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Mastering Python 2E

Mastering Python 2E - Second Edition

By : Rick Hattem
4.6 (65)
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Mastering Python 2E

Mastering Python 2E

4.6 (65)
By: Rick Hattem

Overview of this book

Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python’s capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code’s performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges
Table of Contents (21 chapters)
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19
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20
Index

Pythonic Design Patterns

The previous chapter covered a lot of guidelines for what to do and what to avoid in Python. Next, we will explore a few examples of how to work in a Pythonic way using the modules included with Python.

Design patterns are largely dependent on storing data; for this, Python comes bundled with several very useful collections. The most basic collections such as list, tuple, set, and dict will already be familiar to you, but Python also comes bundled with more advanced collections. Most of these simply combine the basic types for more powerful features. In this chapter, I will explain how to use these data types and collections in a Pythonic fashion.

Before we can properly discuss data structures and related performance, a basic understanding of time complexity (and specifically the big O notation) is required. The concept is really simple, but without it, I cannot easily explain the performance characteristics of operations and why seemingly nice-looking...

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Mastering Python 2E
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