan These options let you create a big widget (one that spans multiple rows or columns). Example: Breakfast Buttons Listing 19-2 presents a beefier Tkinter program. It provides a food menu, with several buttons you can click to build up a complete breakfast. Your selection is displayed on a multiline label. Figure 19-2 shows the resulting user interface. This example initializes widgets in several different ways. In practice, you’ll want to do it the same way every time. (Personally, I like the pattern for the “Spam” button, and I hate the pattern for the “Beans” button.) Listing 19-2: FoodChoice.py import Tkinter # In Tkinter, a common practice is to subclass Tkinter.Frame, and make # the subclass represent “the application itself”. This is # convenient (although, in some cases, the separation # between logic and UI should be clearer). FoodWindow is our application: class FoodWindow(Tkinter.Frame): def __init__(self): # Call the superclass constructor explicitly: Tkinter.Frame.__init__(self) self.FoodItems= self.CreateChildWidgets() def CreateChildWidgets(self): ButtonFrame=Tkinter.Frame(self) # The fill parameter tells the Packer that this widget should # stretch horizontally to fill its parent widget: ButtonFrame.pack(side=Tkinter.TOP,fill=Tkinter.X) # Create a button, on the button frame: SpamButton=Tkinter.Button(ButtonFrame) # Button[“text”] is the button label: SpamButton[“text”]=”Spam” # Button[“command”] is the function to execute (without arguments) # when someone clicks the button: SpamButton[“command”]=self.BuildButtonAction(“Spam”) SpamButton.pack(side=Tkinter.LEFT) 4807-7 ch19.F 5/24/01 9:00 AM Page 353 Chapter 19 ✦ Tinkering with Tkinter # You can specify most options by passing keyword-arguments # to the widget’s constructor: EggsAction=self.BuildButtonAction(“Eggs”) EggsButton=Tkinter.Button(ButtonFrame,text=”Eggs”,command=EggsAction) # This is the second widget packed on the LEFT side of ButtonFrame, so # it goes to the right of the “Spam” button: EggsButton.pack(side=Tkinter.LEFT) # Some people like to do everything all in one go: Tkinter.Button(ButtonFrame,text=”Beans”,\ command=self.BuildButtonAction(“Beans”)).pack(side=Tkinter.LEFT) # You can also set widget options with the “config” method: SausageButton=Tkinter.Button(ButtonFrame) SausageAction=self.BuildButtonAction(“Sausage”) SausageButton.config(text=”Sausage”,command=SausageAction) SausageButton.pack(side=Tkinter.LEFT) # It’s often good for parent widgets to keep references to their # children. Here, we keep a reference (self.FoodLabel) to the label, so # we can change it later: self.FoodLabel=Tkinter.Label(self, wraplength=190,\ relief=Tkinter.SUNKEN,borderwidth=2,text=””) self.FoodLabel.pack(side=Tkinter.BOTTOM,pady=10,fill=Tkinter.X) # Packing top-level widgets last often saves some repainting: self.pack() def ChooseFood(self,FoodItem): # Add FoodItem to our list of foods, and build a nice # string listing all the food choices: self.FoodItems.append(FoodItem) LabelText=”” TotalItems=len(self.FoodItems) for Index in range(TotalItems): if (Index>0): LabelText+=”, “ if (TotalItems>1 and Index==TotalItems-1): LabelText+=”and “ LabelText+=self.FoodItems[Index] self.FoodLabel[“text”]=LabelText # Lambda forms are a convenient way to define commands, especially when # several buttons do similar things. I put the lambda-construction in its # own function, to prevent duplicated code for each button: def BuildButtonAction(self,Label): # Note: Inside a lambda definition, you can’t see any names # from the enclosing scope. So, we must pass in self and Label: Action=lambda Food=self,Text=Label: Food.ChooseFood(Text) return Action if (__name__==”__main__”): MainWindow=FoodWindow() MainWindow.mainloop() 353 4807-7 ch19.F 354 5/24/01 9:00 AM Page 354 Part IV ✦ User Interfaces and Multimedia Figure 19-2: Responding to buttons Using Common Options The following sections provide an overview of the most commonly used widget options, organized by category. Those options that apply to button widgets also apply to check button and radio button widgets. Color options The following options control the colors of a widget: background, foreground Background and foreground colors. A synonym for background is bg; a synonym for foreground is fg. activebackground, activeforeground For a button or menu, these options provide colors used when the widget is active. disabledforeground Alternative foreground color for a disabled button or menu. selectforeground, selectbackground highlightcolor, highlightbackground Alternative colors for the selected element(s) of a Canvas, Entry, Text, or Listbox widget. Colors for the rectangle around a menu. 4807-7 ch19.F 5/24/01 9:00 AM Page 355 Chapter 19 ✦ Tinkering with Tkinter Size options The following options govern the size and shape of a widget. width Widget width, as measured in average-sized characters of the widget’s font. A value of 0 (the default) makes the widget just large enough to hold its current text. height Widget height, as measured in average-sized characters. padx, pady Amount of extra internal horizontal or vertical padding, in pixels. Generally ignored if the widget is displaying a bitmap or image. Appearance options The following options, together with the color and size options, control a widget’s appearance: text Text to display in the widget. image Image for display in a button or label. If an image is supplied, any text option is ignored. Pass an empty string for image to remove an image. relief Specifies a 3-D border for the widget. Valid values are FLAT, GROOVE, RAISED, RIDGED, SOLID, and SUNKEN. borderwidth Width of the widget’s 3-D border, in pixels. font The font to use for text drawn inside the widget. Behavior options The following options affect the behavior of a widget: command Specifies a function to be called, without parameters, when the widget is clicked. Applies to buttons, scales, and scrollbars. state Sets a widget state to NORMAL, ACTIVE, or DISABLED. A DISABLED widget ignores user input, and (usually) appears grayed-out. The ACTIVE state changes the widget’s color (using the activebackground and activeforeground colors). underline Widgets can use keyboard shortcuts. The underline option is the index of a letter in the widget’s text; this letter becomes the “hot key” for using the widget. takefocus If true, the widget is part of the “tab order” — when you cycle through widgets by hitting Tab, this widget will get the focus. 355 4807-7 ch19.F 356 5/24/01 9:00 AM Page 356 Part IV ✦ User Interfaces and Multimedia Gathering User Input Many widgets collect input from the user. For example, the Entry widget enables the user to enter a line of text and the Checkbox widget can be switched on and off. Most such widgets store their value in a Tkinter variable. Tkinter variable classes include StringVar, IntVar, DoubleVar, and BooleanVar. Each Tkinter variable class provides set and get methods to access its value: >>> Text=Tkinter.StringVar() >>> Text.get() ‘’ >>> Text.set(“Howdy!”) >>> Text.get() ‘Howdy!’ You hook a widget to a variable by setting one of the widget’s options. A check button generally uses a BooleanVar, attached using the variable option: SmokingFlag=BooleanVar() B1=Checkbutton(ParentFrame,text=”Smoking”,variable=SmokingFlag) # This line sets the variable *and* checks the Checkbutton: SmokingFlag.set(1) The Entry and OptionMenu widgets generally use a StringVar, attached using a textvariable option: # PetBunnyName.get() and NameEntry.get() will both # return the contents of the entry widget: PetBunnyName=StringVar() NameEntry=Entry(ParentFrame,text=”Bubbles”, textvariable=PetBunnyName) ChocolateName=StringVar() FoodChoice=OptionMenu(ParentFrame,ChocolateName, “Crunchy Frog”,”Spring Surprise”,”Anthrax Ripple”) Several Radiobutton widgets can share one variable, attached to the variable option. The value option stores that button’s value; I like to make the value the same as the radio button’s label: Flavor=StringVar() Chocolate=Radiobutton(ParentFrame,variable=Flavor, text=”Chocolate”,value=”Chocolate”) Strawberry=Radiobutton(ParentFrame,variable=Flavor, text=”Strawberry”,value=”Strawberry”) Albatross=Radiobutton(ParentFrame,variable=Flavor, text=”Albatross”,value=”Albatross”) 4807-7 ch19.F 5/24/01 9:00 AM Page 357 Chapter 19 ✦ Tinkering with Tkinter Some widgets, such as Listbox and Text, use custom methods (not Tkinter variables) to access their contents. Accessors for these widgets are described together with the widgets. Example: Printing Fancy Text The program in Listing 19-3 can print text in various colors and sizes. It uses various widgets, attached to Tkinter variables, to collect user input. Figure 19-3 shows the program in action. Listing 19-3: UserInput.py import Tkinter import tkFont # the Font class lives here! class MainWindow(Tkinter.Frame): def __init__(self): Tkinter.Frame.__init__(self) # Use Tkinter variables to hold user input: self.Text=Tkinter.StringVar() self.ColorName=Tkinter.StringVar() self.BoldFlag=Tkinter.BooleanVar() self.UnderlineFlag=Tkinter.BooleanVar() self.FontSize=Tkinter.IntVar() # Set some default values: self.Text.set(“Ni! Ni! Ni!”) self.FontSize.set(12) self.ColorName.set(“black”) self.TextItem=None # Create all the widgets: self.CreateWidgets() def CreateWidgets(self): # Let the user specify text: TextFrame=Tkinter.Frame(self) Tkinter.Label(TextFrame,text=”Text:”).pack(side=Tkinter.LEFT) Tkinter.Entry(TextFrame,textvariable=self.Text).pack(side=Tkinter.LEFT) TextFrame.pack() # Let the user select a color: ColorFrame=Tkinter.Frame(self) Colors=[“black”,”red”,”green”,”blue”,”deeppink”] Tkinter.Label(ColorFrame,text=”Color:”).pack(side=Tkinter.LEFT) Tkinter.OptionMenu(ColorFrame,self.ColorName,”white”,*Colors).pack(\ side=Tkinter.LEFT) ColorFrame.pack() Continued 357 4807-7 ch19.F 358 5/24/01 9:00 AM Page 358 Part IV ✦ User Interfaces and Multimedia Listing 19-3 (continued) # Let the user select a font size: SizeFrame=Tkinter.Frame(self) Tkinter.Radiobutton(SizeFrame,text=”Small”,variable=self.FontSize, value=12).pack(side=Tkinter.LEFT) Tkinter.Radiobutton(SizeFrame,text=”Medium”,variable=self.FontSize, value=24).pack(side=Tkinter.LEFT) Tkinter.Radiobutton(SizeFrame,text=”Large”,variable=self.FontSize, value=48).pack(side=Tkinter.LEFT) SizeFrame.pack() # Let the user turn Bold and Underline on and off: StyleFrame=Tkinter.Frame(self) Tkinter.Checkbutton(StyleFrame,text=”Bold”,variable=\ self.BoldFlag).pack(side=Tkinter.LEFT) Tkinter.Checkbutton(StyleFrame,text=”Underline”,variable=\ self.UnderlineFlag).pack(side=Tkinter.LEFT) StyleFrame.pack() # Add a button to repaint the text: GoFrame=Tkinter.Frame(self) Tkinter.Button(GoFrame,text=”Go!”,command=self.PaintText).pack() GoFrame.pack(anchor=Tkinter.W,fill=Tkinter.X) # Add a canvas to display the text: self.TextCanvas=Tkinter.Canvas(self,height=100,width=300) self.TextCanvas.pack(side=Tkinter.BOTTOM) # Pack parent-most widget last: self.pack() def PaintText(self): # Erase the old text, if any: if (self.TextItem!=None): self.TextCanvas.delete(self.TextItem) # Set font weight: if (self.BoldFlag.get()): FontWeight=tkFont.BOLD else: FontWeight=tkFont.NORMAL # Create and configure a Font object. # (Use tkFont.families(self) to get a list of available font-families) TextFont=tkFont.Font(self,”Courier”) TextFont.configure(size=self.FontSize.get(), underline=self.UnderlineFlag.get(), weight=FontWeight) self.TextItem=self.TextCanvas.create_text(5,5,anchor=Tkinter.NW, text=self.Text.get(),fill=self.ColorName.get(),font=TextFont) if (__name__==”__main__”): App=MainWindow() App.mainloop() 4807-7 ch19.F 5/24/01 9:00 AM Page 359 Chapter 19 ✦ Tinkering with Tkinter Figure 19-3: Printing fancy text Using Text Widgets The text widget (Tkinter.Text) is a fancy, multiline text-editing widget. It can even contain embedded windows and graphics. It is an Entry widget on steroids! The contents of a text widget are indexed by line and column. A typical index has the form n.m, denoting character m in line n. For example, 5.8 would be character 8 from line 5. The first line of text is line 1, but the first character in a line has column 0. Therefore, the beginning of a text widget has index 1.0. You can also use the special indices END, INSERT (the insertion cursor’s location), and CURRENT (the mouse pointer’s location). You can retrieve text from a text widget via its method get(start[,end]). This returns the text from index start up to (but not including!) index end. If end is omitted, get returns the single character at index start: TextWidget.get(“1.0”,Tkinter.END) # Get ALL of the text TextWidget.get(“3.0”,”4.0”) # Get line 3 TextWidget.get(“1.5”) # get the 6th character only 359 4807-7 ch19.F 360 5/24/01 9:00 AM Page 360 Part IV ✦ User Interfaces and Multimedia The method delete(start[,end]) deletes text from the widget. The indexes start and end function as they do for the get method. The method insert(pos,str) inserts the string str just before the index pos: TextWidget.insert(“1.0”,”Bob”) # Prepend Bob to the text TextWidget.insert(Tkinter.END,”Bob”) # Append Bob to the text # insert Bob wherever the mouse is pointing: TextWidget.insert(Tkinter.CURRENT,”Bob”) # Clear the widget (remove all text): TextWidget.delete(“1.0”,Tkinter.END) Building Menus To build a menu in Tkinter, you use a menu widget (Tkinter.Menu). You then flesh out the menu by adding entries. The method add_command(label=?,command=?) adds a menu line with the specified label. When the user chooses the menu line, the specified command is executed. add_separator adds a separator line to a menu, suitable for grouping commands. A call to add_cascade(label=?,menu=?) attaches the specified menu as a submenu of the current menu. And add_checkbutton(label=?[,...]) adds a check button to the menu. You can pass other options for the new Checkbutton widget (such as variable) to add_checkbutton. Create one instance of Menu to represent the menu bar itself, and then create one Menu instance for each “real” menu. Unlike most widgets, a menu is never packed. Instead, you attach it to a window using the menu option of a TopLevel widget, as shown in the following example: root=Tkinter.Tk() MenuBar=Tkinter.Menu(root) # Menu bar must be child of Toplevel root[“menu”]=MenuBar # attach menubar to window! FileMenu=Tkinter.Menu(MenuBar) # Submenu is child of menubar FileMenu.add_command(label=”Load”,command=LoadFile) FileMenu.add_command(label=”Save”,command=SaveFile) HelpMenu=Tkinter.Menu(MenuBar) HelpMenu.add_command(label=”Contents”,command=HelpIndex) # Attach menus to menubar: MenuBar.add_cascade(label=”File”,menu=FileMenu) MenuBar.add_cascade(label=”Help”,menu=HelpMenu) You can create pop-up menus in Tkinter. Call the menu method tk_popup(x,y[,default]) to bring a menu up as a pop-up. The pop-up is positioned at (x,y). If default is supplied, the pop-up menu starts with the specified label selected, as shown in Listing 19-4: 4807-7 ch19.F 5/24/01 9:00 AM Page 361 Chapter 19 ✦ Tinkering with Tkinter Listing 19-4: Popup.py import Tkinter def MenuCommand(): print “Howdy!” def ShowMenu(): PopupMenu.tk_popup(*root.winfo_pointerxy()) root=Tkinter.Tk() PopupMenu=Tkinter.Menu(root) PopupMenu.add_command(label=”X”,command=MenuCommand) PopupMenu.add_command(label=”Y”,command=MenuCommand) Tkinter.Button(root,text=”Popup”,command=ShowMenu).pack() root.mainloop() Using Tkinter Dialogs The module tkMessageBox provides several functions that display a pop-up message box. Each takes title and message parameters to control the window’s title and the message displayed. Table 19-1 Message Boxes Function Description showinfo Shows an informational message. showwarning Displays a warning message. showerror Displays an error message. Askyesno Displays Yes and No buttons. Returns true if the user chose Yes. Askokcancel Displays OK and Cancel buttons. Returns true if the user chose OK. Askretrycancel Displays Retry and Cancel buttons. Returns true if the user chose Retry. Askquestion Same as askyesno, but returns Yes or No as a string. This snippet of code uses tkMessageBox to get user confirmation before quitting: def Quit(self): if self.FileModified: if (not tkMessageBox.askyesno(“Confirm”,\ “File modified. Really quit?”): return # don’t quit! sys.exit() 361 4807-7 ch19.F 362 5/24/01 9:00 AM Page 362 Part IV ✦ User Interfaces and Multimedia File dialogs The module tkFileDialog provides functions to bring up file-selection dialogs. The function askopenfile lets the user choose an existing file. The function asksaveasfilename lets the user choose an existing file or provide a new file name. Both functions return the full path to the selected file (or an empty string, if the user cancels out). Optionally, pass a filetypes parameter to either function, to limit the search to particular file types. The parameter should be a list of tuples, where each tuple has the form (description,extension): MusicFileName=tkFileDialog.askopenfilename( filetypes=[(“Music files”,”mp3”)]) Example: Text Editor The example in Listing 19-5 is a simple text editor. With it, you can open, save, and edit text files. The code illustrates the use of the text widget, Tkinter menus, and some of Tkinter’s standard dialog boxes. Figure 19-4 shows what the text editor looks like. Listing 19-5: TextEditor.py import import import import import Tkinter tkFileDialog tkMessageBox os sys # Filetype selections for askopenfilename and asksaveasfilename: TEXT_FILE_TYPES=[(“Text files”,”txt”),(“All files”,”*”)] class TextEditor: def __init__(self): self.FileName=None self.CreateWidgets() def CreateWidgets(self): self.root=Tkinter.Tk() self.root.title(“New file”) MainFrame=Tkinter.Frame(self.root) # Create the File menu: MenuFrame=Tkinter.Frame(self.root) 4807-7 ch19.F 5/24/01 9:00 AM Page 363 Chapter 19 ✦ Tinkering with Tkinter MenuFrame.pack(side=Tkinter.TOP,fill=Tkinter.X) FileMenuButton=Tkinter.Menubutton(MenuFrame, text=”File”,underline=0) FileMenuButton.pack(side=Tkinter.LEFT,anchor=Tkinter.W) FileMenu=Tkinter.Menu(FileMenuButton,tearoff=0) FileMenu.add_command(label=”New”,underline=0, command=self.ClearText) FileMenu.add_command(label=”Open”,underline=0,command=self.Open) FileMenu.add_command(label=”Save”,underline=0,command=self.Save) FileMenu.add_command(label=”Save as...”,underline=5, command=self.SaveAs) FileMenu.add_separator() self.FixedWidthFlag=Tkinter.BooleanVar() FileMenu.add_checkbutton(label=”Fixed-width”, variable=self.FixedWidthFlag,command=self.SetFont) FileMenu.add_separator() def def def def FileMenu.add_command(label=”Exit”,underline=1,command=sys.exit) FileMenuButton[“menu”]=FileMenu # Create Help menu: HelpMenuButton=Tkinter.Menubutton(MenuFrame,text=”Help”,underline=0) HelpMenu=Tkinter.Menu(HelpMenuButton,tearoff=0) HelpMenu.add_command(label=”About”,underline=0,command=self.About) HelpMenuButton[“menu”]=HelpMenu HelpMenuButton.pack(side=Tkinter.LEFT,anchor=Tkinter.W) # Create the main text field: self.TextBox=Tkinter.Text(MainFrame) self.TextBox.pack(fill=Tkinter.BOTH,expand=Tkinter.YES) # Pack the top-level widget: MainFrame.pack(fill=Tkinter.BOTH,expand=Tkinter.YES) SetFont(self): if (self.FixedWidthFlag.get()): self.TextBox[“font”]=”Courier” else: self.TextBox[“font”]=”Helvetica” About(self): tkMessageBox.showinfo(“About textpad...”,”Hi, I’m a textpad!”) ClearText(self): self.TextBox.delete(“1.0”,Tkinter.END) Open(self): FileName=tkFileDialog.askopenfilename(filetypes=TEXT_FILE_TYPES) if (FileName==None or FileName==””): return try: File=open(FileName,”r”) NewText=File.read() File.close() self.FileName=FileName self.root.title(FileName) Continued 363 4807-7 ch19.F 364 5/24/01 9:00 AM Page 364 Part IV ✦ User Interfaces and Multimedia Listing 19-5 (continued) def def def def except IOError: tkMessageBox.showerror(“Read error...”, “Could not read from ‘%s’”%FileName) return self.ClearText() self.TextBox.insert(Tkinter.END,NewText) Save(self): if (self.FileName==None or self.FileName==””): self.SaveAs() else: self.SaveToFile(self.FileName) SaveAs(self): FileName=tkFileDialog.asksaveasfilename(filetypes=TEXT_FILE_TYPES) if (FileName==None or FileName==””): return self.SaveToFile(FileName) SaveToFile(self,FileName): try: File=open(FileName,”w”) NewText=self.TextBox.get(“1.0”,Tkinter.END) File.write(NewText) File.close() self.FileName=FileName self.root.title(FileName) except IOError: tkMessageBox.showerror(“Save error...”, “Could not save to ‘%s’”%FileName) return Run(self): self.root.mainloop() if (__name__==”__main__”): TextEditor().Run() 4807-7 ch19.F 5/24/01 9:00 AM Page 365 Chapter 19 ✦ Tinkering with Tkinter Figure 19-4: A text editor with dialogs Handling Colors and Fonts You can customize the color (or colors) of your widgets, as well as the font used to paint widget text. Colors Colors are defined using three numbers. The three numbers specify the intensity of red, green, and blue. Tkinter accepts colors in the form of a string of the form #RGB, or #RRGGBB, or #RRRGGGBBB. For example, #FFFFFF is white, #000000 is black, and #FF00FF is purple. The longer the string, the more precisely one can specify colors. Tkinter also provides many predefined colors — for example, red and green are valid color names. The list also includes some exotic colors, such as thistle3 and burlywood2. 365 4807-7 ch19.F 366 5/24/01 9:00 AM Page 366 Part IV ✦ User Interfaces and Multimedia Fonts Font descriptors are tuples of the form (family,size[,styles]). For example, the following lines display a button whose label is in Helvetica 24-point italics: root=Tkinter.Tk() Tkinter.Button(root,text=”Fancy”, font=(“Helvetica”,24,”italic”)).pack() If the name of a font family does not contain spaces, a string of the form “family size styles” is an equivalent font descriptor. You can also use X font descriptors: Tkinter.Button(root,text=”Fixed-width”, font=”-*-Courier-bold-r-*-*-12-*-*-*-*-*-*-*’).pack() Drawing Graphics The PhotoImage class enables you to add images to your user interface. Images in GIF, PPM, and PGM format are supported. The constructor enables you (optionally) to name the image. You can also specify a file to read the image from, or pass in raw image data: MisterT=PhotoImage(“Mr. T”,file=”mrt.gif”) # Another way to get the same image: ImageFile=open(“mrt.gif”) ImageData=ImageFile.read() ImageFile.close() MisterT=PhotoImage(data=ImageData) # no name Once you have a PhotoImage object, you can attach it to a label or button using the image option: MisterT=Tkinter.PhotoImage(file=”mrt.gif”) Tkinter.Button(root,image=MisterT).pack() You can query the size of a PhotoImage using the width and height methods. Note You can construct PhotoImage objects only after you instantiate a TopLevel instance. The canvas widget The canvas widget (Tkinter.Canvas) is a window in which you can programmatically draw ovals, rectangles, lines, and so on. For example, the following code draws a smiley-face: Figure=Tkinter.Canvas(root,width=50,height=50) Figure.pack() 4807-7 ch19.F 5/24/01 9:00 AM Page 367 Chapter 19 ✦ Tinkering with Tkinter Figure.create_line(10,10,10,20) Figure.create_line(40,10,40,20) Figure.create_arc(5,15,45,45,start=200,extent=140, style=Tkinter.ARC) Several different canvas items are available for your drawing pleasure: create_line(x1,y1,x2, y2,...,xn,yn) Draws lines connecting the points (x1,y1) through (xn,yn), in order. The lines are normally straight; set the smooth option to true to draw smooth lines. create_polygon(x1,y2, x2,y2,...,xn,yn) Similar to create_line. Fills the area spanned by the lines with the color supplied for the fill option (by default, “transparent”). Pass a color for the outline option to control the line color. Set the smooth option to true to draw smooth lines. create_image(x,y, image=?[,anchor=?]) (x,y). Draw the specified image on the canvas at The image option can be either a PhotoImage instance or the name of a previously created PhotoImage. The anchor option, which defaults to CENTER, specifies which portion of the image lies at (x,y). create_oval(x1,y1,x2,y2) Draw an oval inside the rectangle defined by the points (x1,y1) and (x2,y2). Pass a color in the outline option to control the outline’s color. Pass a color in the fill option to fill the oval with that color. You can control the outline’s width (in pixels) with the width option. create_rectangle (x1,y2,x2,y2) Draw a rectangle. The fill, outline, and width options have the same effect as for create_oval. create_text(x,y,text=? [,font=?]) Draw the specified text on the canvas. Uses the supplied font, if any. Manipulating canvas items The items drawn on a canvas are widgets in their own right — they can be moved around, have events bound to them, and so on. The create_* methods return an ID for the canvas item. You can use that ID to manipulate the canvas item, using the canvas’s methods. For example, the canvas method delete(ID) deletes the specified item. The method move(ID, DeltaX, DeltaY) moves the canvas item horizontally by DeltaX units, and vertically by DeltaY units. 367 4807-7 ch19.F 368 5/24/01 9:00 AM Page 368 Part IV ✦ User Interfaces and Multimedia Using Timers Tkinter also provides a timer mechanism. Call the method after(wait,function) on a TopLevel widget to make the specified function execute after wait milliseconds. To make a timed action recur (for example, once every five minutes), make another call to after at the end of function. For example, the code in Listing 19-6 calls a function every ten seconds: Listing 19-6: Timer.py import Tkinter def MinuteElapsed(): print “Ding!” root.after(1000*60,MinuteElapsed) root=Tkinter.Tk() root.after(10000,MinuteElapsed) root.mainloop() Example: A Bouncing Picture The program in Listing 19-7 displays a picture that moves around, bouncing off the sides of the window, as shown in Figure 19-5. It uses a PhotoImage object and a canvas to handle the display and the TopLevel after method to schedule calls to MoveImage. Listing 19-7: CanvasBounce.py import Tkinter class Bouncer: def __init__(self,Master): self.Master=Master self.X=0 self.Y=0 self.DeltaX=5 self.DeltaY=5 self.Figure=Tkinter.Canvas(self.Master) self.GrailWidth=GrailPicture.width() self.GrailHeight=GrailPicture.height() self.GrailID=self.Figure.create_image( 0,0,anchor=Tkinter.NW,image=GrailPicture) self.Figure.pack(fill=Tkinter.BOTH,expand=Tkinter.YES) # Move the image after 100 milliseconds: root.after(100,self.MoveImage) 4807-7 ch19.F 5/24/01 9:00 AM Page 369 Chapter 19 ✦ Tinkering with Tkinter def MoveImage(self): # Move the image: self.X+=self.DeltaX self.Y+=self.DeltaY self.Figure.coords(self.GrailID,self.X,self.Y) # Bounce off the sides: if (self.X<0): self.DeltaX=abs(self.DeltaX) if (self.Y<0): self.DeltaY=abs(self.DeltaY) if (self.X+self.GrailWidth>self.Figure.winfo_width()): self.DeltaX=-abs(self.DeltaX) if (self.Y+self.GrailHeight >\ self.Figure.winfo_height()): self.DeltaY=-abs(self.DeltaY) # Do it again after 100 milliseconds: self.Master.after(100,self.MoveImage) if (__name__==”__main__”): root=Tkinter.Tk() GrailPicture=Tkinter.PhotoImage(file=”HolyGrail.gif”) Bouncer(root) root.mainloop() Figure 19-5: A bouncing picture 369 4807-7 ch19.F 370 5/24/01 9:00 AM Page 370 Part IV ✦ User Interfaces and Multimedia Summary After working with Tkinter, you will understand why it is so popular. Creating and customizing an interface is simple. In this chapter, you: ✦ Created a GUI with buttons, labels, menus, and other Tkinter widgets. ✦ Used Tkinter’s standard dialogs. ✦ Set up timers. ✦ Drew pictures on a canvas. The next chapter delves into Tkinter in more detail. It covers events, drag-and-drop operations, and some more widgets. ✦ ✦ ✦ 4807-7 ch20.F 5/24/01 9:00 AM Page 371 20 CHAPTER Using Advanced Tkinter Widgets ✦ ✦ ✦ ✦ In This Chapter T his chapter introduces some of Tkinter’s fancier features — custom event handlers, advanced widgets, and more. Tkinter scales up painlessly from quick-and-dirty interfaces to sophisticated, full-featured applications. Handling Events Handling events Advanced widgets Creating dialogs Supporting drag-anddrop operations A GUI program spends most of its time waiting for something to happen. When something does happen — the user clicking the mouse, for example — events are sent to the affected widget(s). Events are sometimes called messages or notifications. A widget responds to an event using a function called an event handler. Using cursors Creating event handlers ✦ Often, Tkinter’s standard event handlers are good enough. As you saw in the last chapter, you can create an interesting UI without ever writing event handlers. However, you can always define a custom event handler for a widget. To define a custom handler, call the widget method bind(EventCode, Handler[,Add=None]). Here, EventCode is a string identifying the event, and Handler is a function to handle the event. Passing a value of + for Add causes the new handler to be added to any existing event binding. You can also bind event handlers for a particular widget class with a call to bind_class(ClassName,EventCode, Handler[,Add]), or bind event handlers for application-level events with bind_all(EventCode,Handler[,Add]). When the widget receives a matching event, Handler is called, and passed one argument — an event object. For example, the following code creates a label that beeps when you click it: Designing new widgets Further Tkinter adventures ✦ ✦ ✦ 4807-7 ch20.F 372 5/24/01 9:00 AM Page 372 Part IV ✦ User Interfaces and Multimedia BeepLabel=Tkinter.Label(root,text=”Click me!”) BeepHandler=lambda Event,Root=root:Root.bell() BeepLabel.bind(“<Button-1>”,BeepHandler) BeepLabel.pack() Binding mouse events Mouse buttons are numbered — 1 is the left button, 2 is the middle button (if any), and 3 is the right button. Table 20-1 lists the available mouse event codes. Table 20-1 Mouse Events Event code Description <Button-1> Button 1 was pressed on the widget. Similarly for <Button-2> and <Button-3>. <B1-Motion> The mouse pointer was dragged over the widget, with button 1 pressed. <ButtonRelease-1> Button 1 was released over the widget. <Double-Button-1> Button 1 was double-clicked over the widget. Binding keyboard events The event code <Key> matches any keypress. You can also match a particular key, generally by using that key’s character as an event code. For example, the event code x matches a press of the x key. Some keystrokes have special event codes. Table 20-2 lists the event codes for some of the most common special keystrokes. Table 20-2 Common Special Keystrokes Event code Keystroke <Up> Up arrow key <Down> Down arrow key <Left > Left arrow key <Right > Right arrow key 4807-7 ch20.F 5/24/01 9:00 AM Page 373 Chapter 20 ✦ Using Advanced Tkinter Widgets Event code Keystroke <F1> Function key 1 <Shift_L >,<Shift_R> Left and right Shift key <Control_L >,<Control_R> Left and right Control key <space> Spacebar Event objects An event object, as passed to an event handler, has various attributes that specify just what happened. The attribute widget is a reference to the affected widget. For mouse events, the attributes x and y are the coordinates of the mouse pointer, in pixels, as measured from the top-left corner of the widget. The attributes x_root and y_root are mouse pointer coordinates, as measured from the top-left corner of the screen. For keyboard events, the attribute char is the character code, as a string. Example: A Drawing Canvas The program in Listing 20-1 provides a canvas on which you can draw shapes by left- and right-clicking. In addition, you can move the Quit button around by using the arrow keys. Figure 20-1 shows the program in action. Listing 20-1: Events.py import Tkinter import sys def DrawOval(Event): # Event.widget will be the main canvas: Event.widget.create_oval(Event.x-5,Event.y-5, Event.x+5,Event.y+5) def DrawRectangle(Event): Event.widget.create_rectangle(Event.x-5,Event.y-5, Event.x+5,Event.y+5) def MoveButton(Side): # The methods pack_forget() and grid_forget() unpack # a widget, but (unlike the destroy() method) Continued 373 4807-7 ch20.F 374 5/24/01 9:00 AM Page 374 Part IV ✦ User Interfaces and Multimedia Listing 20-1 (continued) # do not destroy it; it can be re-displayed later. QuitButton.pack_forget() QuitButton.pack(side=Side) root=Tkinter.Tk() MainCanvas=Tkinter.Canvas(root) MainCanvas.bind(“<Button-1>”,DrawOval) MainCanvas.bind(“<Button-3>”,DrawRectangle) MainCanvas.pack(fill=Tkinter.BOTH,expand=Tkinter.YES) QuitButton=Tkinter.Button(MainCanvas,text=”Quit”, command=sys.exit) QuitButton.pack(side=Tkinter.BOTTOM) root.bind(“<Up>”,lambda e:MoveButton(Tkinter.TOP)) root.bind(“<Down>”,lambda e:MoveButton(Tkinter.BOTTOM)) root.bind(“<Left>”,lambda e:MoveButton(Tkinter.LEFT)) root.bind(“<Right>”,lambda e:MoveButton(Tkinter.RIGHT)) root.geometry(“300x300”) # Set minimum window size root.mainloop() Figure 20-1: A canvas with custom mouse and keyboard event handlers 4807-7 ch20.F 5/24/01 9:00 AM Page 375 Chapter 20 ✦ Using Advanced Tkinter Widgets Advanced Widgets This section introduces three more widgets for your Tkinter widget toolbox: listbox, scale, and scrollbar. Listbox A listbox (Tkinter.Listbox) displays a list of options. Each option is a string, and each takes up one row in the listbox. Each item is assigned an index (starting from 0). The option selectmode governs what kind of selections the user can make. SINGLE allows one row to be selected at a time; MULTIPLE permits the user to select many rows at once. BROWSE (the default) is similar to SINGLE, but allows the user to drag the mouse cursor across rows. EXTENDED is similar to MULTIPLE, but allows fancier selections to be made by Control- and Shift-clicking. The option height, which defaults to 10, specifies how many rows a listbox displays at once. If a listbox contains more rows than it can display at once, you should attach a scrollbar — see the section “Scrollbar” for details. Editing listbox contents To populate the listbox, call the method insert(before,element[,...]). This inserts one or more elements (which must be strings!) prior to index before. Use the special index Tkinter.END to append the new item(s) to the end of the listbox. The method delete(first[,last]) deletes all items from index first to index last, inclusive. If last is not specified, the single item with index first is deleted. Checking listbox contents The method size returns the number of items in the listbox. The method get(first[,last]) retrieves the items from index first to index last, inclusive. Normally, get returns a list of strings; if last is omitted, the single item with index first is returned. The method nearest(y) returns the index of the row closest to the specified y-coordinate. This is useful for determining what row a user is clicking. Checking and changing the selection The method curselection returns the current selection, in the form of a list of indices. If no row is selected, curselection returns an empty string. The method selection_includes(index) returns true if the item with the specified index is selected. 