Since 2008, the Python world has been watching the slow evolution of Python 3. It was always known that the adoption of Python 3 would likely take a long time. In fact, even at the time of this writing (2013), most working Python programmers continue to use Python 2 in production. A lot has been made about the fact that Python 3 is not backward compatible with past versions. To be sure, backward compatibility is an issue for anyone with an existing code base. However, if you shift your view toward the future, you’ll find that Python 3 offers much more than meets the eye.
Just as Python 3 is about the future, this edition of the Python Cookbook represents a major change over past editions. First and foremost, this is meant to be a very forward looking book. All of the recipes have been written and tested with Python 3.3 without regard to past Python versions or the “old way” of doing things. In fact, many of the recipes will only work with Python 3.3 and above. Doing so may be a calculated risk, but the ultimate goal is to write a book of recipes based on the most modern tools and idioms possible. It is hoped that the recipes can serve as a guide for people writing new code in Python 3 or those who hope to modernize existing code.
Needless to say, writing a book of recipes in this style presents a certain editorial challenge. An online search for Python recipes returns literally thousands of useful recipes on sites such as ActiveState’s Python recipes or Stack Overflow. However, most of these recipes are steeped in history and the past. Besides being written almost exclusively for Python 2, they often contain workarounds and hacks related to differences between old versions of Python (e.g., version 2.3 versus 2.4). Moreover, they often use outdated techniques that have simply become a built-in feature of Python 3.3. Finding recipes exclusively focused on Python 3 can be a bit more difficult.
Rather than attempting to seek out Python 3-specific recipes, the topics of this book are merely inspired by existing code and techniques. Using these ideas as a springboard, the writing is an original work that has been deliberately written with the most modern Python programming techniques possible. Thus, it can serve as a reference for anyone who wants to write their code in a modern style.
In choosing which recipes to include, there is a certain realization that it is simply impossible to write a book that covers every possible thing that someone might do with Python. Thus, a priority has been given to topics that focus on the core Python language as well as tasks that are common to a wide variety of application domains. In addition, many of the recipes aim to illustrate features that are new to Python 3 and more likely to be unknown to even experienced programmers using older versions. There is also a certain preference to recipes that illustrate a generally applicable programming technique (i.e., programming patterns) as opposed to those that narrowly try to address a very specific practical problem. Although certain third-party packages get coverage, a majority of the recipes focus on the core language and standard library.
This book is aimed at more experienced Python programmers who are looking to deepen their understanding of the language and modern programming idioms. Much of the material focuses on some of the more advanced techniques used by libraries, frameworks, and applications. Throughout the book, the recipes generally assume that the reader already has the necessary background to understand the topic at hand (e.g., general knowledge of computer science, data structures, complexity, systems programming, concurrency, C programming, etc.). Moreover, the recipes are often just skeletons that aim to provide essential information for getting started, but which require the reader to do more research to fill in the details. As such, it is assumed that the reader knows how to use search engines and Python’s excellent online documentation.
Many of the more advanced recipes will reward the reader’s patience with a much greater insight into how Python actually works under the covers. You will learn new tricks and techniques that can be applied to your own code.
This is not a book designed for beginners trying to learn Python for the first time. In fact, it already assumes that you know the basics that might be taught in a Python tutorial or more introductory book. This book is also not designed to serve as a quick reference manual (e.g., quickly looking up the functions in a specific module). Instead, the book aims to focus on specific programming topics, show possible solutions, and serve as a springboard for jumping into more advanced material you might find online or in a reference.
The following typographical conventions are used in this book:
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Almost all of the code examples in this book are available online at http://github.com/dabeaz/python-cookbook. The authors welcome bug fixes, improvements, and comments.
This book is here to help you get your job done. In general, if this book includes code examples, you may use the code in this book in your programs and documentation. You do not need to contact us for permission unless you’re reproducing a significant portion of the code. For example, writing a program that uses several chunks of code from this book does not require permission. Selling or distributing a CD-ROM of examples from O’Reilly books does require permission. Answering a question by citing this book and quoting example code does not require permission. Incorporating a significant amount of example code from this book into your product’s documentation does require permission.
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We would like to acknowledge the technical reviewers, Jake Vanderplas, Robert Kern, and Andrea Crotti, for their very helpful comments, as well as the general Python community for their support and encouragement. We would also like to thank the editors of the prior edition, Alex Martelli, Anna Ravenscroft, and David Ascher. Although this edition is newly written, the previous edition provided an initial framework for selecting the topics and recipes of interest. Last, but not least, we would like to thank readers of the early release editions for their comments and suggestions for improvement.
Writing a book is no small task. As such, I would like to thank my wife Paula and my two boys for their patience and support during this project. Much of the material in this book was derived from content I developed teaching Python-related training classes over the last six years. Thus, I’d like to thank all of the students who have taken my courses and ultimately made this book possible. I’d also like to thank Ned Batchelder, Travis Oliphant, Peter Wang, Brian Van de Ven, Hugo Shi, Raymond Hettinger, Michael Foord, and Daniel Klein for traveling to the four corners of the world to teach these courses while I stayed home in Chicago to work on this project. Meghan Blanchette and Rachel Roumeliotis of O’Reilly were also instrumental in seeing this project through to completion despite the drama of several false starts and unforeseen delays. Last, but not least, I’d like to thank the Python community for their continued support and putting up with my flights of diabolical fancy.
David M. Beazley
I would like to thank both my coauthor, David Beazley, as well as Meghan Blanchette and Rachel Roumeliotis of O’Reilly, for working with me on this project. I would also like to thank my amazing wife, Natasha, for her patience and encouragement in this project, and her support in all of my ambitions. Most of all, I’d like to thank the Python community at large. Though I have contributed to the support of various open source projects, languages, clubs, and the like, no work has been so gratifying and rewarding as that which has been in the service of the Python community.
Brian K. Jones