Mark Summerfield - Python in Practice: Create Better Programs Using Concurrency, Libraries, and Patterns

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Create Better Programs Using Concurrency, Libraries, and Patterns

Mark Summerfield

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Library of Congress Control Number: 2013942956

Copyright 2014 Qtrac Ltd.

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ISBN-13: 978-0-321-90563-5
ISBN-10: 0-321-90563-6

Text printed in the United States on recycled paper at RR Donnelley in Crawfordsville, Indiana.
First printing, August 2013

This book is dedicated to free and open-source software contributors everywhereyour generosity benefits us all.

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I have been building software with Python for 15 years in various application areas. Over that time I have seen our community mature and grow considerably. We are long past the days of having to sell Python to our managers in order to be able to use it in work-related projects. Todays job market for Python programmers is strong. Attendance at Python-related conferences is at an all time high, for regional conferences as well as the big national and international events. Projects like OpenStack are pushing the language into new arenas and attracting new talent to the community at the same time. As a result of the robust and expanding community, we have more and better options for books about Python than ever before.

Mark Summerfield is well known in the Python community for his technical writing about Qt and Python. Another of Marks books, Programming in Python 3, is at the top of my short list of recommendations for learning Python, a question I am asked frequently as the organizer of the user group in Atlanta, Georgia. This new book will also go on my list, but for a somewhat different audience.

Most programming books fall at either end of a spectrum that ranges from basic introductions to a language (or programming in general) to more advanced books on very focused topics like web development, GUI applications, or bioinformatics. As I was writing The Python Standard Library by Example, I wanted to appeal to readers who fall into the gap between those extremesestablished programmers and generalists, both familiar with the language but who want to enhance their skills by going beyond the basics without being restricted to a specific application area. When my editor asked me to review the proposal for Marks book, I was pleased to see that Python in Practice is designed for the same types of readers.

It has been a long time since I have encountered an idea in a book that was immediately applicable to one of my own projects, without it being tied to a specific framework or library. For the past year I have been working on a system for metering OpenStack cloud services. Along the way, the team realized that the data we are collecting for billing could be useful for other purposes, like reporting and monitoring, so we designed the system to send it to multiple consumers by passing the samples through a pipeline of reusable transformations and publishers. At about the same time that the code for the pipeline was being finalized, I was also involved in the technical review for this book. After reading the first few sections of the draft for I immediately added a task to our roadmap to change the design during the next release cycle.

Python in Practice is full of similarly useful advice and examples to help you improve your craft. Generalists like me will find introductions to several interesting tools that may not have been encountered before. And whether you are already an experienced programmer or are making the transition out of the beginner phase of your career, this book will help you think about problems from different perspectives and give you techniques to create more effective solutions.

Doug Hellmann
Senior Developer, DreamHost
May 2013

This book is aimed at Python programmers who want to broaden and deepen their Python knowledge so that they can improve the quality, reliability, speed, maintainability, and usability of their Python programs. The book presents numerous practical examples and ideas for improved Python programming.

The book has four key themes: design patterns for coding elegance, improved processing speeds using concurrency and compiled Python (Cython), high-level networking, and graphics.