375 4807-7 ch20.F 376 5/24/01 9:00 AM Page 376 Part IV ✦ User Interfaces and Multimedia The method selection_set(first[,last]) selects the items from index first to index last, inclusive. The method selection_clear(first[,last]) deselects the specified items. Note When you specify a range of listbox indices, the list is inclusive, not exclusive. For example, MyList.selection_set(2,3) selects the items with index 2 and 3. Scale A scale widget (Tkinter.Scale) looks like a sliding knob. The user drags the slider to set a numeric value. You can attach a scale to a Tkinter variable (using the variable option), or use its get and set methods to access its value directly. Range and precision The options from and to specify the numeric range available; the default is the range from 0 to 100. The option resolution is the smallest possible change the user can make in the numeric value. By default, resolution is 1 (so that the scale’s value is always an integer). Note Remember to use from_ , not from, when passing the “from” option as a keyword argument. Widget size The option orient determines the direction in which the scale is laid out; valid values are HORIZONTAL and VERTICAL. The option length specifies the length (in pixels) of the scale; it defaults to 100. The option sliderlength determines the length of the sliding knob; it defaults to 30. Labeling By default, a scale displays the current numeric value above (or to the left of) the sliding scale. Set the showvalue option to false to disable this display. You can label the axis with several tick-marks. To do so, pass the distance between ticks in the option tickinterval. Scrollbar A scrollbar widget (Tkinter.Scrollbar) is used in conjunction with another widget when that widget has more to show than it can display all at once. The scrollbar enables the user to scroll through the available information. The orient option determines the scrollbar’s orientation; valid values are VERTICAL and HORIZONTAL. 4807-7 ch20.F 5/24/01 9:00 AM Page 377 Chapter 20 ✦ Using Advanced Tkinter Widgets To attach a vertical scrollbar to a Listbox, Canvas, or Text widget, set the scrollbar’s command option to the yview method of the widget. Then, set the widget’s yscrollcommand option to the scrollbar’s set method. (To attach a horizontal scrollbar, perform a similar procedure, but use xview and xscrollcommand.) For example, the following two lines “hook together” a scrollbar (MyScrollbar) and a listbox (MyListbox): MyScrollbar[“command”]= MyListbox.yview MyListbox[“yscrollcommand”]= MyScrollbar.set Example: Color Scheme Customizer Tkinter allows you to use a predefined color scheme. These colors are used as defaults for the foreground and background options of widgets. The TopLevel method option_readfile(filename) reads in default colors and fonts from a file. You should call option_readfile as early in your program as possible, because it doesn’t affect any widgets already displayed onscreen. A typical line in the file has the form *Widget*foreground: Color, where Widget is a widget class and Color is the default color for that sort of widget. The line *foreground: Color sets a default foreground for all other widgets. Similar lines set the default background colors. The example shown in Listing 20-2 lets you define a new color scheme. It uses a listbox, a scrollbar, and three sliding scales (for setting red, green, and blue levels). See Figure 20-2 for an example. Listing 20-2: ColorChooser.py import Tkinter import os import sys WIDGET_NAMES = [“Entry”,”Label”,”Menu”,”Text”,”Button”,”Listbox”,”Scale”, “Scrollbar”,”Canvas”] OPTION_FILE_NAME=”TkinterColors.ini” COLOR_COMPONENTS=[“Red”,”Green”,”Blue”] class ColorChooser: def __init__(self): self.root = Tkinter.Tk() # Dictionary of options and values - corresponds to # the option database (TkinterColors.ini): self.Options={} Continued 377 4807-7 ch20.F 378 5/24/01 9:00 AM Page 378 Part IV ✦ User Interfaces and Multimedia Listing 20-2 (continued) def def def def def def # Flag linked to the “Option set?” checkbox: self.OptionSetFlag=Tkinter.BooleanVar() self.GetOptionsFromFile() self.BuildWidgets() self.SelectedColorItem=None self.SelectNewColorItem(0) SaveCurrentColorValues(self): “Use Scale-widget values to set internal color value” if (self.SelectedColorItem!=None): if (self.OptionSetFlag.get()): ColorString=”#” for ColorComponent in COLOR_COMPONENTS: ColorString+=”%02X”%self.ColorValues[ColorComponent].get() self.Options[self.SelectedColorItem]=ColorString else: # The user un-checked the “option set” box: if (self.Options.has_key(self.SelectedColorItem)): del self.Options[self.SelectedColorItem] UpdateControlsFromColorValue(self): “Use internal color value to update Scale widgets” if (self.SelectedColorItem!=None and self.OptionSetFlag.get()): ColorString=self.Options.get(self.SelectedColorItem,””) if len(ColorString)!=7: ColorString=”#000000” # default else: ColorString=”#000000” RedValue=int(ColorString[1:3],16) self.ColorValues[“Red”].set(RedValue) GreenValue=int(ColorString[3:5],16) self.ColorValues[“Green”].set(GreenValue) BlueValue=int(ColorString[5:],16) self.ColorValues[“Blue”].set(BlueValue) OptionChecked(self): “””Callback for clicking the “Option set” checkbox””” if (self.OptionSetFlag.get()): self.EnableColorScales() else: self.DisableColorScales() EnableColorScales(self): for ColorComponent in COLOR_COMPONENTS: self.ColorScales[ColorComponent][“state”]=Tkinter.NORMAL DisableColorScales(self): for ColorComponent in COLOR_COMPONENTS: self.ColorScales[ColorComponent][“state”]=Tkinter.DISABLED SelectNewColorItem(self,NewIndex): “””Choose a new color item - save the current item, select the new entry in the listbox, and update the scale-widgets from the new entry””” 4807-7 ch20.F 5/24/01 9:00 AM Page 379 Chapter 20 ✦ Using Advanced Tkinter Widgets self.SaveCurrentColorValues() self.SelectedColorItem=self.ItemList.get(NewIndex) self.ItemList.activate(NewIndex) self.ItemList.selection_set(NewIndex) print “sel:”,self.SelectedColorItem print self.Options.has_key(self.SelectedColorItem) self.OptionSetFlag.set(self.Options.has_key(self.SelectedColorItem)) print self.OptionSetFlag.get() self.OptionChecked() self.UpdateControlsFromColorValue() def ListboxClicked(self,ClickEvent): “Event handler for choosing a new Listbox entry” NewIndex=self.ItemList.nearest(ClickEvent.y) self.SelectNewColorItem(NewIndex) def BuildWidgets(self): “””Set up all the application widgets””” self.LeftPane=Tkinter.Frame(self.root) self.RightPane=Tkinter.Frame(self.root) self.ItemList=Tkinter.Listbox(self.LeftPane, selectmode=Tkinter.SINGLE) self.ItemList.pack(side=Tkinter.LEFT,expand=Tkinter.YES, fill=Tkinter.Y) self.ListBoxScroller=Tkinter.Scrollbar(self.LeftPane) self.ListBoxScroller.pack(side=Tkinter.RIGHT,expand=Tkinter.YES, fill=Tkinter.Y) # Add entries to listbox: self.ItemList.insert(Tkinter.END,”*foreground”) self.ItemList.insert(Tkinter.END,”*background”) for WidgetName in WIDGET_NAMES: self.ItemList.insert(Tkinter.END,”*%s*foreground”%WidgetName) self.ItemList.insert(Tkinter.END,”*%s*background”%WidgetName) # Attach scrollbar to listbox: self.ListBoxScroller[“command”]=self.ItemList.yview self.ItemList[“yscrollcommand”]=self.ListBoxScroller.set # Handle listbox selection events specially: self.ItemList.bind(“<Button-1>”,self.ListboxClicked) # Add checkbox for setting and un-setting the option: ColorSetCheck=Tkinter.Checkbutton(self.RightPane, text=”Option set”, variable=self.OptionSetFlag, command=self.OptionChecked) ColorSetCheck.pack(side=Tkinter.TOP,anchor=Tkinter.W) # Build red, green, and blue scales for setting colors: self.ColorValues={} self.ColorScales={} for ColorComponent in COLOR_COMPONENTS: ColorValue=Tkinter.IntVar() self.ColorValues[ColorComponent]=ColorValue NewScale=Tkinter.Scale(self.RightPane, orient=Tkinter.HORIZONTAL,from_=0,to=255, variable=ColorValue) self.ColorScales[ColorComponent]=NewScale Continued 379 4807-7 ch20.F 380 5/24/01 9:00 AM Page 380 Part IV ✦ User Interfaces and Multimedia Listing 20-2 (continued) Tkinter.Label(self.RightPane,text=ColorComponent).pack\ (side=Tkinter.TOP) NewScale.pack(side=Tkinter.TOP,pady=10) # Add “SAVE” and “QUIT” buttons: ButtonFrame=Tkinter.Frame(self.RightPane) ButtonFrame.pack() Tkinter.Button(ButtonFrame,text=”Save”, command=self.SaveOptionsToFile).pack(side=Tkinter.LEFT) Tkinter.Button(ButtonFrame,text=”Quit”, command=sys.exit).pack(side=Tkinter.LEFT) # Pack the parentmost widgets: self.LeftPane.pack(side=Tkinter.LEFT,expand=Tkinter.YES, fill=Tkinter.BOTH) self.RightPane.pack(side=Tkinter.RIGHT,expand=Tkinter.YES, fill=Tkinter.BOTH) def Run(self): self.root.mainloop() def SaveOptionsToFile(self): # Update internal color-settings from scale-widgets: self.SaveCurrentColorValues() File=open(OPTION_FILE_NAME,”w”) # Save *foreground and *background first: if self.Options.has_key(“*foreground”): File.write(“*foreground: %s\n”%self.Options[“*foreground”]) del self.Options[“*foreground”] if self.Options.has_key(“*background”): File.write(“*background: %s\n”%self.Options[“*background”]) del self.Options[“*background”] for Key in self.Options.keys(): File.write(“%s: %s\n”%(Key,self.Options[Key])) File.close() print “Saved!” def GetOptionsFromFile(self): if os.path.exists(OPTION_FILE_NAME): # Read the colors in: File=open(OPTION_FILE_NAME,”r”) for Line in File.readlines(): LineHalves=Line.split(“:”) if len(LineHalves)!=2: # Not a proper setting continue Value = LineHalves[1].strip() Index = LineHalves[0].strip() self.Options[Index] = Value File.close() # Tell Tkinter to use these colors, too! self.root.option_readfile(OPTION_FILE_NAME) if (__name__==”__main__”): ColorChooser().Run() 4807-7 ch20.F 5/24/01 9:00 AM Page 381 Chapter 20 ✦ Using Advanced Tkinter Widgets Figure 20-2: Using scales and listboxes to design a color scheme Creating Dialogs Instead of using the standard dialogs (as described in Chapter 19), you can create dialog boxes of your own. The module tkSimpleDialog provides a class, Dialog, that you can subclass to create any dialog box. When you construct a Dialog instance, the dialog is (synchronously) displayed, and the user can click OK or Cancel. The constructor has the syntax Dialog(master[,title]). Override the method body(master) with a method that creates the widgets in the dialog body. If the body method returns a widget, that widget receives the initial focus when the dialog is displayed. Override the apply method with a function to be called when the user clicks OK. In addition, you can create custom buttons by overriding the buttonbox method. The buttons should call the ok and cancel methods. In addition, binding <Return> to OK, and <Escape> to Cancel, is generally a good idea. The example in Listing 20-3 displays a simple dialog when the user presses a button. 381 4807-7 ch20.F 382 5/24/01 9:00 AM Page 382 Part IV ✦ User Interfaces and Multimedia Listing 20-3: Complaint.py import Tkinter import tkSimpleDialog class ComplaintDialog(tkSimpleDialog.Dialog): def body(self,Master): Tkinter.Label(self, text=”Enter your complaint here:”).pack() self.Complaint=Tkinter.Entry(self) self.Complaint.pack() return self.Complaint # set initial focus here! def apply(self): self.ComplaintString=self.Complaint.get() def Complain(): # This next line doesn’t return until the user # clicks “Ok” or “Cancel”: UserDialog=ComplaintDialog(root,”Enter your complaint”) if hasattr(UserDialog,”ComplaintString”): # They must have clicked “Ok”, since # apply() got called. print “Complaint:”,UserDialog.ComplaintString root=Tkinter.Tk() Tkinter.Button(root,text=”I wish to register a complaint”, command=Complain).pack() root.mainloop() Supporting Drag-and-Drop Operations The module Tkdnd provides simple drag-and-drop support for your Tkinter applications. To implement drag-and-drop, you need to have suitable draggable objects, and suitable targets. A draggable object (which can be a widget) should implement a dnd_end method. A target can be any widget that implements the methods dnd_accept, dnd_motion, dnd_enter, dnd_leave, and dnd_commit. To support drag-and-drop, bind a handler for <ButtonPress> in the widget from which you can drag. In the event handler, call Tkdnd.dnd_start(draggable, event), where draggable is a draggable object and event is the event you are handling. The call to dnd_start returns a drag-and-drop object. You can call this object’s cancel method to cancel an in-progress drag; otherwise, you don’t use the drag-and-drop object. 4807-7 ch20.F 5/24/01 9:00 AM Page 383 Chapter 20 ✦ Using Advanced Tkinter Widgets As the user drags the object around, Tkdnd constantly looks for a new target widget. It checks the widget under the mouse cursor, then that parent’s widget, and so on. When it sees a widget with a dnd_accept method, it calls dnd_accept(draggable, event), where draggable is the object being dragged. If the call to dnd_accept returns anything but None, that widget becomes the new target. Whenever the dragged object moves, one of the following happens: ✦ If the old target and the new target are both None, nothing happens. ✦ If the old and new targets are the same widget, its method dnd_motion (draggable,event) is called. ✦ If the old target is None and the new target is not, its method dnd_enter(draggable,event) is called. ✦ If the new target is None and the old target is not, its method dnd_leave(draggable, event) is called. ✦ If the old and new targets are not None and are different, dnd_leave is called on the old one and then dnd_enter is called on the new one. If the draggable object is dropped on a valid target, dnd_commit(draggable,event) is called on that target. If the draggable object is not dropped on a valid target, dnd_leave is called on the previous target (if any). In either case, a call to dnd_end(target,event) is made on the draggable object when the user drops it. The program in Listing 20-4 illustrates drag-and-drop through the use of two custom listboxes. Entries can be dragged around within a listbox, or dragged between listboxes. Figure 20-3 shows what the program looks like. Listing 20-4: DragAndDrop.py import Tkinter import Tkdnd class DraggableRow: def __init__(self,Index,ItemStr,Widget): self.Index=Index self.ItemStr=ItemStr self.Widget=Widget self.PreviousWidget=Widget def dnd_end(self,Target,Event): if Target==None: # Put the item back in its original widget! self.PreviousWidget.insert(Tkinter.END, self.ItemStr) Continued 383 4807-7 ch20.F 384 5/24/01 9:00 AM Page 384 Part IV ✦ User Interfaces and Multimedia Listing 20-4 (continued) class DragAndDropListbox(Tkinter.Listbox): def __init__(self,Master,cnf={},**kw): Tkinter.Listbox.__init__(self,Master,cnf) self.bind(“<ButtonPress>”,self.StartDrag) def StartDrag(self,Event): Index=self.nearest(Event.y) ItemStr=self.get(Index) Tkdnd.dnd_start(DraggableRow(Index,ItemStr,self),Event) def dnd_accept(self,Item,Event): return self def dnd_leave(self,Item,Event): self.delete(Item.Index) Item.PreviousWidget=self Item.Widget=None Item.Index=None def dnd_enter(self,Item,Event): if (Item.Widget==self and Item.Index!=None): self.delete(Item.Index) Item.Widget=self NewIndex=self.nearest(Event.y) NewIndex=max(NewIndex,0) self.insert(NewIndex,Item.ItemStr) Item.Index=NewIndex def dnd_commit(self,Item,Event): pass def dnd_motion(self,Item,Event): if (Item.Index!=None): self.delete(Item.Index) NewIndex=self.nearest(Event.y) NewIndex=max(NewIndex,0) Item.Index=NewIndex self.insert(NewIndex,Item.ItemStr) root=Tkinter.Tk() LeftList=DragAndDropListbox(root) LeftList.pack(side=Tkinter.LEFT,fill=Tkinter.BOTH, expand=Tkinter.YES) RightList=DragAndDropListbox(root) RightList.pack(side=Tkinter.RIGHT,fill=Tkinter.BOTH, expand=Tkinter.YES) # Add some elements to the listbox, for testing: for Name in [“Nene”,”Syvia”,”Linna”,”Priscilla”]: LeftList.insert(Tkinter.END,Name) root.mainloop() 4807-7 ch20.F 5/24/01 9:00 AM Page 385 Chapter 20 ✦ Using Advanced Tkinter Widgets Figure 20-3: Dragging and dropping elements between two listboxes Using Cursors The standard widget option cursor specifies the name of a cursor image to use when the mouse is positioned over the widget. Setting cursor to an empty string uses the standard system cursor. For example, the following code creates a Quit button, and changes the cursor to a skull-and-crossbones when it is positioned over the button: Tkinter.Button(root,text=”Quit”,command=sys.exit, cursor=”pirate”).pack() Many cursors are available, which range from the useful to the silly. Table 20-3 describes some useful cursors. 385 4807-7 ch20.F 386 5/24/01 9:00 AM Page 386 Part IV ✦ User Interfaces and Multimedia Table 20-3 Cursors Name Description left_ptr Pointer arrow; a good default cursor watch Stopwatch; used to tell the user to wait while some operation finishes pencil Pencil; good for drawing xterm Insertion cursor; the default for Text and Entry widgets trek, gumby, box_spiral Some cute, silly cursors The TopLevel method after executes a function after a specified amount of time has passed. (See “Using Timers” in Chapter 19). The related method after_idle(function) executes a specified function as soon as Tkinter empties its event queue and becomes idle. It is a handy way for restoring the cursor to normal after an operation has finished. The example in Listing 20-5 finds .mp3 files in the current directory and all its subdirectories, and adds them to a playlist. It displays a busy cursor while it is searching the directories. (A fancier approach would be to spawn a child thread to do the search.) Listing 20-5: WaitCursor.py import Tkinter import os OldCursor=”” def DoStuff(): # Save the old cursor, so we can restore it later. # (In this example, we know the old cursor is just “”) OldCursor=root[“cursor”] # Change the cursor: root[“cursor”]=”watch” # Wait for Tkinter to empty the event loop. We must do # this, in order to see the new cursor: root.update() # Tell Tkinter to RestoreCursor the next time it’s idle: root.after_idle(RestoreCursor) File=open(“PlayList.m3u”,”w”) os.path.walk(os.path.abspath(os.curdir),CheckDir,File) File.close() def CheckDir(File,DirName,FileNames): # Write all the MP3 files in the directory to our playlist: for FileName in FileNames: 4807-7 ch20.F 5/24/01 9:00 AM Page 387 Chapter 20 ✦ Using Advanced Tkinter Widgets if os.path.splitext(FileName)[1].upper()==”.MP3”: File.write(os.path.join(DirName,FileName)+”\n”) def RestoreCursor(): root[“cursor”]=OldCursor root=Tkinter.Tk() Tkinter.Button(text=”Find files!”,command=DoStuff).pack() root.mainloop() Designing New Widgets You can create new widgets by combining or subclassing existing ones. However, before you do, do a quick search online — any widget you can imagine has probably been created already! Listing 20-6 shows a simple example — a progress bar, which keeps track of progress as a percentage from 0 to 100. Figure 20-4 shows the program partway through its run. Listing 20-6: ProgressBar.py import Tkinter import time import sys class ProgressBar: def __init__(self, Parent, Height=10, Width=100, ForegroundColor=None,BackgroundColor=None,Progress=0): self.Height=Height self.Width=Width self.BarCanvas = Tkinter.Canvas(Parent, width=Width,height=Height, background=BackgroundColor,borderwidth=1, relief=Tkinter.SUNKEN) if (BackgroundColor): self.BarCanvas[“backgroundcolor”]=BackgroundColor self.BarCanvas.pack(padx=5,pady=2) self.RectangleID=self.BarCanvas.create_rectangle(\ 0,0,0,Height) if (ForegroundColor==None): ForegroundColor=”black” self.BarCanvas.itemconfigure(\ self.RectangleID,fill=ForegroundColor) self.SetProgressPercent(Progress) def SetProgressPercent(self,NewLevel): Continued 387 4807-7 ch20.F 388 5/24/01 9:00 AM Page 388 Part IV ✦ User Interfaces and Multimedia Listing 20-6 (continued) self.Progress=NewLevel self.Progress=min(100,self.Progress) self.Progress=max(0,self.Progress) self.DrawProgress() def DrawProgress(self): ProgressPixel=(self.Progress/100.0)*self.Width self.BarCanvas.coords(self.RectangleID, 0,0,ProgressPixel,self.Height) def GetProgressPercent(self): return self.Progress # Simple demonstration: def IncrememtProgress(): OldLevel=Bar.GetProgressPercent() if (OldLevel>99): sys.exit() Bar.SetProgressPercent(OldLevel+1) root.after(20,IncrememtProgress) root=Tkinter.Tk() root.title(“Progress bar!”) Bar=ProgressBar(root) root.after(20,IncrememtProgress) root.mainloop() Figure 20-4: A custom widget for displaying a progress bar 4807-7 ch20.F 5/24/01 9:00 AM Page 389 Chapter 20 ✦ Using Advanced Tkinter Widgets Further Tkinter Adventures There are many more widgets, options, and tricks in Tkinter than are covered here. Following are some places to learn more. Additional widgets Python MegaWidgets (Pmw) is a large collection of Tkinter widgets. Examples include Notebook (a tabbed display) and Balloon (a class for adding popup help). Pmw is a nice way to develop fancier interfaces without becoming a Tk Jedi Master. Visit http://www.dscpl.com.au/pmw/ to check it out. There are other collections of Tk widgets — such as Tix and BLT — that may help you save time developing a GUI. Learning more The Tkinter distribution is lacking in documentation, but there are several good Tkinter references out there: ✦ An Introduction to Tkinter, by Fredrik Lundh. Comprehensive, with many good examples. http://www.pythonware.com/library/tkinter/introduction/ index.htm ✦ Python and Tkinter Programming, by John E. Grayson. Many interesting examples. Covers Pmw in great detail. The book’s Web site is at http://www.manning.com/Grayson/ ✦ The Tkinter topic guide — a good starting point for all things Tkinter. http://www.python.org/topics/tkinter/doc.html ✦ The Tkinter Life Preserver, by Matt Conway. http://www.python.org/doc/life-preserver/index.html When all else fails, read up on Tk. The correspondence between Tkinter and Tk is straightforward, so anything you learn about Tk will carry over to Tkinter too. 389 4807-7 ch20.F 390 5/24/01 9:00 AM Page 390 Part IV ✦ User Interfaces and Multimedia Summary Tkinter can handle sophisticated GUIs without much trouble. You can use the layout managers and event handler to get your program’s appearance and behavior just right. In this chapter, you: ✦ Handled various events. ✦ Created advanced widgets and dialogs. ✦ Used custom mouse cursors. In the next chapter, you learn all about the Curses module — a good user interface choice for terminals on which graphics (and hence Tkinter) aren’t available. ✦ ✦ ✦ 4807-7 ch21.F 5/24/01 9:00 AM Page 391 21 CHAPTER Building User Interfaces with wxPython A lthough it is not Python’s official user interface library, wxPython is becoming an increasingly popular set of tools for building graphical user interfaces. Like Tkinter, it is powerful, easy to use, and works on several platforms. This chapter gives you a jump start on using wxPython in your own applications. ✦ ✦ ✦ ✦ In This Chapter Introducing wxPython Creating simple wxPython programs Choosing different window types Using wxPython controls Controlling layout Introducing wxPython wxPython (http://wxpython.org) is an extension module that wraps a C++ framework called wxWindows (http://wxwindows.org). Both wxPython and wxWindows provide cross-platform support and are free for private as well as commercial use. This chapter focuses on the cross-platform GUI support provided by wxPython, but wxWindows also gives you cross-platform APIs for multithreading, database access, and so on. Tip Visit the wxPython Web site for straightforward downloading and installing instructions, as well as the latest news and support. You can also join the wxPython community by subscribing to a free mailing list for questions, answers, and announcements. Visit http://wxpros.com for information about professional support and training. The full feature set of wxPython deserves an entire book of its own, and a single chapter will all but scratch the surface. The purpose of this chapter, therefore, is to give you a high-level picture of what it supports, and to get you started on writing some wxPython programs of your own. You’ll still want to Using built-in dialogs Drawing with device contexts Adding menus and keyboard shortcuts Accessing mouse and keyboard input Other wxPython features ✦ ✦ ✦ ✦ 4807-7 ch21.F 392 5/24/01 9:00 AM Page 392 Part IV ✦ User Interfaces and Multimedia later sift through the documentation for additional options and features. Because wxPython is so easy to use, however, by the end of this chapter you’ll be able to write some very functional programs, and with very little effort. In addition to its built-in features, wxPython can also detect and use some popular Python extension modules such as Numerical Python (NumPy) and PyOpenGL, the OpenGL bindings for Python. CrossReference See Chapter 32 for an introduction to NumPy. wxPython often outperforms Tkinter, both with large amounts of data and overall responsiveness; it comes with a good set of high-level controls and dialogs; and it does a pretty good job of giving applications a native look and feel (which isn’t necessarily a goal of Tkinter anyway). For these reasons, and because I find using wxPython very straightforward and intuitive, I personally prefer wxPython over Tkinter even though it doesn’t ship as a standard part of the Python distribution. Creating Simple wxPython Programs Most wxPython programs have a similar structure, so once you have that under your belt, you can quickly move on to programs that are more complex. Listing 21-1 is a simple program that opens up a main window with a giant button in it. Clicking the button pops up a dialog box, as shown in Figure 21-1. Listing 21-1: wxclickme.py — A wxPython application with buttons from wxPython.wx import * class ButtonFrame(wxFrame): ‘Creates a frame with a single button in the center’ def __init__(self): wxFrame.__init__(self, NULL, -1, ‘wxPython’, wxDefaultPosition, (200, 100)) button = wxButton(self, 111, ‘Click Me!’) EVT_BUTTON(self, 111, self.onButton) def onButton(self, event): ‘Create a message dialog when the button is clicked’ dlg = wxMessageDialog(self, ‘Ow, quit it.’, \ ‘Whine’, wxOK) dlg.ShowModal() dlg.Destroy() 4807-7 ch21.F 5/24/01 9:00 AM Page 393 Chapter 21 ✦ Building User Interfaces with wxPython class App(wxApp): def OnInit(self): ‘Create the main window and insert the custom frame’ frame = ButtonFrame() frame.Show(true) return true # Yes, continue processing # Create the app and start processing messages app = App(0) app.MainLoop() Figure 21-1: The program in Listing 21-1 opens the dialog box on the button click event. To understand this program, start at the end and work your way back. All wxPython programs instantiate a wxApp (or subclass) object and call its MainLoop method to start the message handling (MainLoop doesn’t return until the application window is closed). The wxApp subclass in the example, App, overloads the OnInit method that is called during initialization. OnInit creates a custom frame, ButtonFrame, makes it visible, and returns true (actually, wx.true) to signal success. These lines of code will be nearly identical for almost all your wxPython programs; for each new program, I usually cut and paste them from the previous program I wrote, changing only the name of the frame class to use. A frame is a top-level window like the main window in most applications (it usually has a title bar, is resizable, and so forth). The __init__ method of the ButtonFrame class calls the parent (wxFrame) constructor to set the title to “wxPython” and the size to 200 pixels wide and 100 tall. It adds a button with the label Click Me!, and tells wxPython to route button-click messages for that button to ButtonFrame’s onButton method. Notice how trivial it is to set up event routing. The line EVT_BUTTON(self, 111, self.onButton) tells wxPython to take all button-click events generated in the current window (self) with an ID of 111 (a random number I chose and assigned to the button) and send them to the onButton method. The only requirement for the onButton method is that it take an event argument. You can use a method such as onButton as the handler for many different events (if it makes sense to do so) because it receives as an argument the event to process. Each event is derived from the 393 4807-7 ch21.F 394 5/24/01 9:00 AM Page 394 Part IV ✦ User Interfaces and Multimedia wxEvent class and has methods that identify the event source, type, and so on. For example, if you registered onButton to handle events from several different buttons, onButton could call the event’s GetId() method to determine which button was clicked. Tip Use the wxNewId() function to generate unique ID numbers. The onButton method pops open a standard message dialog, waits for you to click OK, and closes it. Fiddle around with the program until the basic structure makes sense and you’re comfortable with what’s happening. Conceptually, that’s the bulk of programming in wxPython — now you can just learn about other widgets besides buttons, and other events besides button-clicks. There’s plenty more to learn, of course, but the designers of wxPython have done an excellent job of insulating us from a lot of nasty details. Choosing Different Window Types The wxWindow class is the base class of all other windows (everything from the main application window to a button or a text label is considered a window). Of the window types that can contain child windows, there are two types: managed and nonmanaged. Tip Repeat ten times out loud: “A button is a window.” Nearly everything is a descendent of wxWindow; therefore, for example, if the documentation tells you that you can call some method to add a child window to a parent, bear in mind that the child window can be a panel, a button, a scrollbar, and so on. Managed windows A managed window is one that is directly controlled by the operating system’s window manager. The first type is one you’ve already seen, wxFrame, which often has a title bar, menus, and a status bar, and is usually resizable and movable by the user. wxMiniFrame is a wxFrame subclass that creates a tiny frame suitable for floating toolbars. A wxDialog window is similar to a wxFrame window and is usually used to request input or display a message. When created with the wxDIALOG_MODAL style, the calling program can’t receive any user input until the dialog box is closed. Managed window constructors are generally like wxWindow(parent, id, title[, position][, size][, style]), where parent can be None for managed windows, id can be –1 for a default ID, and style is a bitwise OR combination of several class-specific flags: 4807-7 ch21.F 5/24/01 9:00 AM Page 395 Chapter 21 ✦ Building User Interfaces with wxPython >>> from wxPython.wx import * >>> f = wxFrame(None,-1,’’, size=(200,100), style=wxRESIZE_BORDER) >>> f.Center(); f.Show(1) # Later, use f.Show(0) to kill it Nonmanaged windows Nonmanaged windows are controlled by wxPython, and you use them by placing them inside other windows. For example, the following creates a window with a resizable vertical split like the one shown in Figure 21-2: >>> >>> >>> 1 >>> 1 f = wxFrame(None,-1,’SplitterWindow’,size=(200,100)) s = wxSplitterWindow(f,-1) s.SplitVertically(wxWindow(s,-1),wxWindow(s,-1)) f.Show(1) Figure 21-2: A user-resizable splitter window Notice that wxSplitterWindow’s SplitVertically method takes as parameters the two windows it splits; for simplicity, I just created two plain windows. A wxPanel window is like a dialog box in that you place controls (buttons, text entry fields, and so on) in it, except that a panel lives inside another window such as a frame. The wxHtmlWindow class displays HTML files; you can even embed any wxPython widget within an HTML page and have it respond to events normally. Tip Consult demo.py in the wxPython distribution for information about embedding widgets in HTML pages. The demo also contains terrific examples of many other wxPython features. You can add scrolling to any window by first placing it inside a wxScrolledWindow instance. Be sure to call its SetScrollBars method to initialize the size of the scrollbars. Some windows, such as wxHtmlWindow, are derived from wxScrolledWindow, or already have scrolling support to save you the trouble. The wxGrid class gives your application a spreadsheet-like table with rows and columns. It has plenty of standard helpers for controlling user input or displaying data in certain ways, or you can implement your own grid cell renderers. The wxStatusBar and wxToolBar classes enable you to add a status bar and a toolbar to any frame (call the frame’s SetStatusBar and SetToolBar methods, respectively). In the wxPython.lib.floatbar module, you’ll find wxFloatBar, a 395 4807-7 ch21.F 396 5/24/01 9:00 AM Page 396 Part IV ✦ User Interfaces and Multimedia wxToolBar subclass implemented in Python that provides “dockable” toolbars that users can pull out of the frame and move elsewhere. Applications such as Microsoft Visual Studio enable you to open several files at a time, each in a separate child window that can’t leave the boundaries of a single parent window. wxPython enables you to create applications with this style of interface using the wxMDIChildFrame, wxMDIClientWindow, and wxMDIParentFrame classes. The program in Listing 21-2 creates a viewer for HTML files stored locally. Notice in Figure 21-3 that it uses a wxNotebook window to enable you to open several HTML files simultaneously, and the toolbar has buttons for adding and removing pages as well as quitting the application. Listing 21-2: grayul.py — A local HTML file viewer from wxPython.wx import * from wxPython.html import * from wxPython.lib.floatbar import * import time,os class BrowserFrame(wxFrame): ‘Creates a multi-pane viewer for local HTML files’ ID_ADD = 5000 ID_REMOVE = 5001 ID_QUIT = 5002 # Load support for viewing GIF files wxImage_AddHandler(wxGIFHandler()) def __init__(self): wxFrame.