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Secret Recipes of the Python Ninja

You're reading from   Secret Recipes of the Python Ninja Over 70 recipes that uncover powerful programming tactics in Python

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788294874
Length 380 pages
Edition 1st Edition
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Author (1):
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Cody Jackson Cody Jackson
Author Profile Icon Cody Jackson
Cody Jackson
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Table of Contents (11) Chapters Close

Preface 1. Working with Python Modules FREE CHAPTER 2. Utilizing the Python Interpreter 3. Working with Decorators 4. Using Python Collections 5. Generators, Coroutines, and Parallel Processing 6. Working with Python's Math Module 7. Improving Python Performance with PyPy 8. Python Enhancement Proposals 9. Documenting with LyX 10. Other Books You May Enjoy

Preface

Many readers might feel that they have mastered the Python language and know everything it takes to write applications that utilize the best features of the language. This book aims to delve into aspects of Python and related technology that some developers have never experienced.

The book will unveil little-known or misunderstood aspects of Python related to the implementation of the standard library and provide understanding of how the modules actually work. The book shows the proper implementation of collections and the math module, along with numbers such as decimals and fractions that will help readers expand their horizons. Readers will learn about decorators, context managers, coroutines, and generator functions before learning about internal special methods in detail. The book explores the CPython interpreter, covering command options that can change how the environment functions as well as alternative interactive shells that improve on the normal Python experience. Readers will take a tour of the PyPy project, where they will be exposed to several new ways to improve speed and concurrency of their applications. Several Python Enhancement Proposals of the latest versions are reviewed to see what will be coming in the future of Python. Finally, it provides information on the different ways to document Python code.

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