Brett Slatkin - Effective Python - 59 Specific Ways to Write Better Python (Effective Software Development) pdf
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Brett Slatkin - Effective Python - 59 Specific Ways to Write Better Python (Effective Software Development) pdf
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Brett Slatkin - Effective Python - 59 Specific Ways to Write Better Python (Effective Software Development).pdf -
12.27 MB
Description
“Each item in Slatkin’s Effective Python teaches a self-contained lesson with its own source code. This makes the book random-access: Items are easy to browse and study in whatever order the reader needs. I will be recommending Effective Python to students as an admirably compact source of mainstream advice on a very broad range of topics for the intermediate Python programmer.â€
—Brandon Rhodes, software engineer at Dropbox and chair of PyCon 2016-2017
It’s easy to start coding with Python, which is why the language is so popular. However, Python’s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up.
Effective Python will help you master a truly “Pythonic†approach to programming, harnessing Python’s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers’ best-selling Effective C++, Brett Slatkin brings together 59 Python best practices, tips, and shortcuts, and explains them with realistic code examples.
Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You’ll learn the best way to accomplish key tasks, so you can write code that’s easier to understand, maintain, and improve.
Key features include
Actionable guidelines for all major areas of Python 3.x and 2.x development, with detailed explanations and examples
Best practices for writing functions that clarify intention, promote reuse, and avoid bugs
Coverage of how to accurately express behaviors with classes and objects
Guidance on how to avoid pitfalls with metaclasses and dynamic attributes
More efficient approaches to concurrency and parallelism
Better techniques and idioms for using Python’s built-in modules
Tools and best practices for collaborative development
Solutions for debugging, testing, and optimization in order to improve quality and performance
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