__init__(self, NULL, -1, ‘Grayul’) # Create a toolbar with Add, Remove, and Quit buttons tb = wxFloatBar(self,-1) addWin = wxButton(tb,self.ID_ADD,’Add new window’) removeWin = wxButton(tb,self.ID_REMOVE, ‘Remove current window’) quit = wxButton(tb,self.ID_QUIT,’Quit’) # Tie button clicks to some event handlers EVT_BUTTON(tb,self.ID_ADD,self.OnAdd) EVT_BUTTON(tb,self.ID_REMOVE,self.OnRemove) EVT_BUTTON(tb,self.ID_QUIT,self.OnQuit) # Add the buttons to the toolbar tb.AddControl(addWin) 4807-7 ch21.F 5/24/01 9:00 AM Page 397 Chapter 21 ✦ Building User Interfaces with wxPython tb.AddControl(removeWin) tb.AddSeparator() tb.AddControl(quit) tb.Realize() self.SetToolBar(tb) tb.SetFloatable(1) # Create a notebook to hold each window self.note = wxNotebook(self,-1) def GetFileName(self): ‘Gets the name of an HTML file from the user’ types = ‘HTML files|*.html;*.htm’ # Limit types to view dlg = wxFileDialog(self,style=wxOPEN|wxFILE_MUST_EXIST, wildcard=types) dlg.ShowModal() file = dlg.GetFilename() dlg.Destroy() return file def OnAdd(self,event): ‘Adds a new HTML window’ file = self.GetFileName() if file: newWin = wxHtmlWindow(self.note,-1) self.note.AddPage(newWin,os.path.split(file)[1],1) newWin.LoadPage(file) def OnRemove(self,event): ‘Removes the current HTML window’ page = self.note.GetSelection() if page != -1: self.note.DeletePage(page) self.note.AdvanceSelection() def OnQuit(self,event): self.Destroy() class App(wxApp): def OnInit(self): ‘Create the main window and insert the custom frame’ frame = BrowserFrame() frame.Show(true) return true # Create an app and go! app = App(0) app.MainLoop() 397 4807-7 ch21.F 398 5/24/01 9:00 AM Page 398 Part IV ✦ User Interfaces and Multimedia Figure 21-3: Build this simple viewer to display the documentation that ships with Python. This application uses an instance of the wxFloatBar class (a wxToolbar child) to create a floating toolbar. (Try it out — click on the toolbar and drag it around the screen. Close it or move it back over its original location to dock it.) Although I just added some normal buttons, you can use the AddTool method to add icons like the ones you find on toolbars in many applications. Using the wxNotebook class is straightforward; for each tab, create a new window that is a child of the notebook, and add it with a call to AddPage or InsertPage. Likewise, the wxHtmlWindow class is an easy way to display HTML pages. The BrowserFrame class definition contains a call to wxImage_AddHandler so that it can view CompuServe GIF files. A PyShellWindow enables users to access a Python interpreter running in interactive mode: from wxPython.wx import * from wxPython.lib.pyshell import PyShellWindow class App(wxApp): def OnInit(self): frame = wxFrame(None,-1,’MyPyShell’) PyShellWindow(frame,-1) frame.Show(true) return true app = App(0) app.MainLoop() 4807-7 ch21.F 5/24/01 9:00 AM Page 399 Chapter 21 ✦ Building User Interfaces with wxPython Using wxPython Controls wxPython ships with a comprehensive set of high-level controls, or widgets. Most often, you place them in a wxPanel or wxDialog, but they can be used elsewhere, such as in a status bar or toolbar. This section shows you what controls are available and how to use some of them; the process of controlling their layout is covered in the Controlling Layout section. Common controls Figure 21-4 shows most of the common controls available to you in wxPython. Figure 21-4: Names and examples of the common wxPython controls You can use wxButton and wxBitmapButton to trigger an event; use the EVT_BUTTON(id, func) function to link a button ID and an event handler. The FileBrowseButton button combines a button, a file dialog, and a text entry widget so that when clicked, the user browses for a file and the chosen file name ends up in the text entry field. FileBrowseButtonWithHistory’s text entry field has a drop-down list in which you can store previous choices. The wxGenButton class is a button class that is implemented by wxPython (and not natively) so that you can customize how the button behaves and how it looks when pressed. See the wxGenBitmapButton, wxGenToggleButton, and wxGenBitmapToggleButton for additional variations. Most controls let you attach event handlers when the user modifies the control’s state. For example, by using the EVT_CHECKBOX(id, func) function, your handler function will be called anytime the checkbox is toggled. 399 4807-7 ch21.F 400 5/24/01 9:00 AM Page 400 Part IV ✦ User Interfaces and Multimedia Controls with a user-defined value (such as a text entry widget) usually have one or more Get methods to retrieve the user’s input. wxSlider.GetValue(), for example, returns the current position of the slider. Controls that let users choose from a predefined set of values usually have methods such as GetSelection. wxChoice.GetSelection() returns the 0-based index of the currently selected string. Each Get method of a control usually has a corresponding Set method that you can use to programmatically set the control’s state. Tree controls wxTreeCtrl is the standard tree control in wxPython. Use the code in Listing 21-3 to create the tree shown in Figure 21-5. Figure 21-5: wxPython’s tree control showing the results of nested dir() calls Listing 21-3: treedemo.py — Sample using wxTreeCtrl from wxPython.wx import * class TreeFrame(wxFrame): def __init__(self): wxFrame.__init__(self, NULL, -1, ‘Tree Demo’,size=(300,400)) # Make it a scrolled window so all data fits scroll = wxScrolledWindow(self,-1) self.tree = wxTreeCtrl(scroll) EVT_SIZE(scroll,self.OnSize) 4807-7 ch21.F 5/24/01 9:00 AM Page 401 Chapter 21 ✦ Building User Interfaces with wxPython # Populate a small tree parent = self.tree.AddRoot(‘dir()’) for i in dir(): child = self.tree.AppendItem(parent,i) for j in dir(i): grandchild = self.tree.AppendItem(child,j) def OnSize(self, event): # Make the tree control the size of the client area self.tree.SetSize(self.GetClientSizeTuple()) class App(wxApp): def OnInit(self): ‘Create the main window and insert the custom frame’ frame = TreeFrame() frame.Show(true) return true app = App(0) app.MainLoop() Apart from the usual initialization work, there is code to populate the tree and to ensure that the tree control fills the entire client area of the frame (using the EVT_SIZE event function). You create a root node with a call to AddRoot, and then add children with AppendItem calls. Refer to the documentation for information about other features, including support for event notification, editing items, and using icons in the tree. wxPython.lib.mvctree has the wxMVCTree class, which is a tree control that uses a model-view-control architecture in which code to display the information is largely independent of the code to store the data. Such a model enables you to change one with little or no change to the other. Editor controls The wxEditor and wxPyEditor classes (in wxPython.lib.editor) are rudimentary text editor controls (wxPyEditor is a wxEditor subclass that adds syntax highlighting). A more heavyweight and advanced edit control is wxStyledTextCtrl (in wxPython.stc). It enables you to mix different fonts and font attributes much like a word processor, and it has built-in syntax highlighting for a few languages, including Python. Controlling Layout When you put more than one control into a panel, dialog box, or other container, you have to decide how you want to lay out, or organize, them. In some cases, you 401 4807-7 ch21.F 402 5/24/01 9:00 AM Page 402 Part IV ✦ User Interfaces and Multimedia can get by with specifying exact x and y coordinates for the controls. Other times, you need to correctly handle layout if there is a change in window size, default font (vision-impaired users often use a larger default font, for example), or platform (this is Python, after all). wxPython gives you several mechanisms to control the layout. Tip It’s important to learn what layout options are available to you, but if you plan to build a lot of user interfaces, consider acquiring a tool such as wxDesigner, Boa Constructor, or wxStudio to help you out. As you learn about the different types of layout mechanisms, don’t be fooled into thinking that you always have to choose one to the exclusion of another. You should use whatever works best for your particular situation, and that may mean mixing them together. You can’t combine them within the same container (a panel, window, and so on), but you can have child containers use different methods. For example, your GUI could have two panels, one that uses sizers and one that uses layout constraints; and then you can lay them both out in the main window using hard-coded coordinates. Specifying coordinates The simplest way is occasionally the best. The constructor for every control takes two optional parameters, size and pos, that specify the control’s size and position, respectively: >>> >>> >>> 1 >>> >>> from wxPython.wx import * dlg = wxDialog(None,-1,’Hey’,size=(200,200)) dlg.Show(1) dlg.SetSize((200,200)) wxButton(dlg,-1,’Quit’,pos=(10,100),size=(100,25)) Using size and pos, you can manually control the exact size and position of each control. It can be pretty tedious, however, so if this is the route you choose, build your GUI in an interactive Python session so that you can fine-tune it without having to re-run your program. Tip After you’ve added a control to a container, you can adjust its size and position by calling its SetSize and SetPosition methods: myButton.SetSize((200,100)) # Both methods take a tuple wxWindows ships with a simple dialog editor (and documentation) that creates a WXR file describing the layout of your dialog box, and you can use WXR files in wxWindows or wxPython programs. For example, if you have a file called sample.wxr and it contains the definition for a dialog box named ‘myDialog’, you could open the dialog as follows: ... wxResourceParseFile(‘sample.wxr’) dlg = wxDialog(parent, -1, ‘’) 4807-7 ch21.F 5/24/01 9:00 AM Page 403 Chapter 21 ✦ Building User Interfaces with wxPython dlg.LoadFromResource(parent,’MyDialog’) dlg.ShowModal() ... The call to wxResourceParseFile needs to happen only once, so you could call it during initialization. Tip If your dialog box looks great in wxPython’s dialog editor, but looks compressed or otherwise messed up in your program, toggle the useDialogUnits flag in the dialog box’s properties in the editor. The downside to using fixed coordinates is that, well, they’re fixed. A well-organized dialog box on one platform may look lousy on another, and if you have to change something later, you might end up doing a lot of extra work. One alternative is to create a different version of the resource file for each platform, and load the appropriate one on startup. Despite these potential problems, precise widget layout sometimes requires less effort than wxPython’s other layout mechanisms, so you’ll have to judge for yourself. One approach that has helped me is to sketch out on paper the GUI I plan to build and then divide it up into small groups of controls. Implement each group with a wxPanel that has its controls laid out at specific coordinates, and then use sizers (see the next section) to add the different groups to the window. Sizers Sizers are objects that help control window layout by dividing a window into subwindows that are laid out according to sizer rules. A sizer talks to all of its child objects to determine its own minimum size, which it reports to its parent. You can nest sizers inside other sizers to form an arbitrarily complex and deep nesting. The sizers you’ll use are children classes of wxSizer, but if you want to create your own sizer type, you should derive it from wxPySizer. Box sizers wxBoxSizer and wxStaticBoxSizer are the simplest forms of sizers, and the two are the same except that wxStaticBoxSizer includes a wxStaticBox control around the outside of all of its children objects. A box sizer lays out controls to form either a row or a column, which you choose when you create the sizer: sizer = wxBoxSizer(wxVERTICAL) # A sizer that creates a column box = wxStaticBox(myFrame, -1, ‘Stuff’) sizer = wxStaticBoxSizer(box, wxHORIZONTAL) # A row with border The direction you choose is called its primary orientation, so a wxBoxSizer with wxVERTICAL has a vertical primary orientation. Once you have your sizer, you add objects to it using its Add or Prepend methods (Add puts the new object at the end of the group, Prepend at the beginning), which have the following forms: 403 4807-7 ch21.F 404 5/24/01 9:00 AM Page 404 Part IV ✦ User Interfaces and Multimedia sizer.Add(window, option, flag, border) # Add window or widget sizer.Add(sizer, option, flag, border) # Add a child sizer sizer.Add(w, h, option, flag, border) # Add a spacer When you add a window or control, keep in mind that when you create the control, it is still a child of a window, not a sizer (so don’t try to use the sizer as the parent argument in the control’s constructor). You can pass to Add (or Prepend) a control or window, a child sizer (which may in turn contain other sizers), or the width and height of an invisible spacer object to pad between two items. When the sizer is laying out its items and has extra space along its primary orientation, it looks at the option argument to determine how much extra space to give to each one. A value of 0 means that that item does not change size. If one item has an option value of 1 and another has a value of 2, the second item will get twice as much space as the first. The flag argument is a bitwise OR of several values that tell the sizer the border type to use around the item and what it should do with extra space along the opposite, or secondary, orientation. The border can be any combination of wxTOP, wxBOTTOM, wxLEFT, or wxRIGHT (wxALL puts them all together for you). For example, if you want a blank border around the top and left sides of your widget, you could use a flag of wxTOP | wxLEFT. If the flag value contains wxGROW (or wxEXPAND), the item will grow to fill the available extra space. A value of wxSHAPED means that it will grow proportionally so that it always maintains the original aspect (width-to-height) ratio. Instead of growing, the item can remain aligned against a side (by using wxALIGN_LEFT, wxALIGN_ CENTER, wxALIGN_RIGHT, wxALIGN_TOP, or wxALIGN_BOTTOM). The border argument is the number of pixels of padding around the item, and it makes sense only if the flag argument specifies one or more borders (such as wxTOP). Tip The sizers also have an AddMany method that you can use to combine multiple Add calls. Call the parent window’s SetSizer(sizer) method to tell it to use your new sizer. When the window’s Layout() method is called, the window will lay out its contents with help from the sizer. An alternative is to call the window’s SetAutoLayout(1) method so that it automatically calls Layout anytime the window size changes. The sizer.Fit(window) method resizes the parent window to the minimum acceptable size of its contents. If you then call sizer.SetSizeHints(window), the sizer will remember the current size as the minimum and prevent the user from ever making the window smaller than that minimum. Before all of this seeps out of your brain, try the following code so you can see a wxBoxSizer in action: 4807-7 ch21.F 5/24/01 9:00 AM Page 405 Chapter 21 ✦ Building User Interfaces with wxPython >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> from wxPython.wx import * f = wxFrame(None,-1,’Sizer Test’) f.Show(1) sizer = wxBoxSizer(wxVERTICAL) sizer.Add(wxButton(f,-1,’One’),1,wxALL|wxALIGN_LEFT,3) sizer.Add(wxButton(f,-1,’Two’),2,wxALIGN_RIGHT) sizer.Add(wxButton(f,-1,’Three’),2,wxALL|wxALIGN_CENTER,3) sizer.Add(10,10,2,wxALL,3) sizer.Add(wxButton(f,-1,’Four’),4,wxALL|wxGROW,3) sizer.Add(wxButton(f,-1,’Five’),4,wxALL,3) f.SetAutoLayout(1) f.SetSizer(sizer) sizer.Fit(f) sizer.SetSizeHints(f) Resize the window in each direction, and once you’re done playing, use f.Show(0) to make the window go away. As shown in Figure 21-6, vertically (the primary orientation) the buttons grow according to the option value used (for example, button Five is four times as tall as button One). Most of the buttons have a three-pixel border on all sides, and their horizontal alignment, or stretching, follows the flag values. Figure 21-6: Buttons resize and align according to the rules of the box sizer. A good exercise for you to try now would be to replace one of the buttons with a horizontal wxBoxSizer that also contains buttons of its own. This forms a row of buttons that are treated as a single unit by the parent sizer, but are laid out individually by the child sizer. This will help you see how you can use a hierarchy of nested sizers to achieve a complex layout. Grid sizers wxGridSizer lays out objects in a table. The width of each column is the width of the widest item in the grid; and the height of each row is that of the tallest item. You 405 4807-7 ch21.F 406 5/24/01 9:00 AM Page 406 Part IV ✦ User Interfaces and Multimedia create this sizer by calling wxGridSizer([rows|cols]=n), where n is the number of rows or columns you want. You choose either rows or cols to limit the number of rows or columns, and wxGridSizer figures out the correct value for the other dimension. For example, if you set a limit of two rows and then added seven buttons to the sizer, the first row would have the first four buttons, and then second row would have the last three buttons. wxFlexGridSizer is like wxGridSizer except that instead of having uniform column and row sizes, each column is the width of the widest item in that column only; and the height of each row is that of the tallest item in that row only. Layout constraints Layout constraints define the size and position of an item in terms of its siblings or parents. Each item has eight constraints that you can define: four for the edges (left, right, top, and bottom), two for the size (width and height), and two for its center (x, y). For example, you might constrain a button by specifying that its height should be left unchanged, its left edge should be aligned with that of some other button, its width should be half that of the parent panel, and its center y coordinate should match that of some other widget’s top: wc = wxLayoutConstraints() wc.height.AsIs() # “Don’t change it” wc.left.SameAs(someButton, wxLeft) wc.width.PercentOf(parentPanel, 50) wc.centerY.SameAs(someOtherWidget, wxTop) myButton.SetConstraints(wc) You usually have to specify four of the eight constraints in order for the widget to be fully constrained. Once it is fully constrained, the layout algorithm can deduce the remaining constraints on its own. The constraint names are left, right, top, bottom, width, height, centerX, and centerY. You can call the following methods for each constraint: Above(win[, margin]), Below(win[, margin]), LeftOf(win[, margin]), RightOf(win[,margin]) Sets the constraint to be above, below, to the left of, or to the right of the window win, with an optional margin Absolute(value) Sets the constraint to this value. For example, wc.left.Absolute(10) gives the left edge an x coordinate of 10. AsIs() Does not change the constraint’s current value Unconstrained() Returns this constraint to its default state 4807-7 ch21.F 5/24/01 9:00 AM Page 407 Chapter 21 ✦ Building User Interfaces with wxPython PercentOf (win,edge,percent) Makes the current constraint a percentage of the given edge of the given window SameAs (win, edge[, margin]) Makes the current constraint the same as the given edge of the given window As with sizers, you can call a window’s Layout() method to perform the layout, or you can call SetAutoLayout(1) so that Layout is called each time the parent window is resized. Layout algorithms For MDI or SDI applications, you can use the wxLayoutAlgorithm class to lay out subwindows. Study the wxLayoutAlgorithm and wxSashLayoutWindow documentation for more information. Using Built-in Dialogs One of wxPython’s strengths is its rich set of built-in dialogs that you can use to get user input. In general, the way you use each dialog follows this pattern (the example here uses a dialog that has the user choose a directory name): dlg = wxDirDialog(None) if dlg.ShowModal() == wxID_OK: path = dlg.GetPath() dlg.Destroy() # # # # Create it Check the return code Read user’s input Destroy it The dialog’s ShowModal method usually returns wxID_OK or wxID_CANCEL, and each dialog has its own set of methods you use to retrieve the user’s input. Table 21-1 describes some of wxPython’s useful built-in dialogs. Table 21-1 Useful wxPython Dialogs Class Use the Dialog To wxDirDialog Browse for a directory name wxFileDialog Browse for a file name wxFontDialog Choose a font, point size, color, and so on wxColourDialog Choose a color wxPrintDialog Select a printer Continued 407 4807-7 ch21.F 408 5/24/01 9:00 AM Page 408 Part IV ✦ User Interfaces and Multimedia Table 21-1 (continued) Class Use the Dialog To wxPageSetupDialog Modify page orientation and margins wxProgressDialog Display a moving progress meter wxMessageDialog Display a simple message wxScrolledMessageDialog Display a longer message in a scrollable window wxSingleChoiceDialog Choose an item from a list wxMultipleChoiceDialog Choose one or more items from a list wxTextEntryDialog Enter a line of text wxBusyInfo Notify the user that the program is temporarily busy The wxBusyInfo dialog is unique in that the dialog appears as soon as you create it, and it disappears when the object goes out of scope: def rollbackChanges(self): wxBusyInfo(‘Reverting to previous state...’) # Do some work, dialog destroyed automagically when done Drawing with Device Contexts Like some other GUI frameworks, wxPython uses device contexts as an abstraction for displaying information on some output device. All device contexts are descendents of the wxDC class, so code that outputs to a device context automatically works whether the output device is the screen, a printer, or just a file. Table 21-2 lists some common device context classes. Table 21-2 wxPython Device Context Classes Class Outputs To wxWindowDC An entire window, including title bars and borders wxClientDC Window client area outside of the OnPaint method wxPaintDC Window client area during a call to OnPaint wxPrinterDC A Microsoft Windows printer wxPostScriptDC A PostScript file or printer wxMemoryDC A bitmap wxMetaFileDC A Microsoft Windows metafile 4807-7 ch21.F 5/24/01 9:00 AM Page 409 Chapter 21 ✦ Building User Interfaces with wxPython Device contexts give you a large number of methods to perform all sorts of actions, including clipping; writing text; converting between different units; and drawing graphics primitives, including lines, arcs, and splines. Tip To ensure that your programs work on Microsoft Windows, before drawing, call the device context’s BeginDrawing() method; and call its EndDrawing() method when you’re done. The device context uses the current pen to draw lines and outlines; pens (wxPen) have attributes such as line thickness and color. Text color is not affected by pen color. To fill in regions, it uses the current brush (wxBrush), which can have both a color and a pattern that it uses when filling. The program in Listing 21-6 shows you how to use a device context to paint on the screen, and generates output as shown in Figure 21-7. Listing 21-6: wxcanvas.py – An example of drawing with device contexts from wxPython.wx import * import whrandom class CanvasFrame(wxFrame): # A list of stock brushes we can use instead of # creating our own brushes = [wxBLACK_BRUSH,wxBLUE_BRUSH, wxCYAN_BRUSH,wxGREEN_BRUSH, wxGREY_BRUSH,wxRED_BRUSH,wxWHITE_BRUSH] def __init__(self): wxFrame.__init__(self,None,-1, ‘CanvasFrame’,size=(550,350)) self.SetBackgroundColour (wxNamedColor(“WHITE”)) # Capture the paint message EVT_PAINT(self, self.OnPaint) def OnPaint(self, event): dc = wxPaintDC(self) dc.BeginDrawing() # Draw a grid of randomly colored boxes for y in range(15): for x in range(10): dc.SetBrush(whrandom.choice(self.brushes)) dc.DrawRectangle(x*20,y*20,20,20) # Draw a random polygon over the boxes # (Outline is in blue, but fill color is that Continued 409 4807-7 ch21.F 410 5/24/01 9:00 AM Page 410 Part IV ✦ User Interfaces and Multimedia Listing 21-6 (continued) # of the last box it drew) dc.SetPen(wxPen(wxNamedColour (‘BLUE’))) pts = for i in range(20): pts.append((whrandom.randint(0,200), whrandom.randint(0,300))) dc.DrawPolygon(pts) # Draw some rotated text font = wxFont(20, wxNORMAL, wxNORMAL, wxNORMAL) font.SetFaceName(‘Jokerman LET’) dc.SetFont(font) for a in range(0, 360, 20): c = a * 0.71 # 360/255, fit angle into color range dc.SetTextForeground(wxColour (c,c,c)) dc.DrawRotatedText(“ wxPython”, 350, 150, a) dc.EndDrawing() class App(wxApp): def OnInit(self): ‘Create the main window and insert the custom frame’ frame = CanvasFrame() frame.Show(true) return true app = App(0) app.MainLoop() Figure 21-7: Using device contexts to draw graphics 4807-7 ch21.F 5/24/01 9:00 AM Page 411 Chapter 21 ✦ Building User Interfaces with wxPython The __init__ function calls EVT_PAINT so that the OnPaint method will be called each time the screen needs to be redrawn. Notice that OnPaint creates a wxPaintDC for drawing, and that it begins and ends with calls to BeginDrawing and EndDrawing. Adding Menus and Keyboard Shortcuts Your wxPython application can have popup menus or groups of menus on a menu bar at the top of a frame. Individual menu items can be disabled or grayed out, and each can have an associated line of help text. A menu consists of one or more menu items, each of which has a unique numerical identifier. Create a menu by calling wxMenu([title]), and add items with its Append(id, name) method: menu = wxMenu() menu.Append(10, ‘Load’) menu.Append(11, ‘Save’) menu.Append(12, ‘Quit’) The menu title is displayed as part of the menu’s contents. Create a menu bar by calling wxMenuBar(). Attach a menu to a menu bar by calling the menu bar’s Append(menu, title) method: mb = wxMenuBar() mb.Append(menu, ‘File’) Finally, call a frame’s SetMenuBar(bar) method to attach the menu bar to the frame: frame.SetMenuBar(mb) Tip By creating menu items separately as wxMenuItems, you can create more powerful menu items, such as menu items with bitmaps. Accelerators are keyboard shortcuts for commands users would normally have to generate with the mouse (clicking a menu item, for example). By calling a window’s SetAcceleratorTable(table) method, you can assign a group of shortcuts to that window. You create an accelerator table by calling the wxAcceleratorTable(list) constructor, where list is a list of accelerator entry tuples of the form (flag, code, command). flag is a bitwise-OR combination of keypress modifiers such as wxACCEL_ALT and wxACCEL_SHIFT, and code is the ASCII code of the keypress or one of wxPython’s many special key variables, such as WXF_10 (for the F10 key) or WXK_END (the End key). command is the menu item identifier. For example: 411 4807-7 ch21.F 412 5/24/01 9:00 AM Page 412 Part IV ✦ User Interfaces and Multimedia accel = [(wxACCEL_CTRL,WXK_ESCAPE,10), (wxACCEL_NORMAL,WXK_ESCAPE,11), (wxACCEL_CTRL|wxACCEL_SHIFT,WXK_F1,12)] frame.SetAcceleratorTable(wxAcceleratorTable(accel)) enables Ctrl-Esc, Esc, and Ctrl-Shift-F1 as accelerators for menu commands 10 through 12. Accessing Mouse and Keyboard Input Most input events are handled by wxPython directly. When a user clicks a button, for example, the window automatically processes the clicking and releasing of the mouse button. If necessary, however, you can intercept and handle this lower-level input. When you call EVT_CHAR(win, func), future keystrokes (“normal” keys, but not modifiers such as Ctrl or Shift) directed to win will cause wxKeyEvents to be sent to func. Use EVT_CHAR_HOOK to catch modifier keypresses, and EVT_KEY_UP and EVT_KEY_DOWN to be notified when keys are pressed or released. Tip Only one window has keyboard focus at any time, so your window will receive keystroke notifications only if it has the focus. Use the window’s SetFocus() method to acquire keyboard focus. If you want only to intercept some input but let wxPython handle the rest, your handler function can pass the input on to the window’s normal handler. For example, if you want a keypress to be interpreted using the normal behavior, your handler should call the window’s OnChar method. For catching mouse button click events, use EVT_LEFT_DOWN, EVT_LEFT_UP, and EVT_DCLICK to capture mouse left button presses, releases, and double-clicks, respectively. There are corresponding functions for the middle and right buttons as well. EVT_MOTION causes each mouse movement to be reported, and use EVT_ENTER_WINDOW and EVT_LEAVE_WINDOW to be notified when the window has mouse focus. If you want to process all mouse events, just use EVT_MOUSE_EVENTS to capture them all. Other wxPython Features As mentioned before, wxPython has far more features than can adequately be covered in one chapter. This final section is here to pique your interest enough to do some investigating on your own, and to ensure that you don’t invest a lot of time implementing something that wxPython already has. 4807-7 ch21.F 5/24/01 9:00 AM Page 413 Chapter 21 ✦ Building User Interfaces with wxPython Clipboard, drag and drop, and cursors You can create and change mouse cursors and tool tips with the wxCursor and wxToolTip classes and their children. The wxClipboard, wxDataFormat, and wxDataObject class hierarchies implement support for transferring data to and from the clipboard and converting it between different formats. The wxDragImage class is useful for implementing your own visual representation of dragging a file or other object in your application. See the wxDropSource and wxDropTarget classes too. By calling a window’s SetCursor(cursor) method, the mouse cursor will change to the given cursor any time it enters the window. You can create your own cursor or use one of the built-in cursors: myFrame.SetCursor(wxStockCursor(wxCURSOR_BULLSEYE)) Graphics The Object Graphics Library (OGL) is a library for creating and easily manipulating flowcharts and other graphs. See the wxShapeCanvas, wxShape, and wxDiagram classes for more information. wxBitmap, wxImage, and wxIcon all deal with loading and displaying images in different ways. For each file type you use, you must load a wxImageHandler instance that handles decoding the image data (wxPython comes with several, such as wxJPEGHandler and wxGIFHandler). See also the wxMask and wxPalette classes. If you have installed the PyOpenGL extension module, you can use wxGLCanvas to include an OpenGL window in your application. Date and time wxPython has powerful date and time support (covering dates even hundreds of millions of years in the future). wxDateTime represents a specific point in time, whereas wxDateSpan and wxTimeSpan represent intervals. The wxCalendarCtrl is a control that looks like a wall calendar and is useful for both displaying and inputting dates. Fonts wxFont objects hold information about fonts, and wxFontData objects hold infor- mation about the dialogs users use to choose fonts and set font properties. 413 4807-7 ch21.F 414 5/24/01 9:00 AM Page 414 Part IV ✦ User Interfaces and Multimedia HTML The wxPython.html module contains classes for parsing, printing, and displaying HTML pages in a window or a device context. Printing wxPrintDialog and wxPageSetupDialog wrap two dialogs used for configuring the printer and page in preparation for printing, and wxPrinter and wxPrintout take care of the actual printing. There are also the wxPrintPreview and wxPreviewFrames classes for supporting print preview. Other Finally, if you’re using Windows and want to use COM, you can dynamically create a wxWindows-like class to embed any ActiveX control in your application by using wxPython.lib.activexwrapper.MakeActiveXClass. Summary wxPython is a powerful library for creating cross-platform GUI applications. It has a full set of simple and high-level controls, including built-in support for trees and tables; and it is very easy to use. In this chapter you: ✦ Learned the basic structure of most wxPython applications. ✦ Created powerful and functional GUI-based applications in very few lines of code. ✦ Used wxPython’s built-in dialogs for browsing for files, choosing colors, and so on. ✦ Reviewed the different types of windows, controls, and features that wxPython provides. The next chapter shows you how to use the curses (not the spoken kind) library to create text-based user interfaces. ✦ ✦ ✦ 4807-7 ch22.F 5/24/01 9:00 AM Page 415 22 CHAPTER Using Curses C urses is a library for handling a text-based display terminal. It is widely used on UNIX. It can handle text windows, colors, and keyboard input. Moreover, it saves you the trouble of learning the control codes for every kind of terminal. A Curses Overview In ancient days of yore, there was not a computer in every office. People used terminals like the VT100 to connect to a central system. These terminals displayed a grid on which each square contained a text character. Sending control codes to the terminal could change the color, move the cursor, and so on. However, the magical control codes varied between systems. Therefore, a program that produced cute output on a Tektronix 4105 terminal might have produced bizarre symbol salad on a VT230. The curses library was born as a portable tool for text display. It has been eclipsed by ncurses, which adds some features. The Python module curses is a thin wrapper for the ncurses API. The various functions in the curses API have some overlap — for example, the window methods addch, addstr, and addnstr all print text. For purposes of brevity, this chapter omits many redundant items. Curses provides a class, WindowObject, for display. You can use one or more windows, resize them, move them, and so forth. Note In curses, the top-left corner square of the screen has coordinates (0,0). Screen coordinates in curses are given with vertical position first — (y, x). This is the opposite of the usual ordering, so be careful not to get your coordinates reversed! Listing 22-1 provides a simple curses program. Run it to get some quick gratification (and to make sure that curses is installed on your system!) ✦ ✦ ✦ ✦ In This Chapter A Curses overview Starting up and shutting down Displaying and erasing text Moving the cursor Getting user input Managing windows Editing text Using color Example: a simple maze game ✦ ✦ ✦ ✦ 4807-7 ch22.F 416 5/24/01 9:00 AM Page 416 Part IV ✦ User Interfaces and Multimedia Listing 22-1: CurseWorld.py import curses try: MainWindow=curses.initscr() # initialize curses MainWindow.addstr(“Hello, damn it!”) MainWindow.refresh() MainWindow.getch() # Read a keystroke finally: curses.endwin() # de-initialize curses Starting Up and Shutting Down The function initscr initializes curses and returns a Window object representing the whole screen. The function endwin de-initializes curses. The function isendwin returns true if endwin has been called. The module function wrapper(mainfunc,*args) handles typical setup and shutdown for you. Calling wrapper sets up curses, creates a window, and calls mainfunc(window,*args). It also restores the terminal to normal when your main function completes, even if it terminates abnormally. This is important, because a curses program that doesn’t call endwin may leave the shell in a highly weird state! For reference, wrapper does (and later undoes) the following things: ✦ Creates a window (curses.initscr()) ✦ Turns off echo (curses.noecho()) ✦ Turns off keyboard buffering (curses.cbreak()) ✦ Activates color, where available (curses.start_color()) Caution The functions filter and use_env, which must be called before initscr, do not work (as of Python 2.0 and 2.1). Displaying and Erasing Text The window method addstr([y,x,]text[,attributes]) prints the string text at screen position (y, x) — by default, at the current cursor position. You can specify attributes to control the appearance of the text. Attributes can be combined by bitwise-OR. See Table 22-1 for a list of available text attributes: 4807-7 ch22.F 5/24/01 9:00 AM Page 417 Chapter 22 ✦ Using Curses Table 22-1 Text Attributes Attribute Meaning A_BLINK Blinking text A_BOLD Bold text A_DIM Dim text A_NORMAL Ordinary text A_STANDOUT Highlighted text A_UNDERLINE Underlined text For example, the following code prints a bold, blinking “Howdy!” at column 50 of row 5: MainWindow.addstr(5,50,”Howdy!”,curses.A_BLINK | curses.A_BOLD) Inserting addstr overwrites any text that was already on the window. To insert text, call insstr([y,x,]str[,attributes]). Any characters on the line are moved to the right; characters moved off the right edge of the screen are lost. A call to insertln inserts a blank row under the cursor; all following rows move down by one. Default attributes The method attrset(attributes) sets the default attributes for all subsequent calls to addstr. The methods attron(attribute) and attroff(attribute) toggle one default attribute. Reading from the window (screen-scraping) The method inch(y,x) returns the character at the given window position. Actually, it returns the character as a number in the lower eight bits, and the attributes in the upper twenty-four bits. Therefore, the following code would check for a bold X at row 3, column 10: Character= MainWindow.inch(3,10) Letter = chr(Character & 0xFF) Attributes = Character & (~0xFF) return ((Attributes & curses.A_BOLD) and (Letter==”X”)) The method instr([y,x,]n) returns a string of n characters, extracted from the specified screen position. It ignores attribute information. 417 4807-7 ch22.F 418 5/24/01 9:00 AM Page 418 Part IV ✦ User Interfaces and Multimedia Erasing The method erase clears the window. clrtoeol erases from the current cursor position to the end of the line; clrtobot also clears all lines below the cursor. The method delch([y,x]) erases a single character (by default, the one under the cursor) — characters to its right move left by one square. deleteln deletes the line under the cursor — any following lines move up by one row. Refreshing After changing the contents of a window, call its refresh method to repaint the actual screen. If you get tired of calling refresh, call immedok(flag) to set the “immediate refresh” flag — if the flag is set, the window will be repainted after every change. However, note that this can result in reduced speed and/or flickering. If you are using several windows at once, the most efficient way to repaint is to call the noutrefresh method of a window (instead of refresh), and then call the doupdate function. You can flag a window as “dirty” to ensure that it will be redrawn at the next refresh call. The methods touchwin and untouchwin mark the entire window as dirty or clean, respectively. touchline(y,count) marks count lines as dirty, starting with line y. The methods is_linetouched(y) and is_wintouched return true if the specified line, or the window itself, is dirty. Boxes and lines The method border draws a border around the window’s edges. The border is made up of individual characters. If you like, you can specify the characters to display, by passing them (as integers) to border(W,E,N,S,NW,NE,SW,SE). Here, S is the character to use for the bottom edge, NE is the character to use for the topright corner, and so forth. Pass 0 as a character to use the default. You can draw an arbitrary box by calling curses.textpad.rectangle(window,Top,Left,Bottom,Right). The box uses line-drawing characters where available. Otherwise, it will fall back to standard ASCII-art pluses, pipes, and dashes. The window background Windows have a background. The method bkgdset(character[,attributes]) changes the window’s background. When the window (or a portion of it) is erased, it is painted with character, with the specified attributes. Furthermore, the specified attributes are combined with any nonblank characters drawn on the window. The similar method bkgd(character[,attributes]) immediately paints blank squares of the window with character. 4807-7 ch22.F 5/24/01 9:00 AM Page 419 Chapter 22 ✦ Using Curses Example: masking a box Listing 22-2 illustrates a simple Mask class, for temporarily covering a part of the screen. A mask can cover a rectangular block of a window with a call to cover, and then restore the original text with a call to reveal. Listing 22-2: Mask.py import curses class Mask: def __init__(self,Window,Top,Bottom,Left,Right): self.Window=Window self.Top=Top self.Bottom=Bottom self.Left=Left self.Right=Right self.OldText=None def Cover(self,Character=”X”,Attributes=curses.A_DIM): # Cover the current screen contents. Store # them in OldText[RowIndex][ColumnIndex] for later: self.OldText= for Row in range(self.Top,self.Bottom+1): self.OldText.append() for Col in range(self.Left, self.Right+1): self.OldText[-1].append(\ self.Window.inch(Row,Col)) self.Window.addstr(Row,Col, Character,Attributes) def Reveal(self): if (self.OldText==None): return for Row in range(self.Top,self.Bottom+1): CurrentLine=self.OldText[Row-self.Top] for Col in range(self.Left, self.Right+1): CurrentCol=(Col-self.Left) Character=chr(CurrentLine[CurrentCol] & 0xFF) Attributes=CurrentLine[CurrentCol] & (~0xFF) self.Window.addstr(Row,Col, Character,Attributes) def Main(MainWindow): MainWindow.addstr(10,10,”Yes it is!”) MainWindow.addstr(11,10,”No it isn’t!”,curses.A_BOLD) MainWindow.addstr(12,10,”Yes it is!”,curses.A_UNDERLINE) MainWindow.addstr(13,10,”No it isn’t!”,curses.A_STANDOUT) MainWindow.addstr(14,10,”YES IT IS!”,curses.A_BOLD) MyMask=Mask(MainWindow,10,20,10,40) MainWindow.refresh() MainWindow.getch() Continued 419 4807-7 ch22.F 420 5/24/01 9:00 AM Page 420 Part IV ✦ User Interfaces and Multimedia Listing 22-2 (continued) MyMask.Cover() MainWindow.refresh() MainWindow.getch() MyMask.Reveal() MainWindow.refresh() MainWindow.getch() if (__name__==”__main__”): curses.wrapper(Main) Moving the Cursor The function getsyx returns the cursor’s screen position in the form of a tuple (y, x). The function setsyx(y,x) moves the cursor to the specified position. The window methods getyx and move(y,x) check and set the cursor position within a window. If the window fills the screen (as the window returned by a call to initscr does), window positioning is the same as screen positioning. The window method getparyx returns the window’s coordinates relative to its parent window. These coordinates are the location (in the parent) of the window’s top-left corner. If the window has no parent, getparyx returns (-1, -1). Note that cursor position is tracked independently by every window. The window method getmaxyx returns the size of the window in a tuple of the form (height, width). Note that getmaxyx()[0] is not a valid y-coordinate, as row numbering is 0-based; the last row of the screen has y-coordinate getmaxyx()[0]-1. The same is true for x-coordinates. The window method leaveok (flag) toggles the “Leave-the-cursor-where-it-isafter-repainting-the screen” flag. Calling leaveok(1) is a good idea if a blinking cursor won’t convey useful information to the user. If the flag is set, getsyx returns (-1, -1); calling setsyx(-1,-1) sets the flag to true. The function curs_set(visibility) sets the cursor visibility to 0 (invisible); 1 (visible — often an underline); or 2 (very visible — often a block). The return value of curs_set is the old visibility level. Listing 22-3 paints a spiral pattern on the window, using cursor positioning. 4807-7 ch22.F 5/24/01 9:00 AM Page 421 Chapter 22 ✦ Using Curses Listing 22-3: Spiral.py import curses import math def DrawSpiral(Window,CenterY,CenterX,Height,Width): ScalingFactor=1.0 Angle=0 HalfHeight = float(Height)/2 HalfWidth = float(Width)/2 while (ScalingFactor>0): Y = CenterY + (HalfHeight*math.sin(Angle)*ScalingFactor) X = CenterX + (HalfWidth*math.cos(Angle)*ScalingFactor) Window.move(int(Y),int(X)) Window.addstr(“*”) Angle+=0.05 ScalingFactor=ScalingFactor - 0.001 Window.refresh() def Main(Window): (Height,Width)=Window.getmaxyx() Height-=1 # Don’t make the spiral too big Width-=1 CenterY=Height/2 CenterX=Width/2 DrawSpiral(Window,CenterY,CenterX,Height,Width) Window.getch() if __name__==”__main__”: curses.wrapper(Main) Getting User Input Curses starts out in cooked mode — the user’s keyboard input is buffered and processed one line at a time. In raw mode, buffering is turned off, and keys are processed as they are pressed. Call the functions raw and noraw to toggle between modes. In addition, you can call cbreak and nocbreak to switch cbreak mode (also known as “rare” mode) on and off. The difference between cbreak and raw is that special characters (such as suspend) lose their normal effects in raw mode. The four modes (raw, noraw, cbreak, and nocbreak) are mutually exclusive. The window method keypad(flag) toggles keypad mode for a window. If keypad mode is not set, special character codes are not interpreted by curses. This means that special keystrokes such as function keys will put several special characters 421 4807-7 ch22.F 422 5/24/01 9:00 AM Page 422 Part IV ✦ User Interfaces and Multimedia into the keyboard buffer, extended keystrokes will not be available, and mouse events will not be available. In general, you want keypad mode on! Call echo and noecho to toggle the automatic echoing of user input to the screen. By default, echoing is on; curses.wrapper turns echoing off and switches to cbreak mode. Reading keys The window method getch reads a character and returns it as an integer. For an ASCII character, the value returned is the character’s ASCII value (as returned by ord); other characters (such as function keys) may return non-ASCII values. The method getkey reads a character, returning it as a string. Both getch and getkey are normally synchronous; they wait until the user presses a key. The method nodelay(flag) makes them synchronous if flag is true. In synchronous mode, if no keypress is available, the methods return getch and getkey which return -1 and “-1”, respectively. The method getstr reads a string from the user, handling things such as backspacing in the process. Note that getstr doesn’t play well with nodelay or noecho. In fact, getstr is quite primitive; see “Editing Text” for a more pleasant way to extract input from your users. Other keyboard-related functions You can throw a character onto the keyboard buffer by calling the function ungetch(character). The next call to getch will return character. You can only “un-get” one character at a time. A call to the function flushinp clears out the input buffers, throwing away any pending input that you haven’t processed yet. Fancy characters When keypad mode is active, control characters are interpreted for you by curses. Most of these characters have corresponding constants. For example, the following code fragment checks whether the user pressed F5: Char=Window.getch() if Char==curses.KEY_F5: # do stuff! Arrow keys (where available) are represented by KEY_UP, KEY_LEFT, KEY_RIGHT, and KEY_DOWN. See the curses documentation for a complete list of these constants. 4807-7 ch22.F 5/24/01 9:00 AM Page 423 Chapter 22 ✦ Using Curses In addition, the module curses.ascii provides constants and functions for cleanly handling ASCII characters. For example, curses.ascii.SP is equal to 32 (the ASCII value for a space); curses.ascii.BEL is 7 (the bell-character; Ctrl-G on most systems). Reading mouse input In order to detect mouse events, you must call the function mousemask(mask), where mask represents the mouse events you want to see. The return value has the form (available,old). Here, available is a mask of the events that will be reported (hopefully, the same as mask), and old is the old event mask. For example, the following code tries to watch for clicks and double-clicks of button 1 (the left button): (available,old) = curses.mousemask(curses.BUTTON1_PRESSED | curses.BUTTON2_PRESSED) if (available & curses.BUTTON1_PRESSED): CanSeeClick=1 else: CanSeeClick=0 You also need to turn keypad mode on; otherwise, mouse events are not visible. Mouse events are first signaled by a value of KEY_MOUSE passed to getch. At this point, you can examine the mouse input with a call to the function getmouse. The return value is a tuple of the form (id, x, y, z, state). Here, x and y are the coordinates of the mouse click, state is the event type, and id and z can be safely ignored. Table 22-2 describes all the available mouse events. A particular event (or event mask) may be a bitwise-OR or several of them. The pound sign (#) represents a number from 1 to 4. Table 22-2 Mouse Events Name Meaning BUTTON#_PRESSED Button # was pressed BUTTON#_RELEASED Button # was released BUTTON#_CLICKED Button # was clicked BUTTON#_DOUBLE_CLICKED Button # was double-clicked BUTTON#_TRIPLE_CLICKED Button # was triple-clicked BUTTON_SHIFT Button was Shift-clicked BUTTON_CTRL Button was Control-clicked BUTTON_ALT Button was Alt-clicked 423 4807-7 ch22.F 424 5/24/01 9:00 AM Page 424 Part IV ✦ User Interfaces and Multimedia The function ungetmouse(id,x,y,z,state), similar to ungetch, pushes a mouse event back onto the buffer. Example: yes, no, or maybe The program shown in Listing 22-4 provides three options, and lets the user choose one either by clicking it or by pressing a key. Listing 22-4: Deathray.py import curses import curses.textpad import whrandom class CursesButton: def __init__(self,Window,Y,X,Label,Hotkey=0): self.Y=Y self.X=X self.Label=Label self.Width=len(Label)+2 # label, plus lines on side self.Underline=Underline # Draw the button: curses.textpad.rectangle(Window,Y,X,Y+2,X+self.Width) # Draw the button label: Window.addstr(Y+1,X+1,Label,curses.A_BOLD) # Make the hotkey stand out: Window.addstr(Y+1,X+Underline+1,Label[Underline] ,curses.A_REVERSE) Window.refresh() def KeyPressed(self,Char): if (Char>255): return 0 # skip control-characters if chr(Char).upper()==self.Label[self.Underline]: return 1 else: return 0 def MouseClicked(self,MouseEvent): (id,x,y,z,event)=MouseEvent if (self.Y <= y <= self.Y+2) and \ (self.X <= x < self.X+self.Width): return 1 else: return 0 def ShowDialog(Window): curses.mousemask(curses.BUTTON1_PRESSED) Window.addstr(5,0,”Really, REALLY fire death ray?”) YesButton=CursesButton(Window,8,10,”Yes”) NoButton=CursesButton(Window,8,20,”No”) MaybeButton=CursesButton(Window,8,30,”Maybe”) Buttons=[YesButton,NoButton,MaybeButton] Window.nodelay(1) 4807-7 ch22.F 5/24/01 9:00 AM Page 425 Chapter 22 ✦ Using Curses Action=”” while 1: Key=Window.getch() if (Key==-1): continue for Button in Buttons: if Button.KeyPressed(Key): Action=Button.Label # Handle mouse-events: if (Key==curses.KEY_MOUSE): MouseEvent=curses.getmouse() for Button in Buttons: if Button.MouseClicked(MouseEvent): Action=Button.Label if Action!=””: break # Handle the actions if (Action==”Yes”): FireDeathRay(Window) if (Action==”No”): pass if (Action==”Maybe” and whrandom.random() > 0.5): FireDeathRay(Window) def FireDeathRay(Window): Window.clear() # Kra-ppoowwww! Frrrraapppp!! Window.bkgd(“X”) Window.nodelay(0) Window.getch() if __name__==”__main__”: curses.wrapper(ShowDialog) Managing Windows You can create a new, parentless window by calling the function newwin([lines,columns,]y,x). The new window’s top-left corner will be at (y, x). It will have height lines and width columns — by default, it will stretch to the bottom-right edge of the screen. Similarly, you can create a subwindow within an existing window by calling the method subwin([lines,columns,]y,x). The method mvwin(y,x) moves a window so that its upper-left corner is at (y, x). Pads A pad is similar to a window, except that it can be larger than the screen. It is a convenient way to make more data available than you can show all at once. It supports all the methods of a window, but has a different refresh method. 425 4807-7 ch22.F 426 5/24/01 9:00 AM Page 426 Part IV ✦ User Interfaces and Multimedia The function newpad(rows, columns) creates a pad of the given size. To draw the pad’s contents, call refresh(screenY,screenX,padTop,padLeft,padBottom, padRight). A region within the pad will be displayed, with its top-left corner at (screenY,screenX). The pad contents displayed lie in the rectangle with corners (padTop,padLeft) and (padBottom,padRight). Stacking windows The module curses.panel allows you to cleanly “stack” windows on top of each other so that only the visible portion of each window is displayed. The function new_panel(Window) returns a panel that wraps the specified window. You can change the panel’s stacking position by calling its methods bottom and top. You can hide and reveal panels by calling hide and show. After changing patterns, call the function update_panels to update the virtual screen, then curses.doupdate to repaint the screen. The function bottom_panel returns the bottom-most panel, and top_panel returns the topmost panel. Editing Text The module curses.textpad provides a class, Textbox, for convenient text editing. The constructor takes one argument: the window in which to place the Textbox. Once you have a Textbox, you can call edit([validator]) to let the user enter data, and call gather to retrieve the Textbox’s contents (as a string). The user can type text, scroll around the Textbox, and finish input by pressing Ctrl-G (or Enter, if the window has only one line). Because gather returns the entire window’s contents, you generally want to create a special window for use by only your Textbox. Table 22-3 describes the commands available within a Textbox. Table 22-3 Textbox Commands Keystroke Action Ctrl-A Go to left edge of window Ctrl-B Cursor left, wrapping to previous line if appropriate Ctrl-D Delete character under cursor Ctrl-E Go to right edge (stripspaces off) or end of line (stripspaces on) Ctrl-F Cursor right, wrapping to next line when appropriate 4807-7 ch22.F 5/24/01 9:00 AM Page 427 Chapter 22 ✦ Using Curses Keystroke Action Ctrl-G Terminate, returning the window contents Ctrl-H Delete character backward Ctrl-J Terminate if the window is one line; otherwise, insert newline Ctrl-K If line is blank, delete it; otherwise, clear to end of line Ctrl-L Refresh screen Ctrl-N Cursor down; move down one line Ctrl-O Insert a blank line at cursor location Ctrl-P Cursor up; move up one line You can, optionally, pass a callback function to edit([validator]). This function is called whenever the user presses a key, and the keystroke is passed as a parameter. The return value of validator, if any, is passed along to the Textbox. For instance, use the following if you want Esc to finish input in your Textbox: def Validator(Ch): if Ch==curses.ascii.ESC: return curses.ascii.BEL else: return Ch Using Color The function has_colors returns true if the terminal can display colors. The method start_color initializes color display; it should be called immediately after initscr. Numbering Colors come in two forms: color numbers and color pairs. Color numbers range from 0 to COLORS; they identify a color in the curses palette. Color pairs are valid attributes to pass to Window.addstr; they identify a foreground color number and a background color number. Therefore, each color pair is basically a pair of color numbers. Just to make things more interesting, color pairs are also numbered. Try not to confuse pair numbers with color numbers. (Go on, I dare you — try! Actually, the whole system starts to make sense after a while.) 427 4807-7 ch22.F 428 5/24/01 9:00 AM Page 428 Part IV ✦ User Interfaces and Multimedia The function color_pair(number) returns the color pair corresponding to the given pair number; the opposite function, pair_number(pair), returns the pair number of a color pair. Setting colors Color pair 0 is always white on black. You can change the colors of the other pairs by calling init_pair(pair_number, foreground, background). Here background and foreground are color numbers. The function pair_content(pair_number) returns the pair’s current colors as a tuple of the form (foreground,background). The constants COLOR_BLACK, COLOR_RED, COLOR_GREEN, COLOR_YELLOW, COLOR_BLUE, COLOR_MAGENTA, COLOR_CYAN and COLOR_WHITE are available to denote the corresponding color numbers. For example, the following code draws a simple German flag: # In the next line, 1 is the number of a # color-pair, while curses.WHITE is a # color-number: curses.init_pair(1,curses.WHITE,curses.BLACK) curses.init_pair(2,curses.WHITE,curses.RED) curses.init_pair(3,curses.WHITE,curses.YELLOW) Window.addstr(0,0,” “*10,curses.color_pair(1)) Window.addstr(1,0,” “*10,curses.color_pair(2)) Window.addstr(2,0,” “*10,curses.color_pair(3)) Tweaking the colors Defining colors is not possible on most terminals. The function can_change_color returns true on those terminals where it is. A call to init_color(number, red, green, blue) redefines color number to have the specified intensities of red, green, and blue. Intensity ranges from 0 to 1,000. The function color_content(number) returns the current definition of color number as a tuple of the form (red, green, blue). Example: A Simple Maze Game I have a soft spot in my heart for curses because I have spent more time than I care to admit playing ASCII-based games such as Angband and Nethack. The program shown in Listing 22-5 is far simpler, but it does use several curses features. It uses a pad to hold a large maze, which the user can move around in. 4807-7 ch22.F 5/24/01 9:00 AM Page 429 Chapter 22 ✦ Using Curses Listing 22-5: Maze.py import curses import curses.ascii import whrandom # Possible contents of maze-squares: MAZE_WALL=”X” MAZE_ENTRANCE=”*” MAZE_HALLWAY=”.” # Attributes for displaying maze squares: MAZE_ATTRIBUTE={MAZE_WALL:curses.A_NORMAL, MAZE_ENTRANCE:curses.A_BOLD, MAZE_HALLWAY:curses.A_DIM,} # Simple class representing a compass direction: class Direction: def __init__(self,Name,XDelta,YDelta): self.Name=Name self.XDelta=XDelta self.YDelta=YDelta self.Marker=Name[0] def SetOpposite(self,Dir): self.Opposite=Dir Dir.Opposite=self NORTH=Direction(“North”,0,-1) SOUTH=Direction(“South”,0,1) EAST=Direction(“East”,1,0) WEST=Direction(“West”,-1,0) NORTH.SetOpposite(SOUTH) EAST.SetOpposite(WEST) VALID_DIRECTIONS=[NORTH,SOUTH,EAST,WEST] # Maze creation uses direction “markers” to indicate how we got # to a square, so that we can (later) backtrack: MARKED_DIRECTIONS={NORTH.Marker:NORTH,SOUTH.Marker:SOUTH, EAST.Marker:EAST,WEST.Marker:WEST} # Map keystrokes to compass directions: KEY_DIRECTIONS={curses.KEY_UP:NORTH,curses.KEY_DOWN:SOUTH, curses.KEY_LEFT:WEST,curses.KEY_RIGHT:EAST} class Maze: def __init__(self,Size=11): # Maze size must be an odd number: if (Size%2==0): Size+=1 self.Size=Size self.Pad=curses.newpad(self.Size+1,self.Size+1) self.FillWithWalls() def FillWithWalls(self): for Y in range(0,self.Size): self.Pad.addstr(Y,0,MAZE_WALL*self.Size,MAZE_ATTRIBUTE[MAZE_WALL]) def Set(self,X,Y,Char): self.Pad.addstr(Y,X,Char,MAZE_ATTRIBUTE.get(Char,curses.A_NORMAL)) Continued 429 4807-7 ch22.F 430 5/24/01 9:00 AM Page 430 Part IV ✦ User Interfaces and Multimedia Listing 22-5 (continued) def Get(self,X,Y): return self.Pad.instr(Y,X,1) def BuildRandomMaze(self): self.FillWithWalls() CurrentX=1 CurrentY=1 self.Set(CurrentX,CurrentY,MAZE_ENTRANCE) while (1): Direction=self.GetValidDirection(CurrentX,CurrentY) if (Direction!=None): # Take one step forward self.Set(CurrentX+Direction.XDelta, CurrentY+Direction.YDelta,MAZE_HALLWAY) CurrentX+=Direction.XDelta*2 CurrentY+=Direction.YDelta*2 self.Set(CurrentX,CurrentY,Direction.Marker) else: # Backtrack one step BackDirectionMarker=self.Get(CurrentX,CurrentY) BackDirection=MARKED_DIRECTIONS[BackDirectionMarker].Opposite CurrentX+=BackDirection.XDelta*2 CurrentY+=BackDirection.YDelta*2 # If we backtracked to the entrance, the maze is done! if self.Get(CurrentX,CurrentY)==MAZE_ENTRANCE: break # Fix up the maze: for X in range(0,self.Size): for Y in range(0,self.Size): if self.Get(X,Y) not in [MAZE_HALLWAY,MAZE_WALL, MAZE_ENTRANCE]: self.Set(X,Y,MAZE_HALLWAY) def GetValidDirection(self,X,Y): DirectionIndex=whrandom.randint(0,len(VALID_DIRECTIONS)-1) FirstIndex=DirectionIndex while (1): Direction=VALID_DIRECTIONS[DirectionIndex] NextSquare=(X+Direction.XDelta*2,Y+Direction.YDelta*2) if ((0 < NextSquare[0] < self.Size) and (0 < NextSquare[1] < self.Size) and self.Get(NextSquare[0],NextSquare[1])==MAZE_WALL): return Direction DirectionIndex+=1 if (DirectionIndex>=len(VALID_DIRECTIONS)): DirectionIndex=0 if (DirectionIndex==FirstIndex): return None def ShowSelf(self,ScreenLeft,ScreenTop,PlayerX,PlayerY,Radius): Top=PlayerY-Radius Bottom=PlayerY+Radius Left=PlayerX-Radius 4807-7 ch22.F 5/24/01 9:00 AM Page 431 Chapter 22 ✦ Using Curses Right=PlayerX+Radius ScreenRight=ScreenLeft+Radius*2+1 ScreenBottom=ScreenTop+Radius*2+1 if (Top<0): ScreenTop -= Top Top=0 if (Left<0): ScreenLeft -= Left Left=0 if (Right>self.Size-1): ScreenRight-=(self.Size-1-Right) Right=self.Size-1 if (Bottom>self.Size-1): ScreenBottom-=(self.Size-1-Bottom) Bottom=self.Size-1 self.Pad.refresh(Top,Left,ScreenTop,ScreenLeft,ScreenBottom,ScreenRight) def Main(Window): # Set up colors: curses.init_pair(1,curses.COLOR_GREEN,curses.COLOR_BLACK) curses.init_pair(2,curses.COLOR_BLUE,curses.COLOR_BLACK) curses.init_pair(3,curses.COLOR_RED,curses.COLOR_BLACK) MAZE_ATTRIBUTE[MAZE_HALLWAY] |= curses.color_pair(1) MAZE_ATTRIBUTE[MAZE_ENTRANCE] |= curses.color_pair(2) MAZE_ATTRIBUTE[MAZE_WALL] |= curses.color_pair(3) curses.curs_set(0) # invisible cursor MyMaze=Maze(20) MyMaze.BuildRandomMaze() PlayerX=19 PlayerY=19 LightRadius=3 MazeWindow=curses.newwin(10,10,10+LightRadius*2+1,10+LightRadius*2+1) while 1: MazeWindow.erase() MyMaze.ShowSelf(10,10,PlayerX,PlayerY,LightRadius) Window.addch(10+LightRadius,10+LightRadius,”@”, curses.color_pair(2) & curses.A_STANDOUT) Window.refresh() Key=Window.getch() if (Key==ord(‘q’) or Key==curses.ascii.ESC): break Direction=KEY_DIRECTIONS.get(Key,None) if (Direction): TargetSquare=MyMaze.Get(PlayerX+Direction.XDelta, PlayerY+Direction.YDelta) if TargetSquare==MAZE_ENTRANCE: MazeFinished(Window) break if TargetSquare==MAZE_HALLWAY: PlayerX += Direction.XDelta PlayerY += Direction.YDelta Continued 431 4807-7 ch22.F 432 5/24/01 9:00 AM Page 432 Part IV ✦ User Interfaces and Multimedia Listing 22-5 (continued) def MazeFinished(Window): Window.clear() Window.addstr(5,5,”CONGRATULATION!”,curses.color_pair(2)) Window.addstr(6,5,”A WINNER IS YOU!”,curses.color_pair(3)) Window.getch() pass if (__name__==”__main__”): curses.wrapper(Main) print “Bye!” Summary The curses library is an easy, portable way to create a text-mode user interface. In this chapter, you used curses to: ✦ Display and read text onscreen. ✦ Handle mouse and keyboard input. ✦ Use Textboxes for easy input. ✦ Draw colorful text. The next chapter demonstrates various ways to create a command interpreter in Python, including the spiffy graphics language Lepto. ✦ ✦ ✦ 4807-7 ch23.F 5/24/01 9:00 AM Page 433 23 CHAPTER Building Simple Command Interpreters W hen someone says “user interface,” I usually think of a GUI with nice buttons and menus, but sometimes a more appropriate and powerful interface uses a custom minilanguage in which your users write small programs or scripts. This chapter introduces Python’s support for such a user interface and walks you through the process of creating a graphical plotting application that is driven by a small, custom scripting language called Lepto. ✦ ✦ ✦ ✦ In This Chapter Beginning with the end in mind Understanding the Lepto language Creating a Lepto Lexical analyzer Adding interactivemode features Executing Lepto commands Beginning with the End in Mind The Python libraries covered in this chapter are the shlex and cmd modules. The nature of these two modules makes it difficult to cover each feature in isolation, so each section of this chapter builds a portion of a single application. Once you’ve seen the modules in that larger context, rereading the explanations of the modules’ features will make more sense. The application that you will build is a simple plotter (sort of like the turtle graphics you find in languages like LOGO). It is controlled by user-provided scripts, and the scripting language provides basic movement commands and support for creating subroutines (procedures). If you imagine a spectrum on which you position programming languages according to their power and flexibility, the high end would contain Python, and the low end would contain this chapter’s language. Because one of the world’s largest snakes is a type of Python (around 10 meters long), I named this new language Lepto, short for Leptotyphlopidae, a type of blind snake that ranks as one of the world’s smallest, around 13 centimeters. ✦ ✦ ✦ ✦ 4807-7 ch23.F 434 5/24/01 9:00 AM Page 434 Part IV ✦ User Interfaces and Multimedia The following is a sample Lepto program, and Figure 23-1 shows the result of running it through the finished application from this chapter: Listing 23-1: leptogui.py – A sample Lepto program C:\temp>leptogui.py Welcome to Lepto! Enter a command or type ‘help’ : color blue : scale 30 : sub kochedge # A subroutine to draw an edge .. f 1 l 60 # f = forward .. f 1 r 120 # l and r = turn .. f 1 l 60 .. f1 .. r 120 .. end : repeat 3 kochedge : scale 0.5 : repeat 3 kochedge : scale 0.5 : repeat 3 kochedge : scale 0.5 : repeat 3 kochedge Figure 23-1: The result of running a simple Lepto program 4807-7 ch23.F 5/24/01 9:00 AM Page 435 Chapter 23 ✦ Building Simple Command Interpreters Understanding the Lepto Language Lepto programs are very simple; each line of a Lepto script contains one or more complete statements. Blank lines and other whitespace are ignored, and comments will be like Python’s and consist of a pound symbol (#) and everything after it on the same line. Table 23-1 explains the statements Lepto supports. Table 23-1 Valid Lepto Statements Statement Description f amnt Move forward (in the current direction) amnt units b amnt Move backward (away from the current direction) amnt units l amnt Turn left amnt degrees r amnt Turn right amnt degrees scale amnt Multiply the current scale by amnt. Initially the scale is 1, meaning one pixel for each unit of movement. color name Change the current drawing color to name. A color name is any valid Tkinter color. push arg Save a state attribute to its own stack for later retrieval. arg can be one of color, direction, scale, or position. pop arg Restore a previously saved state attribute. arg is one of color, direction, scale, or position. No effect results if the stack is empty. reset arg Restore a state attribute to its original value. arg can be one of direction, color, screen, scale, position, or all. include file Read and execute the contents of the file named file as if the contents had been entered from the console. sub name Begin the creation of a new subroutine called name. Overwrites any previous subroutine of the same name. end Finish creating a new subroutine call name Execute the subroutine called name repeat count sub Repeatedly execute the subroutine called sub count times The features of this language are obviously limited so that the example isn’t too cumbersome, but it has enough functionality to be interesting. 435 4807-7 ch23.F 436 5/24/01 9:00 AM Page 436 Part IV ✦ User Interfaces and Multimedia Creating a Lepto Lexical Analyzer Users will create Lepto programs using a text editor or by entering them in via an interactive console. Either way, their input will be plain text, so the first step toward a finished application is parsing the text input and spitting out Lepto commands in some internal format that the rest of the program can understand. During this conversion, the parser will also verify that the Lepto commands are valid according to the simple grammar explained in the previous section. The shlex module Python’s shlex module provides basic lexical analysis for simple shell-like languages. It defines the shlex class, which you can use as is or through your own subclass. You create a shlex object by calling shlex([instream[, infile]]), where instream is an open filelike object and infile is the file’s name (printed with error messages). If you provide neither, then shlex uses stdin. shlex breaks the input down into individual words, or tokens. A shlex object has several members, which you can modify to affect how it interprets the input stream. The commenters member is a string of all valid comment characters (defaulting to ‘#’), and quotes is a string with all valid quote characters (defaulting to single and double quotes). If a comment character is in the middle of a token (with no surrounding whitespace), it counts as a single token that just so happens to contain the comment character. The whitespace member is a string of token separators (by default, whitespace is any combination of tabs, spaces, carriage returns, and linefeeds). wordchars defaults to alphanumeric characters (letters and numbers) and the underscore; it represents all valid token characters. Any character not in whitespace, wordchars, quotes, or commenters is returned as a single-character token. source is a string holding the keyword shlex uses as the “import” or “include” equivalent found in Python or C, telling shlex to read and parse the contents of a file. Setting it to a value of beable, for example, means a user can use the following command to include the contents of the file foofoo.txt: beable “foofoo.txt” infile is the name of the current file (the original input file name, or the name of the file currently being included), and instream has the filelike object from which data is being read. The lineno member is the current source line number. For debugging purposes, you can set the debug member to 1 or more to have shlex generate more verbose output. With your shlex object configured the way you want, all you need to do is repeatedly call its get_token() method to retrieve the next token from the stream. When all the input has been read, get_token returns an empty string. push_token(str) pushes str onto the token stack (so that the next call to get_token returns str). 4807-7 ch23.F 5/24/01 9:00 AM Page 437 Chapter 23 ✦ Building Simple Command Interpreters When a user includes a file’s contents (using the keyword stored in source), the sourcehook(path) method is called to locate and open the file called path. You can override this method to implement your own file location algorithm; sourcehook returns a 2-tuple (file name, open file object). If you need to print out an error message, prefix your message with the string returned from the object’s error_leader([file[, line]]) method. Unless you indicate otherwise, it uses the current file name and line number to return a message header string that is friendly to editors such as Emacs. For example: >>> print s.error_leader()+’Expected a number’ “foofoo.txt”, line 17: Expected a number Putting shlex to work The parser in Listing 23-2 understands the simple Lepto language as described earlier in this chapter. At the highest level, it repeatedly calls shlex.get_token to get a command and then calls a corresponding parse_<command> method to read and verify that command’s arguments. Each finished command is stored in a LeptoCmd object (a simple container), all of which are buffered and eventually returned as a list of commands. Listing 23-2: leptoparser.py – Coverts tokens to LeptoCmd objects import shlex,sys class LeptoCmd: ‘Simple container class’ def __init__(self,cmd,**kwargs): self.cmd = cmd self.__dict__.update(kwargs) def __repr__(self): s = ‘LeptoCmd %s(‘ % self.cmd for item in self.__dict__.items(): if item[0] != ‘cmd’: s += ‘ %s=%s’ % item return s + ‘ )’ class LeptoParser: def __init__(self,stopOnError=1): self.stopOnError = stopOnError def err(self,msg,dest=sys.stderr): dest.write(self.lexer.error_leader()+msg+’\n’) Continued 437 4807-7 ch23.F 438 5/24/01 9:00 AM Page 438 Part IV ✦ User Interfaces and Multimedia Listing 23-2 (continued) def next_token(self): ‘Returns the next token or None on error’ tok = self.lexer.get_token() if tok == ‘’: self.err(‘Unexpected end of file’) return tok def next_number(self,func=float): ‘Returns the next token as a number’ tok = self.next_token() if tok: try: tok = func(tok) except ValueError: return self.err(‘Expected a number, not ‘+tok) return tok def parse_reset(self): tok = self.next_token() if tok: if not tok in [‘all’,’direction’,’color’,\ ‘screen’,’scale’,’position’,\ ‘stacks’]: return self.err(‘Invalid reset argument’) return LeptoCmd(‘reset’,arg=tok) def parse_push(self): tok = self.next_token() if tok: if not tok in [‘color’,’direction’,\ ‘scale’,’position’]: return self.err(‘Invalid push argument’) return LeptoCmd(‘push’,arg=tok) def parse_pop(self): tok = self.next_token() if tok: if not tok in [‘color’,’direction’,\ ‘scale’,’position’]: return self.err(‘Invalid push argument’) return LeptoCmd(‘pop’,arg=tok) def amntcmd(self,cmd): ‘Util for commands with a single numerical arg’ num = self.next_number() if num: return LeptoCmd(cmd,amnt=num) # These are all nearly identical def parse_f(self): return self.amntcmd(‘f’) def parse_b(self): return self.amntcmd(‘b’) def parse_l(self): return self.amntcmd(‘l’) 4807-7 ch23.F 5/24/01 9:00 AM Page 439 Chapter 23 ✦ Building Simple Command Interpreters def parse_r(self): return self.amntcmd(‘r’) def parse_scale(self): return self.amntcmd(‘scale’) def namecmd(self,cmd): ‘Util for commands with a single string arg’ tok = self.next_token() if tok: return LeptoCmd(cmd,name=tok) # More nearly identical stuff def parse_color(self): return self.namecmd(‘color’) def parse_sub(self): return self.namecmd(‘sub’) def parse_call(self): return self.namecmd(‘call’) def parse_end(self): return LeptoCmd(‘end’) def parse_repeat(self): num = self.next_number() if num: n = self.next_token() if n: return LeptoCmd(‘repeat’,count=num,name=n) def parse(self, stream=None, name=None): ‘Returns a list of LeptoCmd objects’ lexer = shlex.shlex(stream,name) lexer.source = ‘include’ lexer.wordchars += ‘.,-’ # For numbers self.lexer = lexer cmds = while 1: tok = lexer.get_token() if tok == ‘’: # End of the file break # See if there’s a parser for this token parser = ‘parse_’+tok if not hasattr(self,parser): self.err(‘Unknown command: ‘+tok) if self.stopOnError: break else: continue # Call the parser to convert to a LeptoCmd object cmd = getattr(self,parser)() if cmd is None: if self.stopOnError: break else: continue cmds.append(cmd) return cmds 439 4807-7 ch23.F 440 5/24/01 9:00 AM Page 440 Part IV ✦ User Interfaces and Multimedia Basically, you create a LeptoParser object, pass it a stream, and it returns to you a list of LeptoCmd objects, checking for errors along the way. Later sections will make use of the LeptoParser class, but you can already verify that it works correctly: >>> import leptoparser >>> p = leptoparser.LeptoParser() >>> p.parse() color red # You enter this f 10 l 20 f 10 l 5 f 5 # You enter this ^Z # Hit Ctrl-Z (Win) or Ctrl-D (Unix) [LeptoCmd color( name=red ), LeptoCmd f( amnt=10.0 ), LeptoCmd l( amnt=20.0 ), LeptoCmd f( amnt=10.0 ), LeptoCmd l( amnt=5.0 ), LeptoCmd f( amnt=5.0 )] Adding Interactive-Mode Features The next step toward a finished application is the addition of a “shell” similar to when you use Python in interactive mode. The shell passes the commands through to the parser, and also provides online help. Using the cmd module The cmd module defines the Cmd class that provides some scaffolding for building an interactive, command-line interpreter. Because it is just scaffolding, you normally don’t use it directly, but instead create a subclass. If the readline module is present, cmd automatically uses its editing and history features. CrossReference The readline module is an optional UNIX module, covered in Chapter 38. The Cmd constructor takes no arguments, but once you have a Cmd object (or an object of your subclass), you can use the following members to customize it. The prompt member is the input prompt displayed while the user enters a command. identchars is a string containing all acceptable characters in a command prefix (defaulting to letters, numbers, and underscores). By default the prompt is ‘(Cmd) ‘. For each line of input from a user, Cmd considers the first token to be a command prefix, and it uses that prefix to dispatch the input to a handler method. For example, if the first word on the line of input is the string reverse, then Cmd sends the remainder of the line to its do_reverse(line) method, if present. If no handler is present, the line is sent to the default(line) method. 4807-7 ch23.F 5/24/01 9:00 AM Page 441 Chapter 23 ✦ Building Simple Command Interpreters Cmd comes with a few special commands. If a user enters help reverse or just ? reverse, a built-in do_help method calls help_reverse(), if present, which you can implement to print online help (just print it to stdout using one or more print statements). A command prefix of just an exclamation point sends the remaining arguments to a do_shell(line) method if it exists. If the input is just a blank line, the emptyline() method is called, which by default repeats the previous input (by calling self.onecmd(self.lastcmd)). Finally, when the end of user input is reached, the do_EOF() method is called. onecmd(line) takes an entire line of input and processes it as if it had been entered by the user. The cmdloop([intro]) method makes Cmd repeatedly prompt the user for input and then dispatches it. intro is a message to display before entering the loop; if omitted, Cmd displays the message in self.intro, which is empty by default. You can implement the preloop() and postloop() methods to do work immediately before and after Cmd goes into its loop (i.e., they will both be called once per call to the cmdloop method). For each line of input, Cmd performs a series of calls like the following: stop line line stop stop = = = = = None raw_input(self.prompt) self.precmd(line) self.onecmd(line) self.postcmd(stop, line) It receives user input, sends it to precmd (where you can modify it if you want), and then passes it off to onecmd, where the correct do_<command> method is called. If, at the end of the loop, stop has a value besides None, cmdloop calls postloop and then returns. If a user enters help with no other argument, do_help displays a sort of table of contents of available help topics: print print print print print print print print print self.doc_header self.ruler * len(self.doc_header) <all do_ methods that have a help_ method> self.misc_header self.ruler * len(self.misc_header) <all help_ methods that don’t have a do_ method> self.undoc_header self.ruler * self.undoc_header <all do_ methods without a help_ method> 441 4807-7 ch23.F 442 5/24/01 9:00 AM Page 442 Part IV ✦ User Interfaces and Multimedia Sample output might look something like the following: Documented commands (type help <topic>): ======================================== go stop add subtract delete Miscellaneous help topics: ========================== overview rules Undocumented commands: ====================== quit Subclassing cmd.Cmd Listing 23-3 contains the next piece of the Lepto application, and it’s a good way to see a Cmd object in action; it defines LeptoCon, a Cmd subclass that wraps the Lepto parser so that users have online help and readline support, if present. Listing 23-3: leptocon.py — Lepto interactive console import cmd, leptoparser, cStringIO def defaultHandler(cmds): ‘Simple handler for testing’ for cmd in cmds: print cmd class LeptoCon(cmd.Cmd): normalPrompt = ‘: ‘ subPrompt = ‘.. ‘ def __init__(self,handler=defaultHandler): cmd.Cmd.__init__(self) self.timeToQuit = 0 self.prompt = self.normalPrompt self.parser = leptoparser.LeptoParser() self.doc_header = “Type ‘help <topic>’ for info on:” self.intro = ‘Welcome to Lepto!\n’\ “Enter a command or type ‘help’” self.misc_header = ‘’ self.undoc_header = ‘’ self.handler = handler def do_sub(self,line): ‘Change the prompt for subroutines’ self.prompt = self.subPrompt self.default(‘sub ‘+line) # Now process normally 4807-7 ch23.F 5/24/01 9:00 AM Page 443 Chapter 23 ✦ Building Simple Command Interpreters def do_end(self,line): ‘Change the prompt back after subroutines’ self.prompt = self.normalPrompt self.default(‘end ‘+line) # Now process normally def default(self,line): ‘Called on normal commands’ sio = cStringIO.StringIO(line) cmds = self.parser.parse(sio,’Console’) self.handler(cmds) def do_quit(self,line): self.timeToQuit = 1 def postcmd(self,stop,line): if self.timeToQuit: return 1 return stop # Now come all the online documentation functions def help_help(self): print ‘I need help!’ def help_quit(self): print ‘Duh.’ def help_reset(self): print ‘reset <all | direction | color | ‘\ ‘screen | scale | position | stacks>’ print ‘Reverts to default settings’ def help_color(self): print ‘color <name | None>’ print ‘Changes current color to <name> or no color’\ ‘ for invisible movement’ def help_push(self): print ‘push <color | direction | scale | position>’ print ‘Saves an attribute to its own stack’ def help_pop(self): print ‘pop <color | direction | scale | position>’ print ‘Retrieves a previously pushed attribute’ def help_f(self): print ‘f <amnt>’ print ‘Moves forward in the current direction’ def help_b(self): print ‘b <amnt>’ print ‘Moves opposite of the current direction’ def help_l(self): print ‘l <amnt>’ print ‘Turns left the specified number of degrees’ Continued 443 4807-7 ch23.F 444 5/24/01 9:00 AM Page 444 Part IV ✦ User Interfaces and Multimedia Listing 23-3 (continued) def help_r(self): print ‘r <amnt>’ print ‘Turns right the specified number of degrees’ def help_scale(self): print ‘scale <amnt>’ print ‘Multiplies the current scaling factor by amnt’ def help_sub(self): print ‘sub <name>’ print ‘Creates a new subroutine called name’ print ‘Be sure to terminate it using the end command’ def help_end(self): print ‘end\nEnds a subroutine definition’ def help_call(self): print ‘call <name>\nCalls a subroutine’ def help_include(self): print ‘include “file”\nExecutes the contents of a file’ def help_repeat(self): print ‘repeat <count> <name>’ print ‘Calls a subroutine several times’ if __name__ == ‘__main__’: c = LeptoCon() c.cmdloop() Because the parser handles entire commands, most commands are routed to the default method, which passes the whole line on to the parser. Once again, this is part of a still larger program, but you can test this portion of it to make sure everything’s working. Here’s an example session from a Windows command line (text in bold is what I typed): C:\temp>python leptocon.py Welcome to Lepto! Enter a command or type ‘help’ : help Type ‘help <topic>’ for info on: ================================ help quit sub include b pop l scale end repeat call r color reset push f 4807-7 ch23.F 5/24/01 9:00 AM Page 445 Chapter 23 ✦ Building Simple Command Interpreters : help call call <name> Calls a subroutine : color red LeptoCmd color( name=red ) : f 10 r 20 f 10 LeptoCmd f( amnt=10.0 ) LeptoCmd r( amnt=20.0 ) LeptoCmd f( amnt=10.0 ) : quit C:\temp> Notice that you can enter more than one command per line as long as the entire command is on that line. The default command handler does nothing but print the commands to stdout, but it at least lets you see what’s happening. It may seem like overkill to use both shlex and cmd because there is some overlap in what they do (I could have just implemented methods such as do_color, do_reset, and so on, for example). But as you’ve seen, using both made it easy to test these first two parts independently, which could be important for languages with more complex grammars. It also makes it easy to later re-use LeptoParser for handling input directly from a file. Furthermore, it enables you to easily add interactive-mode features (such as online help and using a different prompt when the user is defining a subroutine) without cluttering the parsing code. Executing Lepto Commands Now that you have a Lepto parser and a user-friendly interface, all you need is something to act on those commands. The code in Listing 23-4 builds upon the previous two sections and creates a graphical display showing the results of the Lepto scripts (the display is nothing more than a Tkinter window with a single canvas widget). Listing 23-4: leptgui.py – Plots Lepto commands from Tkinter import * import leptocon, threading, math deg2rad = math.pi * 2.0 / 360.0 class LeptoGUI: def __init__(self,canvas): self.canvas = canvas self.subs = {} self.newSub = None self.firstCmd = 1 Continued 445 4807-7 ch23.F 446 5/24/01 9:00 AM Page 446 Part IV ✦ User Interfaces and Multimedia Listing 23-4 (continued) def do_reset_direction(self): self.direction = 0 def do_reset_color(self): self.color = ‘black’ def do_reset_scale(self): self.scale = 1.0 def do_reset_position(self): # Move to center of canvas x = self.canvas.winfo_width() / 2 y = self.canvas.winfo_height() / 2 self.position = (x,y) def do_reset_screen(self): ids = self.canvas.find_all() self.canvas.delete(*ids) def do_reset_stacks(self): self.direction_stk = self.color_stk = self.scale_stk = self.position_stk = def do_reset_all(self): self.do_reset_direction() self.do_reset_color() self.do_reset_scale() self.do_reset_position() self.do_reset_screen() self.do_reset_stacks() def do_reset(self,cmd): ‘Reset color, position, etc’ getattr(self,’do_reset_’+cmd.arg)() def do_color(self,cmd): ‘Change color’ self.color = None if cmd.name.lower() != ‘none’: self.color = cmd.name def do_push(self,cmd): ‘Push a color, position, etc’ arg = cmd.arg getattr(self,arg+’_stk’).append(getattr(self,arg)) def do_pop(self,cmd): ‘Pop a color, position, etc’ stk = getattr(self,cmd.arg+’_stk’) if len(stk): setattr(self,cmd.arg,stk.pop()) 4807-7 ch23.F 5/24/01 9:00 AM Page 447 Chapter 23 ✦ Building Simple Command Interpreters def do_f(self,cmd): ‘Move forward’ x,y = self.position dir = self.direction * deg2rad amnt = self.scale * cmd.amnt nx = x + amnt * math.cos(dir) ny = y - amnt * math.sin(dir) if self.color: self.canvas.create_line(x, y, nx, ny, width=1,\ fill=self.color) self.position = (nx,ny) def do_b(self,cmd): ‘Move backward’ self.direction = (self.direction + 180) % 360 self.do_f(cmd) self.direction = (self.direction - 180) % 360 def do_l(self,cmd): ‘Turn left’ self.direction = (self.direction + cmd.amnt) % 360 def do_r(self,cmd): ‘Turn right’ self.direction = (self.direction - cmd.amnt) % 360 def do_scale(self,cmd): ‘Change scale’ self.scale *= cmd.amnt def do_sub(self,cmd): ‘Create a new subroutine’ if self.newSub: print “Can’t create nested subroutines” return self.newSub = cmd.name self.subs[cmd.name] = def do_end(self,cmd): ‘Finish creating a subroutine’ if not self.newSub: print ‘No subroutine to end’ return self.newSub = None def do_call(self,cmd): ‘Invoke a subroutine’ sub = cmd.name if self.subs.has_key(sub): self.cmdHandler(self.subs[sub]) else: print ‘Unknown subroutine’,sub Continued 447 4807-7 ch23.F 448 5/24/01 9:00 AM Page 448 Part IV ✦ User Interfaces and Multimedia Listing 23-4 (continued) def do_repeat(self,cmd): ‘repeat - Just do_call <count> times’ c = leptocon.leptoparser.LeptoCmd(‘call’,name=cmd.name) for i in range(cmd.count): self.do_call(c) def cmdHandler(self,cmds): ‘Called for each command object’ if self.firstCmd: # Widget info (w,h) won’t be ready in the # constructor, but it will be ready by now self.firstCmd = 0 self.do_reset_all() for cmd in cmds: if self.newSub and cmd.cmd != ‘end’: self.subs[self.newSub].append(cmd) else: getattr(self,’do_’+cmd.cmd)(cmd) if __name__ == ‘__main__’: # Create a Tk window with a canvas root = Tk() root.title(‘LeptoGUI’) canvas = Canvas(root,bg=’White’) canvas.pack() gui = LeptoGUI(canvas) # Let Tkinter run in the background threading.Thread(target=root.mainloop).start() # Repeatedly get commands and process them c = leptocon.LeptoCon(gui.cmdHandler) c.cmdloop() root.quit() leptogui.py uses the usual trick of dispatching commands by taking a command name (such as scale), converting it to a method name (do_scale), and then invoking it. Because so much work was taken care of by the parser, the final pieces of the graphical application ended up being quite simple and straightforward. Launch leptogui.py to give Lepto a try. Following is a sample session; the resulting output is shown in Figure 23-2. 4807-7 ch23.F 5/24/01 9:00 AM Page 449 Chapter 23 ✦ Building Simple Command Interpreters C:\temp>leptogui.py Welcome to Lepto! Enter a command or type ‘help’ : color blue f 40 r 90 : color green f 40 r 90 : color red f 40 r 90 : color brown f 40 r 90 : l 90 color none f 20 # Please step away from the box : color black : sub rayrot # Draws a ray and then rotates left .. push position .. f 100 .. pop position .. l5 .. end : repeat 10 rayrot Figure 23-2: Sample output from a program written in the custom language called Lepto You can store useful subroutines in a separate file and import them using the include command. For example, save the Lepto code that follows in Listing 23-5 to a file called shapes.lep, and try the following (the output is shown in Figure 23-3): C:\temp>leptogui.py Welcome to Lepto! Enter a command or type ‘help’ : include “shapes.lep” : color blue : call circle : color black : scale 10 : call tri 449 4807-7 ch23.F 450 5/24/01 9:00 AM Page 450 Part IV ✦ User Interfaces and Multimedia : r 180 : color green : call box : sub cirrot # draw a circle and rotate a little .. push color push position .. color none .. f 50 .. pop color .. call circle .. pop position .. r 20 .. end : reset scale reset position reset color : repeat 18 cirrot Listing 23-5: shapes.lep – Sample Lepto include file sub sub sub sub circedge f 10 r 15 end circle repeat 24 circedge end box f 10 r 90 f 10 r 90 f 10 r 90 f 10 r 90 end tri f 10 r 120 f 10 r 120 f 10 r 120 end Figure 23-3: Lepto program using subroutines stored in a separate file Lepto is a simple, yet realistic, example of how you can benefit from the shlex and cmd modules. A good exercise to try now would be to expand the grammar of Lepto to make it more powerful. For example, you could add support for variables and expressions (let Python do the work of evaluation via the eval function), or you could let the repeat statement accept a sequence of commands instead of forcing users to define a subroutine first. 4807-7 ch23.F 5/24/01 9:00 AM Page 451 Chapter 23 ✦ Building Simple Command Interpreters Summary A scripting interface to a program gives your users powerful tools to work with. Python’s shlex module makes lexical analysis a lot less tedious, and cmd gives you a base upon which you can build a flexible command-line interface. In this chapter, you: ✦ Created a parser for a simple scripting language. ✦ Wrapped the parser in a command-line interface complete with built-in online help. ✦ Built an interpreter for the parser output that plots drawings graphically. The next chapter covers Python’s support for processing and playing sound files in various formats. ✦ ✦ ✦ 451 4807-7 ch23.F 5/24/01 9:00 AM Page 452 4807-7 ch24.F 5/24/01 9:00 AM Page 453 24 CHAPTER Playing Sound S ound is stored in a bewildering range of formats. Fortunately, Python’s standard libraries can read, write, and convert a wide range of audio files. You can also play back sounds on a variety of platforms. ✦ ✦ ✦ ✦ In This Chapter Sound file basics Playing sounds Sound File Basics Sound is basically vibration in the air. The louder the sound, the more forceful the vibration. The higher the sound, the faster the vibration. To store sound digitally, a microphone or other recorder measures (or samples) the analog sound waveform many times per second. Each sample takes the form of a number, and this number measures the amplitude of the sound waves at an instant in time. A speaker can later translate digitized sound (this long list of integers) back into sound waves. There are many, many ways to digitize and store sound. They can differ in several ways: ✦ Sample rate — How many times per second the amplitude of the sound waves is measured. A common sample rate is 44100 Hz (samples per second), the rate used on audio compact discs. ✦ Sample encoding — The simplest (and most common) is linear encoding, where each sample is a linear measurement of amplitude. Other encoding types include u-LAW, in which measurement is performed on a logarithmic scale. ✦ Sample width — A sample can be an 8-bit, 16-bit, or 32bit integer. ✦ Channels — Sound can be recorded with one, two, or more channels. This boils down to the storage of one or more audio streams together in one file. The corresponding samples from each channel are normally stored together in one frame. Examining audio files Reading and writing audio files Handling raw audio data ✦ ✦ ✦ ✦ 4807-7 ch24.F 454 5/24/01 9:00 AM Page 454 Part IV ✦ User Interfaces and Multimedia All sound formats make some trade-offs between sound quality (how much information is lost in digitizing the sound) and file size (the better the sound quality, the more data needs to be stored). For example, one second of sound could be stored in 8-bit mono at a sample rate of 22050; the total space used would be 22050 bytes. Storing the same sound in 16-bit stereo at a sampling rate of 44100 would require 44100 frames at 4 bytes per frame, for a total of 176400 bytes (8 times as much space). Playing Sounds Because playing sound is tied to the operating system (OS), the libraries for playing sound are also OS-specific. Playing sound on Windows The module winsound plays sound on a Windows system. The function Beep(frequency,duration) uses the computer’s internal speaker to play a sound at pitch frequency for duration milliseconds. The frequency can range from 37 to 32767. If Beep can’t play the sound, it raises a RuntimeError. For example, the following code plays a tinny-sounding major scale, starting from middle C. Each note lasts half a second: ScalePitches=[262,294,330,349,392,440,494,523] for Pitch in ScalePitches: winsound.Beep(Pitch,500) The function PlaySound(sound,flags) plays a WAV file, using any available sound card. The parameter sound can be a file name, an alias, an audio stream, or None. The parameter flags should equal one or more constants, combined using bitwise-OR. Specify one (and only one) flag to indicate where the sound should come from: ✦ SND_FILENAME indicates that the sound is the path to a WAV file. ✦ SND_ALIAS indicates that sound is the name of a control panel soundassociation. ✦ SND_MEMORY indicates that sound is the contents of a WAV file. For example: # Play a sound file from disk: SoundFileName=”JudyGarlandKraftCheese.wav” winsound.PlaySound(SoundFileName,winsound.SND_FILENAME) 4807-7 ch24.F 5/24/01 9:00 AM Page 455 Chapter 24 ✦ Playing Sound # Play the “Exclamation” sound, as set up in Control Panel: winsound.PlaySound(“Exclamation”,winsound.SND_ALIAS) # Read sound file from disk, then play it: SoundFile=open(SoundFileName,”rb”) winsound.PlaySound(SoundFile.read(),winsound.SND_MEMORY) Other flags let you tweak behavior: SND_ASYNC Start playing the sound and return immediately. Otherwise, the call to PlaySound doesn’t return until the sound has finished playing. SND_LOOP Keep playing the sound indefinitely. (This flag should be combined with SND_ASYNC.) SND_PURGE Stop the specified sound. SND_NOSTOP Don’t stop currently playing sounds. (Raise RuntimeError if a sound is playing.) SND_NOWAIT Return immediately if the sound driver is busy. SND_NODEFAULT If the sound is not found, don’t play a default beep. Playing and recording sound on SunOS The Sun audio hardware can play audio data in u-LAW format, with a sample rate of 8000 Hz. The module sunaudiodev enables you to manipulate the Sun audio hardware using a filelike object. The related module SUNAUDIODEV provides various constants for use with sunaudiodev. The function open(mode) returns an audio device object. The parameter mode can be r for recording, w for playback, rw for both, or control for control access. Playing sound The method write(samples) plays sound, where samples is audio data as a string. A call to write adds the audio data into the audio device’s buffer. If the buffer doesn’t have enough room to contain samples, write will not return immediately. The method obufcount returns the number of samples currently buffered for playback. The method flush stops any currently playing sound, and clears the audio output buffer. The method drain waits until playback is complete, and then returns. Recording sound The method read(size) reads exactly size samples from the audio input, and returns them as a string. It blocks until enough data is available. 455 4807-7 ch24.F 456 5/24/01 9:00 AM Page 456 Part IV ✦ User Interfaces and Multimedia The method ibufcount returns the number of samples buffered for recording; you can read up to this many samples without blocking. Controlling the audio device The audio device provides a status object. The object has no methods, but has attributes as described in the audio man page. The device object provides accessors getinfo and setinfo for the status object. The method fileno returns the file descriptor for the audio device. Examining Audio Files Because there are so many file formats for storing sound, it is sometimes difficult to know which format a particular file uses. The module sndhdr provides a function, what(filename), that examines the file filename and returns its storage format. (The function whathdr is a synonym for what.) The return value of what is a 5-tuple of the form (type, SampleRate, channels, frames, BitsPerSample). Here, type is the data type; its possible values are aifc, aiff, au, hcom, sndr, sndt, voc, wav, 8svx, sb, ub, and ul. The value BitsPerSample is A for A-LAW encoding, U for u-LAW encoding, or the number of bits for standard encoding. The values SampleRate and channels are 0 if they cannot be determined. The value frames is -1 if it cannot be determined. If what is completely stumped (for example, if the file isn’t a sound file at all), it returns None. For example, the following code examines a .wav file. The file has a sampling rate of 11024. It is in mono, and uses 8 bits per sample: >>> print sndhdr.what(“bond.wav”) (‘wav’, 11025, 1, -1, 8) This file is in SunAudio format, in mono, with 188874 frames in all: >>> params=sndhdr.what(“fallofthephoton.au”) >>> params (‘au’, 8012, 1, 188874, ‘U’) >>> float(params[3])/params[1] # sound length (in seconds) 23.573889166250623 Reading and Writing Audio Files The modules aifc, wave, and sunau handle AIFF, WAV, and AU files, respectively. The interfaces for the modules are almost identical. The aifc module is documented first, followed by an accounting of the differences. 4807-7 ch24.F 5/24/01 9:00 AM Page 457 Chapter 24 ✦ Playing Sound Reading and writing AIFF files with aifc The method open(file[, mode]) returns an audiofile object. The parameter file is either a file name or an open filelike object. If file is a file name, use the mode parameter to control how the file is opened. File format An audiofile object provides accessors for the file format. You can access each component of the file format on any audiofile. You can also set the file format on a new audiofile, but only before writing any frames: ✦ getnchannels, setnchannels(channels) — Access the number of channels. ✦ getsampwidth, setsampwidth(size) — Access the size, in bytes, of each sample. ✦ getframerate,setframerate(frames) — Access the number of frames per second. ✦ getnframes, setnframes(frames) — Access the number of frames in the entire file. ✦ getcomptype, getcompname, setcomptype(type,name) — Access the compression scheme. getcomptype returns the compression scheme as a code: NONE, ALAW, ULAW, or G722. getcompname returns the compression scheme as a human-readable string. Of the parameters to setcomptype, type should be a code (as returned by getcomptype), and name should be a humanreadable name (as returned by getcompname). The method setparams sets all five components at once. Its argument is a tuple of the form (Channels,SampleWidth,FrameRate,CompType,CompName). The method getparams returns the parameters in the same order. Note Usually, you need not call setnframes to write out a new file, because the number of frames is written to the file’s header when you call close. However, if you open a filelike object that does not support seeking, then you must call setnframes before writing out audio data. Input The method readframes(count) reads count frames of audio data from the file, returning them (decompressed) in a string. Output The method writeframes(data) writes the audio data data to the file. The method writeframesraw(data) writes audio data without updating the header; it is useful for writing to a filelike object with no seek method. 457 4807-7 ch24.F 458 5/24/01 9:00 AM Page 458 Part IV ✦ User Interfaces and Multimedia Frame numbers When reading, the method setpos(framenumber) jumps to frame framenumber, and the method rewind jumps to the beginning of the file (frame 0). When writing, the method tell returns the current frame number. Using markers An AIFF file can have one or more markers. A marker has an id number, a position (frame number), and a name. To create a marker when writing a file, call setmark(id,position,name). When reading a file, you can access a list of markers by calling getmarkers. Each list element is a tuple of the form (id,position,name). You can also access a particular marker with getmark(id). Reading and writing AU files with sunau The interface of the sunau module is basically the same as that of aifc, with the following two exceptions: ✦ The available compression types are limited to ALAW, ULAW, and NONE. ✦ Markers are not available. Stub marker methods are provided for compatibility with aifc. Reading and writing WAV files with wave The interface of the wave module is basically the same as that of aifc, with these two exceptions: ✦ Compression is not available; the only supported scheme is NONE. ✦ Markers are not available. Stub marker methods are provided for compatibility with aifc. Example: Reversing an audio file Listing 24-1 reads in an audio file, and then writes out the same sound played backwards. Note that this could also be accomplished by one call to audioop.reverse (see “Handling Raw Audio Data,” later in this chapter). This example does things the long way for purposes of exposition. 4807-7 ch24.F 5/24/01 9:00 AM Page 459 Chapter 24 ✦ Playing Sound Listing 24-1: ReverseSound.py “””Reverse a sound file. Handy for finding subliminal messages.””” import sndhdr import aifc import sunau import wave def ReverseAudioStream(AudioFileIn,AudioFileOut): “”” Reverse an audio file (takes two opened audiofiles as arguments) “”” # Get header info from the input file; write it out to # the output file. Params=AudioFileIn.getparams() AudioFileOut.setparams(Params) # Collect all the frames into a list, then write them out # in reversed order: FrameCount=AudioFileIn.getnframes() FrameDataList= for FrameIndex in range(FrameCount): FrameDataList.append(AudioFileIn.readframes(1)) for FrameIndex in range(FrameCount-1,-1,-1): AudioFileOut.writeframes(FrameDataList[FrameIndex]) # We’re done! Close the files. AudioFileIn.close() AudioFileOut.close() def ReverseAudioFile(InputFileName,OutputFileName): “”” Reverse an audio file (takes two file names as arguments) “”” # First, check to see what kind of file it is: FileInfo=sndhdr.what(InputFileName) if (FileInfo==None): print “Unkown sound format - can’t reverse:”, InputFileName return FileType=FileInfo[0] try: if FileType==”aifc” or FileType==”aiff”: # aiff/aifc: use aifc module InFile=aifc.open(InputFileName,”rb”) OutFile=aifc.open(OutputFileName,”wb”) elif FileType==”au”: # Sun Audio format: use sunau module InFile=sunau.open(InputFileName,”rb”) OutFile=sunau.open(OutputFileName,”wb”) Continued 459 4807-7 ch24.F 460 5/24/01 9:00 AM Page 460 Part IV ✦ User Interfaces and Multimedia Listing 24-1 (continued) elif FileType==”wav”: # Wave format: use wave module InFile=wave.open(InputFileName,”rb”) OutFile=wave.open(OutputFileName,”wb”) else: print “Sorry, can’t reverse type”,FileType return ReverseAudioStream(InFile,OutFile) except IOError: print “Unable to open file!” return if (__name__==”__main__”): # Reverse a file. Then reverse it again, to get # (hopefully) the same thing we started with: ReverseAudioFile(“test.wav”,”backwards.wav”) ReverseAudioFile(“backwards.wav”,”forwards.wav”) # Try another audio format, too: ReverseAudioFile(“test.au”,”backwards.au”) ReverseAudioFile(“backwards.au”,”forwards.au”) Reading IFF chunked data Some sound files are divided into chunks, including AIFF files and Real Media File Format (RMFF) files. The chunk module provides a class, Chunk, to make it easier to read these files. Each chunk consists of an ID (4 bytes), a length (4 bytes), data (many bytes), and possibly one byte of padding to make the next chunk start on a 2-byte boundary. The length generally does not include the 8 header bytes. The length is normally stored in big-endian format (most-significant bit first). The constructor has the following syntax: Chunk(file[,align[,bigendian[,inclheader]]]). Here, file is an opened file- like object that contains chunked data. The flag align indicates whether chunks are aligned. The flag bigendian indicates whether the chunk length is a big-endian number. And the flag inclheader indicates whether the length includes the 8 header bytes. Parameters align and bigendian default to true; inclheader defaults to false. The methods getname and getsize return the ID and the size of the chunk, respectively. The method close skips to the end of the current chunk, but does not close the underlying file. After calling close on a chunk, you can no longer read or seek it. 4807-7 ch24.F 5/24/01 9:00 AM Page 461 Chapter 24 ✦ Playing Sound The method read([size]) reads up to size bytes of data from the chunk, and returns them as a string. If size is omitted or is negative, it reads the entire chunk. If no data is left in the chunk, it returns a blank string. The method tell returns the current offset into the chunk. The method skip jumps to the end of the current chunk. And the method seek(pos[,whence]) jumps to the position pos. If whence is 0 (the default), pos is measured from the start of the file. If whence is 1, pos is measured relative to the current file position. And if whence is 2, pos is measured relative to the start of the chunk. In addition, the method isatty is defined and returns 0 (for compatibility with normal file objects). Normally, one iterates over chunks of a file by creating, reading, and closing several chunk instances, as follows: def PrintChunkInfo(ChunkedFile): try: while (1): CurrentChunk=Chunk(ChunkedFile) print “ID:”,CurrentChunk.getname() print “Size:”,CurrentChunk.getsize() Chunk.close() except EOFError: # Constructing a chunk failed, because we # finished reading the file. Exit loop: break Handling Raw Audio Data The module audioop is a big box of handy functions for working with audio data. It is implemented in C, for speed. Each function takes audio data as a fragment, a sequence of linear-encoded samples, stored as a string. Most functions can handle 1-byte, 2-byte, or 4-byte sample widths, and they take the sample width as an argument; a few can only handle 2-byte samples. Examining a fragment These following functions each take two arguments — a fragment and a sample width: avg returns the average of all the samples in the fragment. avgpp returns the average peak-peak (with no filtering done). max returns the largest sample value. maxpp returns the largest peak-peak value. minmax returns a tuple of the minimum and maximum samples. cross returns the number of zero-crossings in the fragment. To measure the power of the fragment audio signal, call rms (root-mean-square). 461 4807-7 ch24.F 462 5/24/01 9:00 AM Page 462 Part IV ✦ User Interfaces and Multimedia The function getsample(fragment,width,n) returns the nth sample from a fragment. The sample is frame number index if fragment is in mono. Searching and matching The function findfactor(target,fragment) attempts to match fragment with target. It returns a float X such that fragment multiplied by X is as similar to target as possible. The samples target and fragment should be 2-byte samples of the same length: >>> QuietData=audioop.mul(Data,2,0.5) # half as loud >>> audioop.findfactor(Data,QuietData) 2.0001516619075197 The function findfit(target,fragment) searches for fragment in target. It returns a tuple of the form (offset,X). The closest match found starts at frame offset, and is scaled by a factor of X. Here, target and fragment are 2-byte samples, where fragment is no longer than target. The function findmax(fragment,length) looks for the loudest part of a sound. It finds a slice length samples long for which the audio signal (as measured by rms) is as large as possible. It returns the offset of the start of the slice. Translating between storage formats The audioop module can handle linear encoding, u-LAW, and Intel/DVI ADPCM. It provides several functions for converting between these schemes, as shown in Table 24-1. Table 24-1 Audio Format Conversion Functions Function Effect lin2lin(fragment, width, NewWidth) Converts a linear-encoded sample to a new sample width; returns the converted sample. Decreasing sample width lowers sound quality but saves space; increasing sample width just uses up more space. lin2adpcm(fragment, width,state) Converts a linear-encoded sample to 4-bit ADPCM encoding. The value state represents the encoder’s internal state. The return value is (newfragment,newstate), where newstate should be passed for state to the next call to lin2adpcm. Pass None for state in the first call. lin2adpcm3 is a variant of lin2adpcm, using only 3 (not 4) bits per sampledifference. 4807-7 ch24.F 5/24/01 9:00 AM Page 463 Chapter 24 ✦ Playing Sound Function Effect adpcm2lin(fragment, width,state) Converts an ADPCM-encoded fragment to linear encoding. Returns a tuple of the form (NewFragment,NewState). adpcm32lin is a variant of adpcm2lin, for conversion from 3-bit ADPCM. lin2ulaw (fragment,width) Converts a linear-encoded sound fragment to u-LAW encoding ulaw2lin (fragment,width) Converts a u-LAW encoded fragment to linear encoding. (u-LAW encoding always uses 1-byte samples, so width affects only the output fragment.) In addition, you can convert linear-encoded fragments between mono and stereo. tomono(fragment,width,lfactor,rfactor) converts a stereo fragment to a mono fragment by multiplying the left channel by lfactor, the right channel by rfactor, and adding the two channels. tostereo(fragment,width,lfactor,rfactor) converts a mono fragment to stereo. The left channel of the new fragment is the original fragment multiplied by lfactor, and similarly on the right. Most audioop functions do not differentiate between the left and right channels of stereo audio. Consider using tostereo and tomono: >>> audioop.max(Data,2) # max over both channels 26155 >>> LeftChannel=audioop.tomono(Data,2,1,0) # left*1,right*0 >>> RightChannel=audioop.tomono(Data,2,0,1) >>> audioop.max(RightChannel,2) 26155 >>> audioop.max(LeftChannel,2) 25556 >>> LoudLeftChannel=audioop.mul(LeftChannel,2,2) >>> QuietRightChannel=audioop.mul(RightChannel,2,0.5) >>> # Add the two channels back together: >>> NewData=audioop.add(audioop.tostereo(LeftChannel,2,1,0), audioop.tostereo(RightChannel,2,0,1), 2) Manipulating fragments The function add(fragment1, fragment2, width) combines two fragments of the same length and sample width by adding each pair of samples. The function reverse(fragment,width) reverses a sound fragment. The function mul(fragment,width,factor) multiplies each sample in fragment by factor, truncating any overflow. This has the effect of making the sound louder or softer. 463 4807-7 ch24.F 464 5/24/01 9:00 AM Page 464 Part IV ✦ User Interfaces and Multimedia The function bias(fragment,width,bias) adds bias to each sample in fragment and returns the result. You can speed up or slow down a fragment by calling ratecv(fragment,width,channels,inrate,outrate,state[,weightA[, weightB]]). Here, inrate and outrate are the frame rates of the input and output fragments; what is important is the ratio between inrate and outrate. The parameter state represents the internal state of the converter. ratecv returns a tuple of the form (fragment,newstate), where the value newstate should be passed in as state for the next call to ratecv. You can pass None for state in your first call. Finally, the values weightA and weightB are used for a simple audio filter; weightA (which must be at least 1) is a weight for the current sample, and weightB (which must be at least 0) is a weight for the previous sample. For example, the following code reads an audio file and slows it down to half-speed: >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> >>> WavFile=wave.open(“green1.wav”,”rb”) Params=WavFile.getparams() Data=WavFile.readframes(Params[3]) # Params[3]=framecount # outrate=2*inrate; twice as many frames per second means # the sound is half as fast: NewData=audioop.ratecv(Data,Params[1],Params[0],1,2,None) NewFile=wave.open(“green2.wav,”wb”) (NewData,State)=audioop.ratecv( Data,Params[1],Params[0],1,2,None) NewFile.setparams(Params) NewFile.writeframes(NewData) NewFile.close() winsound.PlaySound(“green2.wav”,winsound.SND_FILENAME) Summary Sound can be stored in many file formats. Python’s standard libraries can read and write most sound files, and perform low-level manipulation of audio data. They also enable you to play sound on many operating systems. In this chapter, you: ✦ Played a musical scale on a PC speaker. ✦ Parsed sound files in various formats, and stored sounds in reverse. ✦ Manipulated raw audio data. In the next chapter, you learn how to create and manage multiple threads in your Python programs. ✦ ✦ ✦ 4807-7 PO5.F 5/24/01 9:00 AM Page 465 P Advanced Python Programming A R T V ✦ ✦ ✦ ✦ Chapter 25 Processing Images Chapter 26 Multithreading Chapter 27 Debugging, Profiling, and Optimization Chapter 28 Security and Encryption Chapter 29 Writing Extension Modules Chapter 30 Embedding the Python Interpreter Chapter 31 Number Crunching Chapter 32 Using NumPy Chapter 33 Parsing and Interpreting Python Code ✦ ✦ ✦ ✦ 4807-7 PO5.F 5/24/01 9:00 AM Page 466 4807-7 ch25.F 5/24/01 9:00 AM Page 467 25 CHAPTER Processing Images ✦ ✦ ✦ ✦ In This Chapter T his chapter describes the modules that help you work with graphics files. Python comes with modules that help you identify image file types, convert between different color systems, and handle raw image data. Image Basics Computer images are made up of a group of pixels, or picture elements, and an image’s size is usually specified by its width and height in pixels. There is a mind-boggling number of file formats that you can use to store images; fortunately, however, a few (such as GIF, JPEG, and PNG) are popular enough to be considered standard. Some image file formats limit the number of different colors you can have in the image (GIFs, for example, can be any 256 out of 16,777,217 different colors), and some represent each pixel by its index in a palette of color definitions. Image file formats store the data in either raw, or uncompressed, form, or they apply some sort of compression to make the date smaller. Compression techniques fall into two categories: Lossless compression (as is used by GIF files) means that no data is lost and that when a viewer decompresses the image and displays it, it is identical to the original. Lossy compression (as is used by JPEG files) means some detail is thrown away in order to achieve better compression. Some image file formats also support transparency, so that if you display the image over another image, the parts that were marked as transparent leave that part of the original image visible. Index-based formats tag a particular color as the transparent color (so that pixels having that index value are completely transparent), and other formats include an alpha channel that tells the degree of transparency of each pixel. Image basics Identifying image file types Converting between color systems Handling raw image data Using the Python imaging library ✦ ✦ ✦ ✦ 4807-7 ch25.F 468 5/24/01 9:00 AM Page 468 Part V ✦ Advanced Python Programming Identifying Image File Types The imghdr module makes an educated guess as to the type of image stored in a file: >>> import imghdr >>> imghdr.what(‘c:\\temp\\jacobSwingSleep.jpg’) ‘jpeg’ It looks at the first few bytes of the header, not the entire file, so it doesn’t guarantee file integrity, but it does serve to differentiate between valid types. Instead of passing in a file name, you can pass in a string that contains the first few bytes of a file: >>> hdr = open(‘snake.bmp’,’rb’).read(50) # Read a little >>> imghdr.what(‘’,h=hdr) ‘bmp’ Table 25-1 lists the values that the what function returns and the different file types that imghdr recognizes. Table 25-1 Image Types Recognized by imghdr Image Type Value Returned CompuServe Graphics Interchange gif JFIF Compliant JPEG jpeg Windows or OS/2 Bitmap bmp Portable Network Graphics png SGI Image Library (RGB) rgb Tagged Image File Format tiff Portable Bitmap pbm Portable Pixmap ppm Portable Graymap pgm Sun Raster Image rast X11 Bitmap xbm 4807-7 ch25.F 5/24/01 9:00 AM Page 469 Chapter 25 ✦ Processing Images By adding to imghdr’s tests list of functions, you can have it check for additional file types. The module is just testing for known file types; it is not doing anything specific to images. The following example looks for the special prefix at the beginning of all bytecode-compiled Python (.pyc) files: >>> def test_pyc(h,f): ... import imp ... if h.startswith(imp.get_magic()): ... return ‘pyc’ >>> imghdr.tests.append(test_pyc) >>> imghdr.what(‘leptolex.pyc’) ‘pyc’ Custom test functions like the one shown in the preceding example take two parameters. The first contains a string of bytes representing either the first few bytes of the file (if what was called with a file name) or the string of bytes the user passed in to what. If the user called what with a file name, the f parameter is an open filelike object positioned just past the read to retrieve the bytes for the h parameter. Converting Between Color Systems A color system is a model that represents the different colors that exist; color systems make it possible to refer to colors numerically. By converting a color to a number, things like television signals and computer graphics become possible. Each color system has its own set of advantages, and the colorsys module helps you convert colors from one system to another. Color systems colorsys supports conversion between four of the most popular color systems; and in each, a color is represented by a 3-tuple of numbers from 0.0 to 1.0. RGB If you’ve worked with computer graphics, then the RGB or red-green-blue color system is probably somewhat familiar; it’s the color system used by most computer software and hardware. This model is derived from the tristimulus theory of vision, which states that there are three visual pigments in the cones in the retinas of our eyes. When they are stimulated, we perceive color. The pigments are red, green, and blue. 469 4807-7 ch25.F 470 5/24/01 9:00 AM Page 470 Part V ✦ Advanced Python Programming YIQ The YIQ color system is the one used by the National Television System Committee (NTSC), the standards body for television signals in the United States. Unlike RGB, which has three distinct signals, TVs have only a single composite signal. To make matters more complicated, the same signal must work with both black-and-white and color televisions sets. The Y component in a YIQ color is the brightness (luminance) of the color. It is the only component used by black-and-white televisions, and is given the overwhelming majority of the TV signal bandwidth. The I component contains orange-cyan hue information, which provides the coloring used in flesh tones. The Q component has green-magenta hue information, and is given the least amount of signal bandwidth. HLS For people, the HLS, or hue-lightness-saturation, color system is more intuitive than RGB because you can specify a color by first choosing a pure hue (such as pure green) and then adding different amounts of black and white to produce tints, tones, and shades. The L component is the lightness, where 1.0 is white and 0.0 is black. S is the saturation level of the hue; 1.0 is fully saturated (the pure hue), whereas 0.0 is completely unsaturated, giving you just a shade of gray. HSV The HSV, or hue-saturation-value, system is very close to the HLS model except that the pure hues have a V (corresponding to L in HLS) component value of 0.5. Converting from one system to another colorsys contains functions for converting from RGB to any of the other systems, and from any of the others to RGB: >>> import colorsys >>> colorsys.hls_to_rgb(0.167,0.5,1.0) # Yellow (0.998, 1.0, 0.0) To convert from HLS to YIQ, for example, you use a two-step process — converting first to RGB and then from RGB to YIQ. Of course, if you were planning to do many such conversions, it would be worthwhile to write your own function to convert directly between the two. Although these routines use color parameters in the range from 0.0 to 1.0, it’s also common to see each parameter specified using an integer range from 0 to 255 (the values that fit in a single byte of memory). To convert to that format, just multiply each component by 255. This format reduces the number of unique colors you can specify (down to around 16.8 million), but don’t worry: the human eye can’t really distinguish between more than about 83,000 anyway. 4807-7 ch25.F 5/24/01 9:00 AM Page 471 Chapter 25 ✦ Processing Images Listing 25-1 is a color choosing utility. You choose a color using the HLS color system and it shows that color along with its RGB equivalent, as shown in Figure 25-1. Listing 25-1: choosecolor.py — A HLS-to-RGB color converter from Tkinter import * import colorsys def update(*args): ‘Get the scale values and change the canvas color’ r,g,b = colorsys.hls_to_rgb(h.get()/255.0, l.get()/255.0,s.get()/255.0) r,g,b = r*255,g*255,b*255 rgb.configure(text=’RGB:(%d,%d,%d)’ % (r,g,b)) c.configure(bg=’#%02X%02X%02X’ % (r,g,b)) # Create a window with 3 scales and a canvas root = Tk() hue = Label(root,text=’Hue’) hue.grid(row=0,column=0) light = Label(root,text=’Lightness’) light.grid(row=0,column=1) sat = Label(root,text=’Saturation’) sat.grid(row=0,column=2) rgb = Label(root,text=’RGB:(0,0,0)’) rgb.grid(row=0,column=3) h = Scale(root,from_=255,to=0,command=update) h.grid(row=1,column=0) l = Scale(root,from_=255,to=0,command=update) l.grid(row=1,column=1) s = Scale(root,from_=255,to=0,command=update) s.grid(row=1,column=2) c = Canvas(root,width=100,height=100,bg=’Black’) c.grid(row=1,column=3) root.mainloop() 471 4807-7 ch25.F 472 5/24/01 9:00 AM Page 472 Part V ✦ Advanced Python Programming Figure 25-1: This utility converts colors from the HLS system to the RGB system. Handling Raw Image Data Python works well as a general-purpose programming language, and often leaves special-purpose functionality up to third-party developers. As such, Python’s builtin support for handling raw image data is meager at best. The imageop module manipulates raw image data that you pass it as a Python string of bytes. The data must be either 8-bit (each pixel is represented by one character in the string) or 32-bit (4 characters per pixel; each group of 4 characters represents red, green, blue, and alpha or transparency components for that pixel). How you go about obtaining data in that format is up to you, but if you’re on an SGI computer, you can use the imgfile module. In addition, if you have an SGI RGB file, you can load it using the rgbimg module, and then pass its contents to imageop. imageop has a few functions for cropping and scaling images, but the bulk of its functions have to do with converting between grayscale images of different color depths (for example, converting from a 2-bit grayscale image to an 8-bit grayscale image). For real image processing, see the next section for information about available third-party modules. Using the Python Imaging Library If you plan to do a lot of image processing, check out the Python Imaging Library (PIL) from Pythonware (www.pythonware.com). It is free for both private and commercial use, and Pythonware also has commercial support plans available. It’s painless to install and is well worth the download. PIL is fast, and its wide range of features enables you to perform a number of image processing tasks, including converting between different file formats; processing images (cropping, resizing, and so forth); annotating existing images with text; and creating new images from scratch with its drawing functions. 4807-7 ch25.F 5/24/01 9:00 AM Page 473 Chapter 25 ✦ Processing Images The next few sections show you how to get started with PIL; consult its online documentation for even more features. Visit the Graphics section in the Vaults of Parnassus (www.vex.net/parnassus/) for plenty of other graphics and image processing utilities. Tip Retrieving image information The main module in PIL is Image, and you use it to open and create images: >>> import Image >>> i = Image.open(‘shadowtest.bmp’) >>> i.mode ‘RGB’ >>> i.size (320, 240) >>> i.format ‘BMP’ >>> i.getbands() (‘R’, ‘G’, ‘B’) >>> i.show() # Displays the image An image’s mode specifies its color depth and storage; some of the common values are listed in Table 25-2. Table 25-2 PIL Mode Values Mode Description 1 1-bit pixels, black and white L 8-bit pixels, black and white P 8-bit pixels, using a 256-color palette RGB 3 bytes per pixel, true color RGBA 4 bytes per pixel, true color with alpha (transparency) band I 32-bit integer pixels F 32-bit floating point pixels Images have one or more bands, or components, of data. For example, each pixel in an RGB image has a red, green, and blue component; that image is said to have three bands. 473 4807-7 ch25.F 474 5/24/01 9:00 AM Page 474 Part V ✦ Advanced Python Programming An image’s show() method is a debugging facility that saves the image to a temporary file and launches the default viewer for that file type. Note Sometimes the show() command has trouble working from inside IDEs such as PythonWin. One nice feature about PIL is that it waits to read and decode file data until it really needs to. This means, for example, that you can open an enormous image and read its size and type information very quickly. Copying and converting images The copy() method returns a new image object identical to the old one, so that you can make changes without modifying the original. convert(mode) returns a new image in the given mode (there are also variations on this method that let you pass in a palette or even a conversion matrix). The following example loads a full-color JPEG image, converts it to a 1-bit black-and-white image, and displays it as shown in Figure 25-2: >>> img = Image.open(‘binky.jpg’) >>> img.show() # Show the original >>> img.convert(‘1’).show() # Show the new version The save(filename) method writes the contents of the current image to a file. PIL looks at the extension you give the file name, and converts it to the appropriate format. For example, if you have an image file named test.jpg, you can convert it to a GIF as follows: >>> Image.open(‘test.jpg’).save(‘test.gif’) Because JPEG files are true color, but GIF uses a 256-color palette, PIL takes care of the necessary conversion as it saves the file. As mentioned earlier, PIL waits as long as possible before loading and decoding file data, so even if you open an image, its pixel data isn’t read until you display it or apply some conversion. Therefore, you can use the draft(mode, (w,h)) method to instruct the image loader to convert the image as it is loaded. For example, if you have a huge 5,000 × 5,000–pixel, full-color image and you only want to work on a smaller, 256-color copy of it, you can use something like the following: img = Image.open(‘huge.jpg’).draft(‘P’,(250,250)) 4807-7 ch25.F 5/24/01 9:00 AM Page 475 Chapter 25 ✦ Processing Images Figure 25-2: A true color image (on the left) and a 1-bit version (on the right) after using the convert() method Using PIL with Tkinter The ImageTk module provides two classes, BitmapImage and PhotoImage, that create Tkinter-compatible bitmaps and images that can be used anywhere Tkinter expects a bitmap (black-and-white image) or image (color image). Not only can you then use PIL’s image processing features in any Tkinter program, you can also use it to load image formats that Tkinter doesn’t understand. CrossReference Note Refer to Chapters 19 and 20 for coverage of Tkinter. PIL also has functions for creating a Windows-compatible bitmap (DIB) that can be drawn into a Windows device context, and functionality for writing images out to PostScript files or printers. 475 4807-7 ch25.F 476 5/24/01 9:00 AM Page 476 Part V ✦ Advanced Python Programming Cropping and resizing images The crop((left, top, right, bottom)) method returns a rectangle portion of an image. resize((w, h)[, filter) returns a resized copy of an image. The filter argu- ment controls what sort of sampling is used against the original image, and can be one of BILINEAR, BICUBIC, or NEAREST (the default). One other useful method is thumbnail((w, h)), which resizes the object in place while maintaining the original aspect (width-to-height) ratio. Because of this, it may not use the exact size you pass in. Modifying pixel data You can access and change the value of any image pixel by its (x,y) coordinates, with (0,0) being the upper-left corner. Like Python slices, coordinates refer to the spaces between pixels, so a rectangle with its upper-left and lower-right corners at (0,0) and (20,10) would be 20 pixels wide and 10 tall. The getpixel((x, y)) and putpixel((x, y), value) methods get and set individual pixels, where value is in the appropriate form for the image’s mode. The following code opens an image, paints a black band across it, and displays the results (shown in Figure 25-3): >>> i = Image.open(‘shadowtest.bmp’) >>> i.getpixel((10,25)) (156, 111, 56) >>> for y in xrange(50,60): ... for x in xrange(i.size[0]): ... i.putpixel((x,y), (0,0,0)) >>> i.show() Figure 25-3: Use getpixel and putpixel to operate on individual pixel values. 4807-7 ch25.F 5/24/01 9:00 AM Page 477 Chapter 25 ✦ Processing Images getdata() returns a list of tuples representing each pixel in the image, and putdata(data, [,scale][, offset]) places a sequence of tuples into the image (the offset defaults to the beginning of the image, and the scale defaults to 1.0). PIL’s ImageDraw module provides Draw objects that let you draw shapes and text on an image. The following example displays the image shown in Figure 25-4: >>> >>> >>> >>> >>> >>> ... import Image, ImageDraw from whrandom import randrange img = Image.open(‘happy.jpg’) draw = ImageDraw.Draw(img) points = # Create a list of random points for i in xrange(10): points.append((randrange(img.size[0]), # x randrange(img.size[1]))) # y >>> draw.line(points) >>> img.show() Figure 25-4: The ImageDraw module lets you draw shapes and text on images. Listing 25-2 takes the current time and creates a GIF file containing an analog clock face image, as shown in Figure 25-5. On-the-fly image generation is often useful in creating dynamic content for Web pages (and if there’s anything the world needs, it’s yet another time display on a Web page). 477 4807-7 ch25.F 478 5/24/01 9:00 AM Page 478 Part V ✦ Advanced Python Programming Listing 25-2: clockgif.py — Generates a clock face showing the current time import time,Image,ImageDraw def centerbox(rmax,perc): ‘Returns a coordinate box perc % of rmax’ sub = rmax*perc/100.0 return (rmax-sub,rmax-sub,rmax+sub,rmax+sub) r = 100 # clock face radius img = Image.new(‘RGB’,(r*2,r*2),color=(128,128,128)) draw = ImageDraw.Draw(img) # Make the clock body draw.pieslice(centerbox(r,100),0,360,fill=(0,0,0)) draw.pieslice(centerbox(r,98),0,360,fill=(80,80,255)) draw.pieslice(centerbox(r,94),0,360,fill=(0,0,0)) draw.pieslice(centerbox(r,93),0,360,fill=(255,255,255)) # Draw the tick marks for i in range(12): deg = i * 30 draw.pieslice(centerbox(r,90),deg-1,deg+1,fill=(0,0,0)) draw.pieslice(centerbox(r,75),0,360,fill=(255,255,255)) # Get the current time now = time.localtime(time.time()) hour = now[3] % 12 minute = now[4] # Draw the hands hdeg = hour * 30 + minute / 2 mdeg = minute * 6 draw.pieslice(centerbox(r,50),hdeg-4,hdeg+4,fill=(100,100,100)) draw.pieslice(centerbox(r,85),mdeg-2,mdeg+2,fill=(100,100,100)) #img.rotate(90).show() # For debugging img.rotate(90).save(‘currenttime.gif’) 4807-7 ch25.F 5/24/01 9:00 AM Page 479 Chapter 25 ✦ Processing Images Figure 25-5: With PIL, it’s easy to create on-the-fly images. As you may have noticed, this example makes heavy use of Draw’s pieslice((left, top, right, bottom, startangle, stopangle[, fill][, outline]) method. In order to make it easy to use a different size clock, all mea- surements are calculated as percentages of the radius (therefore, changing the value of r is all you need to do). The centerbox function is a helper function that returns a square enclosing a circle of the right size. One other thing to notice is that an angle of zero is directly to the right of center, and angle measurements are clockwise from there. Instead of working around that in the calculations for the placement of the clock hands, it was easier to just draw them as if the clock were on its side, and then rotate the entire image by 90 degrees (note that image rotation degrees are counterclockwise). The following list contains the more common methods of a Draw object: setink(ink) setfill(onoff) setfont(font) arc((x1, y1, x2, y2), start, end[, fill]) bitmap((x, y), bitmap[, fill]) chord((x1, y1, x2, y2), start, end[, fill][, outline]) ellipse((x1, y1, x2, y2)[, fill][, outline]) line((x, y)[, fill]) pieslice((x1, y1, x2, y2), start, end[, fill][, outline]) point((x, y)[, fill]) polygon((x, y)[, fill][, outline]) rectangle((x1, y1, x2, y2)[, fill][, outline]) text((x, y), text[, fill][, font][, anchor]) 479 4807-7 ch25.F 480 5/24/01 9:00 AM Page 480 Part V ✦ Advanced Python Programming Other PIL features New versions of PIL continue to add powerful new features; check the Pythonware Web site (www.pythonware.com) for new versions and more documentation. Other interesting PIL modules and features include: ✦ ImageEnhance — Contains classes for adjusting the color, brightness, contrast, and sharpness of an image ✦ ImageChops — Provides arithmetic image operations (adding and subtracting images) as well as functions for lightening, darkening, and inverting images ✦ Support for creating animated (multiframe) GIF and FLI/FLC images ✦ Transformations, including rotating at arbitrary angles and applying a Python function to each pixel ✦ Image filters for blurring images or finding edges ✦ The capability to add your own decoders for new image types Summary Python offers helpful support for processing images, such as modules for identifying image file types. In this chapter, you: ✦ Learned about the information commonly stored in image files. ✦ Identified file types using the imghdr module. ✦ Converted colors between different color systems such as RGB and HLS. ✦ Modified images using the Python Imaging Library. The next chapter shows you how to create multithreaded applications so that your programs can work on more than one task at a time. ✦ ✦ ✦ 4807-7 ch26.F 5/24/01 9:01 AM Page 481 26 CHAPTER Multithreading R unning several threads is similar to running several different programs concurrently, but with the following benefits: ✦ Threads can easily share data, so writing threads that cooperate is simpler than making different programs work together. ✦ Threads do not require much memory overhead; they are cheaper than processes. (In the UNIX world, threads are often called light-weight processes.) Understanding Threads Threads are useful in many situations where your program needs to perform several tasks that aren’t necessarily interdependent. Programs with a GUI, for example, often use two threads: one to handle user interface jobs such as repainting the window, and one to handle the “heavy lifting,” such as talking to a database. Other times, threads are useful because it’s more logical to divide work into distinct parts. For example, a game might have a separate thread for each computercontrolled player or object. A thread may be interrupted by another thread at any time. After any line of code, the Python interpreter may switch to another thread. Note Some programmers call this interruption timeslicing. However, strictly speaking, timeslicing refers to the vaguely Communist notion of giving every thread equal amounts of CPU time. The interpreter checks for thread switching once every few bytecode instructions; sys.setcheckinterval (which defaults to 10) is the number of bytecodes between switches. ✦ ✦ ✦ In This Chapter Understanding threads Spawning, tracking, and killing threads Avoiding concurrency issues Preventing deadlock Example: downloading from multiple URLs Porting threaded code Weaving threads together with Queue ✦ ✦ ✦ ✦ 4807-7 ch26.F 482 5/24/01 9:01 AM Page 482 Part V ✦ Advanced Python Programming The switching is transparent to you, and exactly when the switch happens is up to the Python interpreter, the operating system, and the phase of the moon: In a multithreaded program, the order of execution may change from one run to the next. This unpredictability is the reason why multithreading can be trickier than singlethreaded programming: A buggy program might work nine times out of ten, and then crash the tenth time because the order of execution was different. In general, you create all threads (other than the main thread) yourself. However, a C extension may create dummy threads to do its work. Talking to these threads from Python is difficult, so be forewarned if you want to communicate with dummy threads. A long-running calculation in an extension module effectively counts as one instruction, so be aware that other threads may have to wait a while for a dummy thread to take its turn! Spawning, Tracking, and Killing Threads Python features two multithreading modules, thread and threading. The modules overlap enough that you can choose the one you like best and use it exclusively. threading is a high-level module that calls thread for lower-level operations. threading includes a Thread class similar to Java’s thread class, so it is a good choice for Java veterans. We included two versions of this chapter’s example — one using thread and one using threading — to illustrate the workings of both. Creating threads with the thread module To spawn another thread, call start_new_thread (function, args[, kwargs]) The function call returns immediately and the child thread starts and calls function; when function returns, the thread terminates. function can be an object method. args is a tuple of arguments; use an empty tuple to call function without passing any arguments. kwargs is an optional dictionary of keyword arguments. Here are two ways of starting a new thread: thread.start_new_thread(NewThread.run,()) thread.start_new_thread(CalcDigitsOfPi,(StartDigit,NumDigits)) Each thread has an ID number, which you can see by calling thread.get_ident(). The ID is unique at any given time, but if a thread dies, a new thread may re-use its ID. If several threads print log messages, it can become hard to determine which thread said what; something like a party where everyone talks at once. The following example uses thread identifiers to indicate which thread is talking: 4807-7 ch26.F 5/24/01 9:01 AM Page 483 Chapter 26 ✦ Multithreading def PrintDebugMessage(ThreadNameDict,Message): CurrentThreadID = thread.get_ident() # Look up the thread name in the name dictionary. If # there is no name entry for this ID, use the ID. CurrentThreadName = ThreadNameDict.get(\ CurrentThreadID, CurrentThreadID) print CurrentThreadName,Message A thread terminates when its target function terminates, when it calls thread.exit(), or when an unhandled SystemExit exception is raised. Python raises the exception thread.error if a threading error occurs. Starting and stopping threads with the threading module threading defines a Thread class to handle threads. To spawn a new thread, you first create a Thread object and then call its start() method. start() creates the actual thread and starts the target function; you should call start only once per thread. The Thread constructor takes several keyword arguments, all of which are optional: ✦ target — Function to call when you start() the thread. Defaults to None. You should pass a value for target unless you override the run() method of Thread in a subclass; otherwise, your thread will not do anything. ✦ name — String name of this thread. The default name is of the form “Threadn,” where n is a small decimal number. ✦ args — A tuple of arguments to pass to the target function. Empty by default. ✦ kwargs — Keyword argument dictionary to pass to the target function. Empty by default. ✦ group — Currently unused. In the future, it will designate a thread group. This code uses a Thread object to run the function CalcDigitsOfPi in a new thread: PiThread = \ Thread(target=CalcDigitsOfPi,args=(StartDigit,NumDigits)) PiThread.start() You can create a subclass of the Thread class, and override the run() method to do what you want. This is a good approach if you are tracking thread-specific data. You should not override methods other than __init__() and run(). If you override __init__, you should call the __init__ method of the parent class in your constructor: 483 4807-7 ch26.F 484 5/24/01 9:01 AM Page 484 Part V ✦ Advanced Python Programming class SearchThread(threading.Thread): def __init__(self): threading.Thread.__init__(self) # Now carry on constructing... self.Matches={} Threads can be flagged as daemon threads. The main thread (and therefore, your Python program) keeps running as long as there are non-daemon threads running; if only daemonic threads are running, the script exits. You set daemon status with setDaemon(boolean) and check it with isDaemon(). You must set a thread’s daemon status before calling start(). Child threads inherit their daemonic status from their parents. Note In a programming context, a daemon is a process or thread that silently handles some ongoing, invisible task. If you should encounter a daemon outside a programming context, we recommend you avoid signing anything. Thread status and information under threading You can check whether a Thread object is running with the method isAlive(). isAlive() returns true if someone has called start(), and the run() method has not returned yet. Each thread has a name, an arbitrary string which you can access by getName() and setName(newName). Finding threads under threading threading.enumerate() returns a list of all active Thread objects. This includes dummy threads, daemon threads, and the main thread. Because the list contains the main thread, it is never empty. threading.activeCount() returns the number of active threads; this number is equal to the length of the list returned by threading.enumerate(). A call to threading.currentThread() returns an object corresponding to the current thread of control. (Even the main thread has a corresponding Thread object.) Waiting for a thread to finish To wait for a Thread to terminate, call its join method. join blocks until the thread dies; it returns immediately if the thread has not started, or has already terminated. For example, the following lines of code (executed in the main thread) wait until all the other currently active threads have terminated: ThisThread = threading.currentThread() 4807-7 ch26.F 5/24/01 9:01 AM Page 485 Chapter 26 ✦ Multithreading while (threading.activeCount()>1): CurrentActiveThreads = threading.enumerate() for WaitThread in CurrentActiveThreads: # Don’t wait for myself: if (WaitThread != ThisThread): WaitThread.join() # Now all those threads have finished. We are now the # only running thread, unless someone spawned new threads # while we were waiting. If that happened, we make # another pass through the while loop. (If that can’t # happen, the whiling is superfluous) Avoiding Concurrency Issues “Oh, what a tangled web we weave, when first we practice to...implement multithreaded database access.” — Sir Walter Scott, as reinterpreted by an unnamed programmer at 2 a.m. Imagine a chalkboard on which three professors are each writing some information. The professors are so deep in thought that they are blissfully unaware of one another’s presence. Each professor erases some chalk marks, writes on the board, pauses to think, and then continues. In the process, the professors erase bits of each other’s writings, and the resulting blackboard is a mess of unrelated word salad. Threads run in the same address space, so they can access the same data. Unfortunately, threads can also break other thread’s data if they do not cooperate. The professors and the chalkboard illustrate what can go wrong. The phrase concurrency issues is a catchall term for all the ways in which two threads, working together, may put data into an unusable form. A program or object free of concurrency issues is called thread-safe. Returning to the chalkboard example: Everything would have been fine if the professors had taken turns, and the second professor had waited until the first was done with the chalkboard. You can solve most concurrency issues by restricting data access to one thread at a time. A lock, or mutex (from “mutually exclusive”), is the way you make your threads take turns. A lock has two states: acquired and released. A thread must acquire the lock before it is allowed to access the data. When the thread is done, it releases the lock. If a lock has been acquired, other threads must wait, or block, until the lock is released before they can acquire it. Locking with thread To create a new lock, call thread.allocate_lock(), which returns a lock object. 485 4807-7 ch26.F 486 5/24/01 9:01 AM Page 486 Part V ✦ Advanced Python Programming To acquire the lock, call the method acquire([waitflag]). Call acquire(1) to wait for the lock as long as necessary. Call acquire(0) to return immediately if the lock isn’t available. If you pass a value for waitflag, acquire() returns 1 if it acquired the lock, 0 if it didn’t. If you don’t pass a waitflag, acquire() waits for the lock, and returns None. This code snippet uses locks to access some data in a thread-safe way: # Acquire the employee lock. Block until acquired. EmployeeLock.acquire(1) # Try to acquire the Company lock, and return immediately. if (CompanyLock.acquire(0)): # Do stuff with the company object, then release it else: # Don’t do stuff with the company object, because # you don’t have its lock! To release a lock, call its release() method. You can release a lock that was acquired by another thread. If you release a lock that isn’t currently acquired, the exception thread.error is raised. You can check whether a lock is acquired with the locked() method. When first created, the object is in its released state. Use acquire(0), and not just a call to locked() if you don’t want your code to wait for a lock. For example, the following code may block if another thread grabs the lock between our call to locked() and our call to acquire(): if (not RecordLock.locked()): RecordLock.acquire() # We may be here a while! Locking with threading The threading module offers several flavors of concurrency control. The Lock class is a simple wrapper for the lock class of the thread module; most of the other concurrency-control classes are variations on the Lock class. Lock — simple locking When you create a Lock object, it starts in the released state. The Lock object has two methods: acquire() and release(). These methods are wrappers for the acquire() and release() methods in the thread module; see the previous sections for details. RLock — reentrant locking RLock (“reentrant lock”) is a variation on Lock, and its acquire() and release() methods have the same syntax. An RLock may be acquired multiple times by the same thread. The RLock keeps track of how many times it has been acquired. Other 4807-7 ch26.F 5/24/01 9:01 AM Page 487 Chapter 26 ✦ Multithreading threads cannot acquire the RLock until the owning thread has called release() once for each call to acquire(). An RLock must be released by the same thread that acquired it. Semaphore — n-at-a-time locking A semaphore is also a kind of lock. The Semaphore class has acquire() and release() methods with the same syntax as Lock. However, whereas a lock restricts access to one thread at a time, a semaphore may permit access by several threads at a time. A semaphore keeps an internal counter of “available slots.” Releasing the semaphore increases the counter; acquiring the semaphore decreases the counter. The counter is not allowed to go below zero. If the counter is at zero, no thread can acquire the semaphore until it has been released at least once, and so threads that try to acquire it will block until the semaphore has an available slot. Passing an integer to the Semaphore constructor gives the counter an initial value; it defaults to 1. For example, assume several threads want to call a function that is memory-intensive. More than one thread can call it at once, but if too many calls happen at once, the system will run out of physical memory and slow down. You could limit the number of simultaneous calls with a semaphore: # Create a semaphore, for later use: MemorySemaphore = Semaphore(MAXIMUM_CALLERS) # This is a safe wrapper for the function MemoryHog: def SafeMemoryHog(): MemorySemaphore.acquire(1) MemoryHog() MemorySemaphore.release() Event — simple messages between threads An event lets one thread block until triggered by another. The Event class has an internal true/false flag that is initially false. This flag is similar to a traffic light, where false means stop and true means go. You can check the flag’s value with the isSet() method, set it to true with set(), and set it to false with clear(). Calling clear() is like a stop sign to other threads; calling set() is a go sign. You can make a thread wait until the flag is true. Call the event’s wait() method to block until the event’s flag is set. You can pass a number to wait(), indicating a timeout. For example: If the flag is not set within 2.5 seconds, a call to wait(2.5) will return anyway. For example, this code snippet is part of a script that munges data. The munging can be stopped and started by setting the global Event object, MungeEvent: def StopMunging(): MungeEvent.clear() # stop! 487 4807-7 ch26.F 488 5/24/01 9:01 AM Page 488 Part V ✦ Advanced Python Programming def StartMunging(): MungeEvent.set() # go! def MungeData(): while (1): MungeEvent.wait() # wait until we get the green light MungeOneRecord() Condition — wrapper for a lock The Condition class wraps a lock. You can pass a Lock object to the Condition constructor; if not, it creates an RLock internally. A condition object has acquire() and release() methods, which wrap those of the underlying lock object. Condition objects have other methods: wait([timeout]), notify(), and notifyAll(). A thread should acquire the lock before calling these methods. A call to the wait([timeout]) method immediately releases the lock, blocks until notification is received (when another thread calls notify() or notifyAll()), acquires the lock again, and then returns. If you supply a value for timeout, the call will return after that many seconds have passed, whether or not it was notified or reacquired the lock. You call notify to wake up other threads that have called wait on the condition. If there are waiting threads, notify awakens at least one of them. (Currently, notify never awakens more than one, but this is not guaranteed for future versions.) notifyAll wakes up all the waiting threads. A word of warning When threads share data, examine every piece of data to ensure that thread interaction can’t put the data into an invalid state. A program that is not thread-safe may work for months, waiting for a dramatic time to fail. Eternal vigilance is the price of multithreading! Preventing Deadlock Assume one thread acquires a lock, but hangs without releasing it. Now, no other threads can acquire that lock. If another thread waits for the lock (by calling the acquire(1) method), it will be frozen, waiting for the lock forever. This state is called deadlock. Deadlock is not as sneaky a bug as some concurrency issues, but it’s definitely not good! The section of code between acquiring a lock and releasing it is called a critical section. To guard against deadlock, there should be only one code path into the critical section, and only one way out. The critical section should be as short as possible, to prevent deadlock bugs from creeping in. In addition, the critical section should 4807-7 ch26.F 5/24/01 9:01 AM Page 489 Chapter 26 ✦ Multithreading execute as quickly as possible — other threads may be waiting for the lock, and if they spend a long time waiting, nothing happens in parallel and the benefits of multithreading evaporate. It is generally good practice to put a try...finally clause in a critical section, where the finally clause releases the lock. For example, here is a short function that tags a string with the current thread ID and writes the string to a file: def LogThreadMessage(LogFile,Message): LogFileLock.acquire(1) try: LogFile.write(thread.get_ident()+Message+”\n”) finally: # If we do not release the lock, then another thread # might wait forever to acquire it: LogFileLock.release() Example: Downloading from Multiple URLs The following code is a more complex example of some of the features covered in this chapter. The script retrieves files from a list of target URLs. It spawns several threads, each of which retrieves one file at once. Multithreading makes the whole process faster, because thread A can receive data while thread B is waiting for a response from the server. CrossReference See “Multitasking Without Threads” in Chapter 13 for an alternate solution to this problem using the asyncore and select modules. We wrote two versions of the URLGrabber script — one using the threading module (see Listing 26-1), and one using thread (see Listing 26-2). Most of the code is the same; unique code is bolded in the source listing. Listing 26-1: URLGrabber — threading version # # # # # # # URLGrabber retrieves a list of target files from the network to the local disk. Each file has a particular URL, indicating where and how we should request it. This version of URLGrabber uses the threading module. It uses a Lock object to limit access to the URLList. (Without this lock, two threads might both grab the same URL) import import import import threading urllib urlparse os Continued 489 4807-7 ch26.F 490 5/24/01 9:01 AM Page 490 Part V ✦ Advanced Python Programming Listing 26-1 (continued) import sys import traceback # The optimal number of worker threads depends on one’s bandwidth WORKER_COUNT = 4 # Default filename of our url list URL_FILE_NAME = “MyURLList.txt” “”” A WorkerThread downloads files from URLs to disk. Each WorkerThread object corresponds to a single flow of control. WorkerThread is a subclass of Thread, overriding the run() and __init__() methods. (Thread’s other methods should not be overridden!) “”” class WorkerThread(threading.Thread): def __init__(self, URLList, URLListLock): # Call the Thread constructor (Python subclasses do *not* # automatically invoke parent class constructors) threading.Thread.__init__(self) # Cache references... self.URLList=URLList self.URLListLock = URLListLock “”” Acquire the URLList lock, grab the first URL from the list, cross the URL off the list, and release the URLList lock. (This code could be part of run(), but it’s good to put critical sections in their own function) “”” def GrabNextURL(self): self.URLListLock.acquire(1) # 1 means we block if (len(self.URLList)<1): NextURL=None else: NextURL=self.URLList[0] del self.URLList[0] self.URLListLock.release() return NextURL “”” We override Thread’s run() method with one that does what we want. Namely: Take URLs from the list, and retrieve them. When we run out of URLs, the function returns, and the thread dies. “”” def run(self): while (1): NextURL = self.GrabNextURL() if (NextURL==None): # The URL list is empty! Exit the loop. break try: self.RetrieveURL(NextURL) except: self.LogError(NextURL) def RetrieveURL(self,NextURL): # urlparse splits a URL into pieces; # piece #2 is the file path 4807-7 ch26.F 5/24/01 9:01 AM Page 491 Chapter 26 ✦ Multithreading FilePath=urlparse.urlparse(NextURL)[2] FilePath = FilePath[1:] # strip leading slash # If file name is blank, invent a name if (FilePath==””): FilePath=”index.html” # Strip trailing newline, if we have one if (FilePath[-1]==”\n”): FilePath=FilePath[:-1] # Create subdirectories as necessary. (Directory,FileName)=os.path.split(FilePath) try: os.makedirs(Directory) # make directories as needed except: # os.makedirs raises an exception if the directory exists. # We ignore the exception. pass LocalPath = os.path.normpath(FilePath) urllib.urlretrieve(NextURL,FilePath) def LogError(self,URL): print “Error retrieving URL:”,URL # Quick-and-dirty error logging: This code prints the # stack-trace that you see normally when an unhandled # exception crashes your script. (ErrorType,ErrorValue,ErrorTB)=sys.exc_info() print “\n\n***ERROR:” print sys.exc_info() traceback.print_exc(ErrorTB) # Main function if __name__ == ‘__main__’: # Open the URL-list file. Take the first command-line # argument, or just use the hard-coded name. if (len(sys.argv)>=2): URLFileName = sys.argv[1] else: URLFileName=URL_FILE_NAME try: URLFile = open(URLFileName) URLList = URLFile.readlines() URLFile.close() except: print “Error reading URLs from:”,URLFileName sys.exit() # Create some worker threads, and start them running URLListLock = threading.Lock() WorkerThreadList = for X in range(0,WORKER_COUNT): NewThread = WorkerThread(URLList,URLListLock) NewThread.setName(X) WorkerThreadList.append(NewThread) # call start() to spawn a new thread (not run()!) NewThread.start() # Wait for each worker in turn, then exit. # join() is the “vulture method” - it waits until the thread dies for X in range(0,WORKER_COUNT): WorkerThreadList[X].join() 491 4807-7 ch26.F 492 5/24/01 9:01 AM Page 492 Part V ✦ Advanced Python Programming Listing 26-2: URLGrabber — thread version # # # # # # # # # # URLGrabber retrieves a list of target files from the network to the local disk. Each file has a particular URL, indicating where and how we should request it. Several threads run in parallel, each downloading one file at once. Multithreading makes the whole process faster, since thread A can receive data while thread B is waiting on the server. This version of URLGrabber uses the thread module. It uses a lock to limit access to the URLList. (Without this lock, two threads might both grab the same URL) import import import import import import thread urllib urlparse os sys traceback # The optimal number of worker threads depends on one’s bandwidth WORKER_COUNT = 4 # Default filename of our url list URL_FILE_NAME = “MyURLList.txt” “”” A WorkerThread downloads files from URLs to disk. Each WorkerThread object corresponds to a single flow of control. “”” class WorkerThread: def __init__(self, URLList, URLListLock): # Cache references... self.URLList=URLList self.URLListLock = URLListLock “”” Acquire the URLList lock, grab the first URL from the list, cross the URL off the list, and release the URLList lock. (This code could be part of run(), but it’s good to put critical sections in their own function) “”” def GrabNextURL(self): self.URLListLock.acquire(1) # 1 means we block if (len(self.URLList)<1): NextURL=None else: NextURL=self.URLList[0] del self.URLList[0] self.URLListLock.release() return NextURL “”” run() is the target-function of our worker threads “”” def run(self): IncrementThreadCount() while (1): NextURL = self.GrabNextURL() 4807-7 ch26.F 5/24/01 9:01 AM Page 493 Chapter 26 ✦ Multithreading if (NextURL==None): # The URL list is empty! Exit the loop. break try: self.RetrieveURL(NextURL) except: self.LogError(NextURL) DecrementThreadCount() def StartFirstWorker(self): MainThreadLock.acquire(1) self.run() def RetrieveURL(self,NextURL): # urlparse splits a URL into pieces; # piece #2 is the file path FilePath=urlparse.urlparse(NextURL)[2] FilePath=FilePath[1:] # strip leading slash # If file name is blank, invent a name if (FilePath==””): FilePath=”index.html” # Strip trailing newline, if we have one if (FilePath[-1]==”\n”): FilePath=FilePath[:-1] # Create subdirectories as necessary. (Directory,FileName)=os.path.split(FilePath) try: os.makedirs(Directory) # make directories as needed except: # os.makedirs raises an exception if the directory exists. # We ignore the exception. pass LocalPath = os.path.normpath(FilePath) urllib.urlretrieve(NextURL,FilePath) def LogError(self,URL): print “Error retrieving URL:”,URL # Quick-and-dirty error logging: This code prints the # stack-trace that you see normally when an unhandled # exception crashes your script. (ErrorType,ErrorValue,ErrorTB)=sys.exc_info() print “\n\n***ERROR:” print sys.exc_info() traceback.print_exc(ErrorTB) def DecrementThreadCount(): ThreadCountLock.acquire() global WorkerThreadCount WorkerThreadCount = WorkerThreadCount - 1 if (WorkerThreadCount<1): MainThreadLock.release() ThreadCountLock.release() def IncrementThreadCount(): ThreadCountLock.acquire() global WorkerThreadCount WorkerThreadCount = WorkerThreadCount + 1 Continued 493 4807-7 ch26.F 494 5/24/01 9:01 AM Page 494 Part V ✦ Advanced Python Programming Listing 26-2 (continued) ThreadCountLock.release() # Main function if __name__ == ‘__main__’: # Open the URL-list file. Take the first command-line # argument, or just use the hard-coded name. if (len(sys.argv)>=2): URLFileName = sys.argv[1] else: URLFileName=URL_FILE_NAME try: URLFile = open(URLFileName) URLList = URLFile.readlines() URLFile.close() except: print “Error reading URLs from:”,URLFileName sys.exit() # Create some worker threads, and start them running URLListLock = thread.allocate_lock() ThreadCountLock = thread.allocate_lock() # We acquire the MainThreadLock. The last worker thread to exit # releases the lock, so that we can acquire it again (and exit) MainThreadLock = thread.allocate_lock() MainThreadLock.acquire() WorkerThreadCount = 0 for X in range(0,WORKER_COUNT): NewThread = WorkerThread(URLList,URLListLock) thread.start_new_thread(NewThread.run,()) # This call will block until the last thread releases the main # thread lock in DecrementThreadCount(). MainThreadLock.acquire() Porting Threaded Code Not all operating systems include support for multithreading — an OS may multitask without including native thread support. Note some minor differences in how threading works on different platforms: ✦ On most platforms, child threads are immediately killed (without executing object destructors or try...finally clauses) when the main thread exits. However, child threads keep running on SGI IRIX. We recommend terminating all threads before the main thread exits anyway, to ensure proper cleanup. ✦ Signals generally go to the main thread. Therefore, if your script handles signals, the main thread should not block. In particular, if you are using Tkinter, you should run mainloop() from the main thread. However, on platforms where the signal module is not available, signals go to an arbitrary thread. 4807-7 ch26.F 5/24/01 9:01 AM Page 495 Chapter 26 ✦ Multithreading Weaving Threads Together with Queues The Queue module defines a thread-safe queue class (Queue.Queue). A queue is similar to a list. A queue handles concurrency control internally, which saves you the bother of handling it in your code. Call the constructor Queue.Queue(maxsize) to create a queue. If maxsize is greater than zero, the queue will be limited to that many elements; otherwise, the length of the queue is unlimited. To add an item to the queue, call put(item, block). The method get(block), returns the next item in the queue. Setting block to 1 makes these methods wait until they can successfully add or retrieve an item. Setting block to 0 causes get and put to return immediately. You can also use the synonym methods get_nowait(item) and put_nowait(item). A nonblocking call to put raises the exception Queue.Full if the queue is full. (If the queue’s length is not limited, put will always succeed.) A nonblocking call to get raises the exception Queue.Empty if no items are on the queue. The Queue class includes some methods to inspect the queue. qsize() returns the queue length. isEmpty() returns 1 if the queue is empty, and 0 otherwise. isFull() returns 1 if the queue is full, and 0 if the queue is empty. Be careful: other threads may have touched the queue while you were inspecting it! Therefore, you must take the output of these methods with a grain of salt. For instance, the following code may raise a Queue.Empty exception: if (not MyQueue.isEmpty()): FirstItem = MyQueue.get() # unsafe! To safely modify a queue synchronously, use get_nowait() and put_nowait(), and catch any Full or Empty exceptions. Technical Note: How Simultaneous Is Simultaneous? A CPU can only handle one flow of control at a time. Computers switch between processes quickly, so in a single second, a processor may execute some instructions for thread A and thread B. To the user, the threads appear to run at the same time. We say that these programs are “simultaneous,” although they are actually taking turns. On a multiprocessor machine, threads can be literally simultaneous — CPU 1 is running program A at the same instant that CPU 2 is running program B. 495 4807-7 ch26.F 496 5/24/01 9:01 AM Page 496 Part V ✦ Advanced Python Programming Currently, Python maintains a global interpreter lock, so that it executes only one Python thread at once. The disadvantage here is that a multiprocessor machine can devote only one processor to a particular Python program. This limitation doesn’t matter much (especially if you’re using a single processor machine!), but you may want to work around it for performance reasons. A C extension can create parallel dummy threads, as long as those threads do not manipulate Python objects directly. Alternatively, you can run separate processes if your program’s work can be cleanly split. For More Information The Python threading SIG is a group working to document and improve the state of threading in Python; mailing list archives are available. See the Python SIG page at http://www.python.org/sigs/. Stackless Python is an alternate implementation of the Python interpreter that supports, among other things, microthreads, or ultra-lightweight processes, which enables your program to handle hundreds or even thousands of threads without getting bogged down just switching between them. Visit www.stackless.org for more information. Summary Threads enable your programs to perform multiple tasks at once. Untamed threads can break one another’s data, but Python’s locking mechanisms let you direct threads to work together. In this chapter, you: ✦ Created threads with the thread and threading modules. ✦ Controlled data access with locks and semaphores. ✦ Built easy thread-safe code with the Queue class. In the next chapter, you’ll learn tools and techniques to help you debug and profile your Python applications. ✦ ✦ ✦ 4807-7 ch27.F 5/24/01 9:01 AM Page 497 27 CHAPTER Debugging, Profiling, and Optimization B ugs can surface in the best of code — often at the worst possible times. Fortunately, Python features a debugger to help squash bugs. You can also use Python’s profiler to identify bottlenecks in your code. A few optimization tricks can go a long way toward speeding up a sluggish script. Debugging Python Code Adding print statements is no substitute for stepping through code. The Python debugger, pdb, lets you set breakpoints, examine and set variables, and view source code. pdb is similar to the C/C++ debugger gdb (which, in turn, was based on xdb), so the gdb veterans in the audience will recognize most commands. Most commands can be written in a long way or a short way. For reference, this chapter lists them in the following form: Long way (abbreviation). For example: continue (c). A list of commands is also available within pdb by typing help (h). CrossReference See Appendix B for a guide to debugging under IDLE and PythonWin. Both provide excellent debuggers that are more powerful than pdb. Starting and stopping the debugger To use the debugger, import the module pdb. Then, you can start the debugger by calling pdb.run(statement[,globals[,locals]]). Here, statement is code to execute (as a string). You can run in a particular context by passing global and local namespace-dictionaries for globals and locals. The debugger will stop and wait for input before actually running the code; this is a handy time to set breakpoints: ✦ ✦ ✦ ✦ In This Chapter Debugging Python code Working with docstrings Automating tests Finding bottlenecks Common optimization tricks Taking out the trash — the Garbage Collector ✦ ✦ ✦ ✦ 4807-7 ch27.F 498 5/24/01 9:01 AM Page 498 Part V ✦ Advanced Python Programming >>> import pdb >>> pdb.run(“import DebugMe”) > C:\PYTHON20\<string>(0)?() (Pdb) print “I can execute arbitrary commands at this prompt!” I can execute arbitrary commands at this prompt! (Pdb) fred=25 (Pdb) fred 25 You can do whatever you want from the pdb prompt. However, it provides some useful special commands, described next. The function runeval is the same as run, except that runeval returns the value of the statement executed in the debugger. The function runcall(function[, arguments...]) executes the function function in the debugger, passing along any arguments to the function. It returns the return-value of function. The function post_mortem(traceback) enters post-mortem debugging of a particular traceback. The function pm starts debugging the most recent traceback; it is a synonym for post_mortem(sys.last_traceback). The function set_trace enters the debugger immediately. It is a useful function to put in code that encounters (or raises) an AssertionError. To get back out of the debugger, use the command quit (q). Examining the state of things The all-important command list (l) shows the source code you are debugging. Use list FirstLine LastLine to list a range of lines (by default, pdb shows up to five lines above and five lines below the current line). The command where (w) shows the current stack trace, while up (u) and down (d) move through the stack. (Note that running w under an IDLE shell shows about 10 extra stack frames, because IDLE is running above your code.) You can display a variable’s value with print (p). For example, here is a simple debugging session. Looking at the code, plus some variables in context, gives me a pretty good idea what went wrong: >>> FancyPrimeFinder.FindPrimes(100) Traceback (innermost last): File “<pyshell#19>”, line 1, in ? FancyPrimeFinder.FindPrimes(100) File “C:\PYTHON20\FancyPrimeFinder.py”, line 9, in FindPrimes NumList=filter(lambda y,x=NumList[Index]: 4807-7 ch27.F 5/24/01 9:01 AM Page 499 Chapter 27 ✦ Debugging, Profiling, and Optimization IndexError: list index out of range >>> import pdb >>> pdb.pm() # Post mortem! > C:\PYTHON20\FancyPrimeFinder.py(9)FindPrimes() -> NumList=filter(lambda y,x=NumList[Index]: (Pdb) l 4 NumList = range(2,EndNumber) 5 Index=0 6 while (Index<len(NumList)): 7 Index += 1 8 -> NumList=filter(lambda y,x=NumList[Index]: 9 (y<=x or y%x!=0), NumList) 10 return NumList [EOF] (Pdb) p NumList [2, 3, 4, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97] (Pdb) Index 26 (Pdb) p len(NumList) 26 (Pdb) p NumList[Index] *** IndexError: <exceptions.IndexError instance at 0098E714> Setting breakpoints The break (b) command handles breakpoints. You set breakpoints in two ways: break [name:]index sets a breakpoint on line index of file name. break function[, condition] sets a breakpoint on the specified function, but only when condition is true. Breakpoints are given sequential ID numbers, starting with 1. Running break (b) with no arguments prints a list of the current breakpoints: (Pdb) b (Pdb) b FancyPrimeFinder.py:9 Breakpoint 1 at C:\PYTHON20\FancyPrimeFinder.py:9 (Pdb) b Num Type Disp Enb Where 1 breakpoint keep yes at C:\PYTHON20\FancyPrimeFinder.py:9 Use clear (cl) to clear breakpoints. Pass their ID numbers, or just type cl to clear them all. Similarly, use disable to disable breakpoints. You can re-enable a breakpoint with enable (but a cleared breakpoint is gone forever). The command ignore id [count] ignores breakpoint id up to count times. The command tbreak, with the same arguments as break, sets a temporary breakpoint, which is automatically cleared the first time it is hit. Finally, the command condition id [expr] attaches the condition expr to breakpoint id; if expr is omitted, the breakpoint becomes unconditional. 499 4807-7 ch27.F 500 5/24/01 9:01 AM Page 500 Part V ✦ Advanced Python Programming Running The command continue (c) tells pdb to start running the program again. The command return (r) keeps running until the current function returns. The commands next (n) and step (s) execute only the current statement. The difference between the two is that step “steps into” functions (it breaks inside the function call), and next “steps over” function calls (it runs the whole function call, and then breaks on the next line of the current source file). Aliases The command alias [name [command]] creates an alias, name, which executes command. The alias can take arguments. These arguments replace %1, %2, and so on, in command, while %* is replaced by all the arguments. Calling alias without passing a command shows the current command for name; calling alias with no arguments lists the current aliases. Aliases can be nested. They only apply to the first word typed at the pdb command line. For example, here is an alias to print an object’s members, and a shortcut for printing the members of self: (Pdb) alias pi for k in %1.__dict__.keys(): print “%1.”+k+”=”+%1.__dict__[k] (Pdb) alias ps pi self (Pdb) pi TempFile TempFile.BackupFileName=C:\DOCUME~1\ADMINI~1\LOCALS~1\Temp\~3400-1 TempFile.File=<open file ‘fred.txt’, mode ‘w’ at 008053D8> TempFile.FileName=fred.txt You can put alias definitions (or any other pdb commands) into a file named .pdbrc in your home directory or the current directory. pdb will execute the commands from .pdbrc on startup. If .pdbrc files exist in your home directory and the current directory, the home directory’s .pdbrc executes first, followed by the local file. Debugging tips Bugs in destructors can be especially hard to track down. Any exceptions thrown in a destructor are spewed to stderr and ignored. Therefore, destructors are a great place to call pdb.set_trace: def __del__(self): try: self.cleanup() except: # If we don’t catch it, NO ONE CAN! pdb.set_trace() 4807-7 ch27.F 5/24/01 9:01 AM Page 501 Chapter 27 ✦ Debugging, Profiling, and Optimization If an object is still around when the program finishes running, its destructor may execute after the Python interpreter has freed any imported modules. Therefore, an innocent-looking call to os.remove may result in the error “‘None’ object has no attribute ‘remove’”. A trick that sometimes works is to prefix a module-level variable with an underscore; such items are destroyed before other members. Safest of all is not to do anything too clever in destructors, unless you carefully get rid of objects as you go. Working with docstrings Documentation helps people use each other’s Python modules. But documentation often becomes out-of-date, which is sometimes worse than no documentation at all! By using docstrings, you can maintain code and documentation in one place. You can also use the pydoc module to extract your code’s docstrings into professionallooking text or HTML documentation, so that people can use your modules without ever needing to read code. You can use pydoc interactively. Call pydoc.help(object) to view Python documentation for an object. This can be much more convenient than leaving the interpreter to read documentation. For example: >>> pydoc.help(string.strip) Help on function strip in module string: strip(s) strip(s) -> string Return a copy of the string s with leading and trailing whitespace removed. You can also use pydoc from the command line. To view module documentation as text, pass the module name as an argument, like this: python pydoc.py urllib Or, use the -w argument to write out documentation to an HTML file. For example, this commend writes HTML documentation of urllib to the file urllib.html: python pydoc.py -w urllib The pydoc module has one more trick up its sleeve: Run it with no command line arguments, and it will run as a documentation Web server. You can read documentation for all the modules in your PYTHONPATH, all from the comfort of your browser! New Feature The pydoc module is new in Python 2.1. (However, it runs on versions 1.5 and up.) 501 4807-7 ch27.F 502 5/24/01 9:01 AM Page 502 Part V ✦ Advanced Python Programming Automating Tests Testing code is not as fun as writing code. But testing is essential to avoid poorquality code. Luckily, Python comes with tools to help you build automated tests. The unittest module (also known as PyUnit) is a framework for testing your code. The doctest module helps you keep documentation and code in synch. New Feature Both doctest and unittest are new in Python 2.1. Synching docstrings with code The doctest module helps you defend against out-of-date documentation. To use doctest, copy the text of a successful interpreter session and then paste it into your code’s docstrings. Later, run doctest.testmod(module) to re-run that interpreter session, and make sure that the output is the same. For example, suppose I am parsing some comma-delimited files that I exported from Microsoft Excel. Normally, I could use string.split to split a line into fields. But Excel uses some special rules to deal with commas within data. So, I write a function called SplitCommaFields to split fields, and test it in the interpreter. It works — so far, so good. To make sure my code’s documentation doesn’t become out-of-date, I copy my interpreter session into the docstring. Listing 27-1 shows the resulting file: Listing 27-1: CSV.py import doctest import CSV # Import ourselves! def SplitCommaFields(Line): “”” SplitCommaFields breaks up a comma-delimited .csv file into fields: >>> SplitCommaFields(‘a,b,c’) [‘a’, ‘b’, ‘c’] It handles commas within fields: >>> SplitCommaFields(‘Atlas shrugged,”Rand,Ayn”,1957’) [‘Atlas shrugged’, ‘Rand,Ayn’, ‘1957’] Also, it handles double-quotes within fields: >>> SplitCommaFields(‘“Are “”you”” happy?”,”Stuff,is,fun”’) [‘Are “you” happy?’, ‘Stuff,is,fun’] “”” Fields=Line.split(“,”) RealFields= InsideQuotes=0 BigField=”” 4807-7 ch27.F 5/24/01 9:01 AM Page 503 Chapter 27 ✦ Debugging, Profiling, and Optimization for Field in Fields: if InsideQuotes: BigField+=”,”+Field if BigField[-1]==’”’: BigField=BigField[:-1] # kill trailing “ RealFields.append(BigField) InsideQuotes=0 elif len(Field)==0 or Field[0]!=’”’: RealFields.append(Field) else: # we saw a start-quote if (Field[-1]==’”’): RealFields.append(Field[1:-1]) else: BigField=Field[1:] InsideQuotes=1 return map(lambda x:x.replace(‘“”’,’”’), RealFields) if __name__==”__main__”: doctest.testmod(CSV) # Test this module When I run CSV.py from the command line, I get no output, indicating that my function still runs as documented. As a sanity check, I can pass the -v argument to see doctest do its work: C:\source\test>python CSV.py -v Running CSV.__doc__ 0 of 0 examples failed in CSV.__doc__ Running CSV.SplitCommaFields.__doc__ Trying: SplitCommaFields(‘Atlas shrugged,”Rand,Ayn”,1957’) Expecting: [‘Atlas shrugged’, ‘Rand,Ayn’, ‘1957’] ok [...deleted for brevity...] 3 passed and 0 failed. Test passed. Unit testing The unittest module is a Python version of Kent Beck’s unit testing framework. It belongs to the same illustrious lineage as JUnit and CppUnit. You can use it to build one or more test cases for a class or module and group test cases into test suites. To build an automated test, create a subclass of unittest.TestCase. Your class should override the runTest method to perform some test, using the assert to flag errors. For example, this class tests the SplitCommaFields function defined earlier: 503 4807-7 ch27.F 504 5/24/01 9:01 AM Page 504 Part V ✦ Advanced Python Programming class CommaContentsTestCase(unittest.TestCase): def runTest(self): Line=’one,two,”three,three,thr,ee”,”fo,ur”,five’ assert SplitCommaFields(Line)==\ [‘one’,’two’,’three,three,thr,ee’,’fo,ur’,’five’] You can run the test interactively by calling the run method of a TestRunner object, such as the TextTestRunner: >>> TestRunner=unittest.TextTestRunner() >>> TestRunner.run(CSV.CommaContentsTestCase()) . --------------------------------------------------------------Ran 1 tests in 0.000s OK <unittest._TextTestResult run=1 errors=0 failures=0> You can also run tests from the command line. One method is to change your script to call unittest.main(): if __name__==”__main__”: unittest.main() Then, calling your script from the command line will run all its test cases. Test suites The TestSuite class is a handy way to group related test cases. It provides a method, addTest(TestCase), for adding test cases to a list. For example, this function returns a suite of test cases: def CSVSuite(): Suite=unittest.TestSuite() Suite.add(CommaContentsTestCase()) Suite.add(QuoteCommentsTestCase()) return Suite If you define a function (such as CSVSuite previously) to return a TestCase or TestSuite object, you can invoke your unit test(s) from the command line like this: python unittest.py CSV.CSVSuite Repeated testing tasks The TestCase class provides setUp and tearDown methods, called before and after the main runTest method. These methods help you build test cases without repeating the same setup and cleanup steps in your test code. For example, suppose you have several tests that must create a temporary file. This base class takes 4807-7 ch27.F 5/24/01 9:01 AM Page 505 Chapter 27 ✦ Debugging, Profiling, and Optimization care of file creation and cleanup, so that your test cases can freely write to self.File in the runTest method: class FileTestCase(unittest.TestCase): def setUp(self): self.FileName=tempfile.mktemp() self.File=open(self.FileName,”w”) def tearDown(self): self.File.close() os.remove(self.FileName) Finding Bottlenecks Python is a high-level language, often used in situations where speed is not crucial. Programmer time is usually more expensive than processor time. However, it is sometimes important to optimize your Python program — to make them conserve time, memory, or some other resource, such as database cursors. Note some rules of thumb for optimization: 1. Optimize last. Life is too short to spend time optimizing code that may be rewritten or scrapped. 2. Test your optimizations by timing them on realistic runs. Optimization often means some sacrifice of simplicity, readability, or maintainability; it’s best to make sure the sacrifice is worth the gains. 3. Comment all but the most glaringly obvious optimizations. This helps innocent bystanders understand your code, and (it is hoped) ensures that no one will undo the optimizations for the sake of readability. Profiling code To quickly profile a statement, import the profile module, and then call profile.run(statement). For example, the following code profiles a script that sorts MP3 files by artist: >>> profile.run(“SortMP3s()”) 30289 function calls (30166 primitive calls) in 10.560 CPU seconds Ordered by: standard name ncalls 1 271 tottime 0.029 0.020 percall 0.029 0.000 cumtime 9.685 0.020 percall filename:lineno(function) 9.685 <string>:1(?) 0.000 ID3Tag.py:105(__init__) 505 4807-7 ch27.F 506 5/24/01 9:01 AM Page 506 Part V ✦ Advanced Python Programming 9 0.000 0.000 9 0.000 0.000 1 0.292 0.292 1 0.000 0.000 271 0.151 0.001 45 0.016 0.000 [...truncated for brevity...] 0.000 0.000 0.704 0.000 0.168 0.016 0.000 0.000 0.704 0.000 0.001 0.000 ID3Tag.py:130(theTitle) ID3Tag.py:137(theArtist) ID3Tag.py:20(?) ID3Tag.py:23(ID3Tag) ID3Tag.py:304(Read) ID3Tag.py:333(RemovePadding) Each line of the output corresponds to a function. The columns show the following: ✦ ncalls — How many times the function was called. If a function recurses, two numbers are shown: total calls, and then total primitive calls. For instance, the script made one call to os.path.walk, which resulted in 123 other calls: 124/1 0.500 0.004 8.862 8.862 ntpath.py:255(walk) ✦ tottime — Total CPU time spent in the function. ✦ percall — Average CPU time. Equal to tottime divided by ncalls. ✦ cumtime — Cumulative CPU time spent in the function and its subfunctions. ✦ percall — Average cumulative time. Equal to cumtime divided by ncalls. ✦ filename:lineno(function) — Source file name, line number, and function name. The first line of output corresponds to the code passed to run; its filename is listed as “<string>”. Note When profiling from a Python shell window in IDLE or PythonWin, any code that prints to stdout will trigger function calls within the IDE’s framework. These function calls will show up in the profiler’s output! Running Python from the command line works around this problem. Using Profile objects The Profile class provides a run(command) method to profile the specified command. Normally, the command runs in the current namespace. To run the command in a particular namespace context, pass the global and local dictionaries (as returned by built-in functions globals and locals) to runctx(command, globals, locals). To profile a function call, you can call runcall(functionname[,arguments...]). After running a command, call the print_stats method to print statistics, or the dump_stats(filename) to write out stats (in nonreadable format) to the specified file. A call to profile.run(command[,filename]) creates a Profile object, calls run(command), and then calls either print_stats or dump_stats(filename). The Profile class can be subclassed. For example, the class HotProfile is a subclass of Profile. It calculates less data (ignores caller-callee relationships), but runs faster. 4807-7 ch27.F 5/24/01 9:01 AM Page 507 Chapter 27 ✦ Debugging, Profiling, and Optimization Calibrating the profiler There is a small time lag between the time that an event happens and the time that profiler records. The call to time.clock is not free. This lag adds up over the course of many function calls, and can make timing information less accurate. Calibrating the profiler compensates for this lag by adding a “fudge factor.” This makes the profiler’s statistics more accurate. To calibrate the profiler, call its calibrate method: >>> import profile >>> Prof=profile.Profile() >>> “%f” % Prof.calibrate(100000) ‘0.000017’ The number returned is your fudge factor. To use it, you must edit the library code (in lib\profile.py). In the trace_dispatch method, replace the line t = t[0] + t[1] - self.t # No Calibration constant with this line: t = t[0] + t[1] - self.t - (your calibration constant) Note Profiling with calibration is more accurate overall. However, the profiler may occasionally report that a negative amount of time was spent in a function. This results from the imperfection of the fudge factor, and is not a cause for panic. Customizing statistics The module pstats provides a class, Stats, for storing and printing statistics gathered in a profiling run. The Stats constructor takes either a file name or a Profile object. You can either pass in a Profile object (after calling run), or pass the name of a stats file created by the profiler. You can also pass one (or more) file names or Profile instances to Stats.add. For example, the following code runs the same command several times, and combines the statistics, on the assumption that behavior may vary from one run to the next: def ProfileSeveralRuns(Command,Times): if (Times<1): return StatsFiles= for RunIndex in range(Times): FileName=”stats%d”%(RunIndex) profile.run(Command, FileName) 507 4807-7 ch27.F 508 5/24/01 9:01 AM Page 508 Part V ✦ Advanced Python Programming StatsFiles.append(FileName) # Pass one filename to the constructor: AggregateStats=pstats.Stats(StatsFiles[0]) # Pass along all other filenames: if len(StatsFiles)>1: AggregateStats.add(*(StatsFiles[1:])) AggregateStats.print_stats() It is generally a good idea to call strip_dirs to trim the path to each function’s file name. You can change the ordering of statistics by calling the method sort_stats (field[,...]). Here, field is the name of a field to sort on. You can pass several field names. In this case, subsequent fields are used to sort if values of the first field are equal. Alphabetic fields are sorted in ascending order; numeric fields are sorted in descending order. (The method reverse_order reverses the ordering.) Table 27-1 lists the available fields. Table 27-1 Stats Field Names Name Meaning cumulative Cumulative time spent in a function calls Total calls to a function time Time spent in a function (not including subfunctions) name Function name file Source filename module Source filename (same meaning as file) line Source line number nfl Name/File/Line. sort_stats(“nfl”) is the same as sort_stats(“name”,”file”,”line”) pcalls Total primitive (nonrecursive) calls to a function stdname Standard name The method print_stats([restrictions...]) prints the statistics. You can pass one or more arguments to filter which lines are printed. Pass an integer, n, to print only the first n lines. Pass a decimal between 0 and 1 to print that percentage of the lines. Or, pass a regular expression (as a string) to print only lines whose file name matches the regular expression. 4807-7 ch27.F 5/24/01 9:01 AM Page 509 Chapter 27 ✦ Debugging, Profiling, and Optimization This example runs some code and then prints statistics for the most timeconsuming functions: >>> Prof=profile.Profile() >>> Prof.run(“import FancyPrimeFinder”) <profile.Profile instance at 00854E54> >>> MyStats=pstats.Stats(Prof) >>> MyStats.sort_stats(“time”) # expensive functions first <pstats.Stats instance at 007E48DC> >>> MyStats.strip_dirs().print_Stats(10) # top 10 only Note that most methods of Profile and Stats return the object itself; this makes it easy to chain several method calls in one line, as the last line of the preceding code does. The method print_callers([restrictions...]) shows all the callers for each function. On the left is the called function; on the right is its caller, with the number of calls in parentheses. Similarly, print_callees([restrictions...]) shows each function on the left column; functions it called are on the right. Common Optimization Tricks The following sections outline some ways to speed up Python code. Use these on bottleneck code, after you have identified the bottlenecks using the profile module. Keep in mind that sometimes the best way to speed up a function is simply to write it as an extension module in C. CrossReference See Chapter 29 for more information about how you can create C libraries usable from your Python programs. Sorting Sorting a sequence with the sort method is very fast for numbers and strings. If you need to perform custom sorting (e.g., a comparison of two objects), you can pass a comparison function to sort. You can also customize sorting for a class by defining a __cmp__ method. However, passing a function to sort is faster than implicit use of the __cmp__ method. Compare the following two lines: PointList.sort(Point) # Uses Point.__cmp__ implicitly PointList.sort(Point.__cmp__) # Trickier, but faster! When sorting a list of objects, one trick is to find a “key” that you can sort on. The key values should be an easy-to-sort type (for example, numbers); and they should be mostly unique across list entries. The following function provides an example: 509 4807-7 ch27.F 510 5/24/01 9:01 AM Page 510 Part V ✦ Advanced Python Programming def SortByKey(List,KeyMaker): “””Sort a list. The parameter KeyMaker is a function that returns a key for the list element. The keys are used sort the list.””” # Replace each element x with (KeyMaker(x),x): TempList=map(lambda x,f=KeyMaker: (f(x),x), List) # Tuples sorted by comparing just the first elements: # If the first elements match, the second elements # are compared; so if KeyMaker(x)==KeyMaker(y), then we # *will* end up comparing x and y directly. TempList.sort() # Get rid of the keys - replace (KeyMaker(x),x) with x: return map(lambda(key,x):x, TempList) For instance, I wrote code to sort a list of points according to their distance from the origin. Using SortByKey (instead of passing a function to sort) made the code roughly three times faster. Looping Use xrange for looping across long ranges; it uses much less memory than range, and may save time as well. Both versions are likely to be faster than a while loop: for x in range(10000): pass # memory hog for x in xrange(10000): pass # good! You can often eliminate a loop by calling map instead. I/O Each call to a file’s readline method is quite slow. It is much faster to read the entire file into memory by calling readlines; however, this uses up a lot of RAM. Another approach is to read blocks of lines. Best of all — in Python 2.1 — is to use the xreadlines method of a file: # 1 - Slow: while 1: FileLine=file.readline() if (FileLine==””): break # EOF DoStuff(FileLine) # 2 - Fast, but possibly memory-intensive: FileLines=file.readlines() for FileLine in FileLines: DoStuff(FileLine) # 3 - Faster than 1, without hogging too much memory: # (Use this for filelike objects without an # xreadlines() method) while 1: FileLines=file.readlines(100) 4807-7 ch27.F 5/24/01 9:01 AM Page 511 Chapter 27 ✦ Debugging, Profiling, and Optimization if len(FileLines)==0: break # EOF for FileLine in FileLines: DoStuff(FileLine) # 4 - Fast and simple; requires version 2.1: for FileLine in file.xreadlines(): DoStuff(FileLine) Strings Building up strings with the concatenation operator + can be slow, because it often involves copying strings several times. Formatting using the % operator is generally faster, and uses less memory. For example: HTMLString=HTMLHeader+HTMLBody+HTMLFooter # slow! HTMLString=”%s%s%s”%(HTMLHeader,HTMLBody,HTMLFooter) # fast! If you are building up a string with an unknown number of components, consider using string.join to combine them all, instead of concatenating them as you go: # Slow way: Str=”” for X in range(10000): Str+=X # Fast way (10 times as fast on my machine): List= for X in range(10000): List.append(X) Str=string.join(List,””) When using regular expressions, create a reusable regular expression object using re.compile instead of re.search and re.match directly. This saves time, because the regular expression doesn’t have to be repeatedly parsed. Following is a contrived example: PATTERN=r”^[0-9]+(\.[0-9]+)*\$” # Match valid version numbers ValidDottedDecimal=re.compile(PATTERN) for Index in range(100): re.search(PATTERN,”2.4.5.3”) # slow way! for Index in range(100): ValidDottedDecimal.search(“2.4.5.3”) # fast way! Threads If your script uses only one thread, you can save time by forcing the interpreter to check for other threads less often. The method sys.setcheckinterval(codes) tells Python to consider switching threads after codes bytecodes. The default check-interval is 10; setting it to something large (like 1,000) may improve your performance. On my Windows machine, the gain is negligible. 511 4807-7 ch27.F 512 5/24/01 9:01 AM Page 512 Part V ✦ Advanced Python Programming Taking out the Trash — the Garbage Collector Python doesn’t require you to explicitly allocate and free memory. When you need more memory to hold some data, the Python interpreter allocates it for you. When you are finished with data, the interpreter usually gets rid of it. Python cleans up memory by using reference counting: For each chunk of memory you use, Python keeps track of how many references to the object exist. When you assign a reference to an object, its reference count increases; when you get rid of a reference, the object’s reference count decreases. When there are no more references to an object, Python frees the object’s memory: >>> class Thingy: ... def __init__(self,Name): ... self.Name=Name ... def __del__(self): ... print “Deleting:”,self.Name ... >>> A=Thingy(“X”) # The variable A holds only reference >>> A=”Crunchy frog” # Refcount goes to 0 -> object is freed! Deleting: X >>> A=Thingy(“X”) >>> B=Thingy(“Y”) >>> A.ref=B # Y’s Refcount goes from 1 to 2 >>> B=None # Y’s Refcount goes from 2 to 1 >>> # This takes X’s refcount to 0, so X is deleted. Deleting >>> # X takes Y’s refcount to 0, so Y is deleted too: >>> A=None Deleting: X Deleting: Y Note that the built-in function del does not (necessarily) delete an object; it deletes a variable (and thus decrements the object’s reference count): >>> >>> >>> >>> >>> ‘Y’ A=Thingy(“X”) B=Thingy(“Y”) A.ref=B del B # Variable B is gone, but object Y still exists A. ref.Name # See! Object Y is still there! Reference counts and Python code Reference counting is different from automatic garbage collection (as seen in Java). For example, as long as two objects hold references to each other, Python won’t free them. If an object is no longer usable by a program, but its memory is not freed, the object is leaked. Leaked memory normally gets cleaned up when the program terminates. However, a program that runs for a long time can leak many 4807-7 ch27.F 5/24/01 9:01 AM Page 513 Chapter 27 ✦ Debugging, Profiling, and Optimization megabytes of memory, a few bytes at a time. For example, after you run the following statements, the two objects each have a reference count of 1, and so will stick around until you exit the interpreter: >>> >>> >>> >>> >>> >>> >>> A=Thingy(“X”) B=Thingy(“Y”) A.ref=B # Y’s refcount is now 2 B.ref=A # X’s refcount is now 2 del A del B # Congratulations! You just leaked memory! Normally, these memory leaks are not big or common enough to worry about. If you find yourself running low on memory, however, you may need to start worrying. In order to rid yourself of an object, you must get rid of all references to it — and to do that, you must keep track of all the references. Reference counts and C/C++ code Shooting yourself in the foot is downright difficult in Python, but very easy in C. When writing C extensions, you must keep track of the reference counts of each Python object. Losing track of reference counts can lead to memory hemorrhaging (as opposed to mere memory leaks), and even core dumps. The macros Py_INCREF(x) and Py_DECREF(x) increment and decrement the reference counts of a Python object x. At any given time, each reference is considered to be owned by some function. When that function exits, it must transfer ownership of the reference, or else get rid of the reference with a call to Py_DECREF. A function can also borrow a reference — the borrower uses the reference, never touches the reference count, and lets go of the reference before the owner does. Owning and borrowing are not explicit in the code, but the comments generally indicate to whom a reference belongs. When writing C extensions, it is important to track reference counts properly. Linking Python with Py_REF_DEBUG and Py_TRACE_REFS turned on provides extra information for debugging reference counts. In addition, you can call _Py_PrintReferences to print out all the objects and their refcounts. Summary Debugging is never a painless process, but pdb helps make it as easy as possible. In addition, IDEs like PythonWin provide debugging with a snappier interface. The Python profiler helps you find bottlenecks in your code. In addition, a review of Python’s garbage collector can save a lot of memory. In this chapter, you: 513 4807-7 ch27.F 514 5/24/01 9:01 AM Page 514 Part V ✦ Advanced Python Programming ✦ Debugged Python programs using pdb. ✦ Profiled code to find the most expensive functions. ✦ Optimized various types of code. ✦ Learned how to leak memory (and how not to leak memory). In the next chapter, you learn how to combine the speed of C with the power of Python by writing C extensions. ✦ ✦ ✦ 4807-7 ch28.F 5/24/01 9:01 AM Page 515 28 CHAPTER Security and Encryption ✦ ✦ ✦ ✦ In This Chapter W ith the explosive growth of the Internet and with countries shifting to more global economies, the issue of security is increasingly important. Banks, businesses, governments, and consumers routinely transfer sensitive information; and computers attached to the Internet are potentially accessible by anyone. This chapter describes Python’s modules for creating digital fingerprints of messages, running Python code in a safe sandbox, and using basic encryption and decryption. Online, you can also find strong encryption extension modules for triple DES, Blowfish, and the like. Checking Passwords The most basic and common form of security is restricting access until the user enters a valid username and password. When you prompt a user for his or her password, however, you don’t want the password to be displayed on the screen, lest a “neighbor” with wandering eyes sees the password too. For these situations, use the getpass module. There really isn’t a safe and platform-independent way to have the user enter a password, so getpass has a different implementation for UNIX, Windows, and Macintosh systems. If for some reason it can’t use any of the special implementations, it will at least warn the user that the password might accidentally be displayed on the screen. Caution The Windows version uses getch() in the msvcrt module, which doesn’t behave quite how you’d expect in some IDEs, such as IDLE or PythonWin, so if you want to try getpass out, run it in an interpreter started on the command line. Checking passwords Running in a restricted environment Creating message fingerprints Using 1940s-era encryption ✦ ✦ ✦ ✦ 4807-7 ch28.F 516 5/24/01 9:01 AM Page 516 Part V ✦ Advanced Python Programming Use the getpass([prompt]) function to request the user’s password. The following function queries the user for a name and password and then returns them as a tuple: >>> import getpass >>> def getLogin(): ... name = raw_input(‘Name:’) ... passwd = getpass.getpass(‘Password:’) ... return name,passwd ... >>> getLogin() Name:robinhood Password: # Characters typed are not echoed (‘robinhood’, ‘littlejohn’) getpass also has the getuser() function, which returns the login name of the user: >>> getpass.getuser() ‘dave’ getuser checks the values of the LOGNAME, USER, LNAME, and USERNAME environ- ment variables, returning the value of the first one that is present and not empty. If all fail and the system has the pwd module (UNIX), then that is used; otherwise, an exception is raised. CrossReference Chapter 38 provides the pwd module, which you can use for accessing the UNIX user account database. You can also use the crypt module to check whether the password a user entered is correct (i.e., matches their login password). Most GUI toolkits have their own method for prompting a user for a password. For example, in wxPython, you can set a flag in the text entry field that holds a password, so that anything typed is displayed with asterisks. Note UNIX users that have the readline module activated need not worry that after entering their password it will show up in the command history. getpass uses its own implementation of raw_input in order to avoid that security hole. Running in a Restricted Environment Imagine that you decided to create an online game in which players from all over the world would upload virtual robots to traverse a maze and destroy one another. Not only did you decide to implement most of the game in Python, you chose to let the players program their robots using Python too. One problem, though, is that a malicious entrant could include code to erase files on your computer, install a Trojan horse, or cause damage in any number of other ways. How could you deal with that danger? 4807-7 ch28.F 5/24/01 9:01 AM Page 517 Chapter 28 ✦ Security and Encryption The rexec sandbox The rexec module helps prevent such a scenario. It enables you to run Python code in a sandbox, a restricted environment in which you control what resources it can access — just as a child in a sandbox imagines it to be the entire world when in reality it’s quite isolated and small. You can, for example, enable Python programs to do whatever they want as long as they don’t try to create any socket connections, or enable them to create files only in a particular directory. With rexec, you can more safely run Python programs that didn’t necessarily come from a trusted source. To create an execution sandbox, you call RExec([hooks][verbose]) to create an RExec object (or call the constructor of a subclass you’ve created in order to override or add to its access policies). hooks is an instance of the RHooks class (or a subclass), which is itself a subclass of the Hooks class in the ihooks module; and is what is called when it’s time to import a module. By providing your own import hooks, you can monitor or log what modules are loaded, or even load them from a different source. The verbose argument is passed to the Hooks constructor and, if 1, prints extra debugging information. CrossReference Refer to Chapter 34 for information about the ihooks module and implementing your own module import behavior. Before creating your RExec instance object, you can change some of its class variables to tailor what modules and functions will be available to the executing code. (Changing these class variables does not affect instances already created — only those subsequent to your changes will see the effects.) For security reasons, you should be careful about what values you change. If you want to change the list of prohibited built-in functions, for example, consider adding to the list instead of completely replacing it, so that you don’t inadvertently create a security hole. ok_path is a tuple containing the paths to search when importing a module. By default, it matches the value of sys.path. ok_builtin_modules is a tuple of built-in (not implemented in Python) modules that are safe to import. The default value contains the names of the following modules: audioop array binascii cmath errno imageop marshal math md5 operator parser regex pcre rotor select strop struct time ok_posix_names is a tuple of allowed functions from the os module (if present in the current platform’s implementation of os). The default value contains the names of the following modules: 517 4807-7 ch28.F 518 5/24/01 9:01 AM Page 518 Part V ✦ Advanced Python Programming error fstat listdir lstat readlink stat times uname getpid getppid getcwd getuid getgid geteuid getegid ok_sys_names is a tuple of variables and functions from the sys module that restricted access programs can use. The default value contains the following: ps1 ps2 copyright version platform exit maxint nok_builtin_names is a tuple of built-in function names that programs are not allowed to use. By default, the list contains ‘open’, ‘reload’, and ‘__import__’, so functions such as map are still allowed (most built-in functions are relatively safe). RExec intercepts calls from the restricted program to import, reload, and unload and routes the calls through the internal module loader and importer (which makes use of the custom import hooks). You can override RExec’s r_reload(module), r_unload(module), and r_import(modulename[, globals[, locals], fromlist]]]) methods to provide custom behavior. If a module isn’t safe to be loaded, r_import should raise in ImportError exception. Calls to open are sent to RExec’s r_open(filename[, mode[, bufsize]]). By default, files can be opened for reading only, but you can override this with different behavior if needed. Once you (finally!) have your RExec object, you can actually execute Python code in a restricted object by calling its r_eval(code), r_exec(code), or r_execfile(filename) methods, all of which run the code in the __main__ module of your new sandbox. r_eval takes as an argument either a Python expression as a string or a compiled code object, and returns the value of the expression: >>> import rexec >>> r = rexec.RExec() >>> r.r_eval(‘2 + 2’) 4 r_exec can take a string containing one or more lines of Python code or a compiled code object: >>> s = “”” ... print ‘My name is George’ ... q = range(10) ... print q ... “”” >>> r.r_exec(s) My name is George [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] 4807-7 ch28.F 5/24/01 9:01 AM Page 519 Chapter 28 ✦ Security and Encryption CrossReference Chapter 33 has information about code objects and Python introspection capabilities. r_execfile executes the contents of a Python file in the restricted environment. For example, first save the code in Listing 28-1 to a file called bad.py. Listing 28-1: bad.py — “Untrusted” code to test in the rexec sandbox SECRET_VIRUS_CODES = ‘...<bad stuff here>...’ f = open(‘cmd.exe’,’w+b’) # This will fail f.write(SECRET_VIRUS_CODES) f.close() RExec halts as soon as the program tries to do something illegal (in this case, open a file for writing). The RExec’s add_module(modulename) method returns a module object existing in the restricted environment (loading it first if necessary). Because __main__ is also a module, you can use this as a gateway between the normal and restricted environments. For example, you can have some variables already present when the restricted code runs: >>> >>> >>> >>> 20 r = rexec.RExec() rmain = r.add_module(‘__main__’) rmain.happyFactor = 10 r.r_eval(‘happyFactor * 2’) You can also use it to retrieve values after the code has finished. Continuing the previous example: >>> r.r_exec(‘sadFactor = happyFactor / 2’) >>> rmain.sadFactor 5 For each r_<func> method (such as r_eval and r_exec), RExec also has a corresponding s_<func> method that behaves similarly except that the s_<func> version will have access to restricted versions of stdin, stdout, and stderr. The restricted versions have the following methods: fileno flush isatty read readline readlines seek tell write writelines 519 4807-7 ch28.F 520 5/24/01 9:01 AM Page 520 Part V ✦ Advanced Python Programming Caution RExec handles some security problems for you, but there are other things to consider too. For example, nothing in RExec protects against code with an infinite loop, or even one that rapidly creates objects until it consumes all available memory. Using a class fortress Most classes were not designed with restricted execution in mind. By using the Bastion module, you can create wrappers for objects that are suitable for use with rexec. The wrapped version of the object has the same attributes as the original, but code in a restricted environment can access the attributes only if the wrapper allows it. Call Bastion(object[, filter[, name[, bastionclass]]]) to create a wrapper, where object is the object you wish to wrap. filter is a function that accepts an argument name and returns true if that attribute can be used (the default filter grants access to all attributes that do not start with an underscore). If the function returns 0, the wrapper will raise an AttributeError. The name argument is the name to use when printing the object; bastionclass is an alternate wrapper class to use, although you would rarely need to supply your own. As an example, suppose your robot game provides each robot with a reference to an Environment object through which the robot can query information about the “world” in which it is running (for example, number of robots still alive, amount of time left in the current round, and so on). The robots call different get methods, but outside the restricted environment, the rest of your program can set various world attributes via some set methods: class Environment: def __init__(self): self._robots = 0 self._timeLeft = 0 def SetNumRobots(self, num): self._robots = num def GetNumRobots(self): return self._robots def SetTimeLeft(self, left): self._timeLeft = left def GetTimeLeft(self): return self._timeLeft In order to make sure a player doesn’t fiddle with the time left in the game, for example, you can give the robots a “bastionified” version of the environment, one that doesn’t grant access to the ‘set’ methods: 4807-7 ch28.F 5/24/01 9:01 AM Page 521 Chapter 28 ✦ Security and Encryption def noPrivateOrSet(name): if name[:1] == ‘_’: return 0 if name[:3] == ‘set’: return 0 return 1 import Bastion, rexec e = Environment() be = Bastion.Bastion(e,noPrivateOrSet) Now your main code could make calls like the following: e.SetNumRobots(5) Code running in the restricted environment, however, could not. This next call would raise an AttributeError exception: r.r_exec(‘environment.SetTimeLeft(100)’) Caution As with access policies in rexec, the planning and consideration you use when designing a Bastion filter should be proportional to the damage that could occur if you leave a security hole open. It’s best to err on the side of being overly restrictive so that later you’re not sorry. Creating Mes