Secret Recipes of the Python Ninja: Over 70 recipes that uncover powerful programming tactics in Python (pdf)

Description

Key Features

• Access built-in documentation tools and improve your code.
• Discover how to make the best use of decorator and generator functions
• Enhance speed and improve concurrency by conjuring tricks from the PyPy project

Book Description

This book covers the unexplored secrets of Python, delve into its depths, and uncover its mysteries.

You’ll unearth secrets related to the implementation of the standard library, by looking at how modules actually work. You’ll understand the implementation of collections, decimals, and fraction modules. If you haven’t used decorators, coroutines, and generator functions much before, as you make your way through the recipes, you’ll learn what you’ve been missing out on.

We’ll cover internal special methods in detail, so you understand what they are and how they can be used to improve the engineering decisions you make. Next, you’ll explore the CPython interpreter, which is a treasure trove of secret hacks that not many programmers are aware of. We’ll take you through the depths of the PyPy project, where you’ll come across several exciting ways that you can improve speed and concurrency.

Finally, we’ll take time to explore the PEPs of the latest versions to discover some interesting hacks.

What you will learn

• Know the differences between .py and .pyc files
• Explore the different ways to install and upgrade Python packages
• Understand the working of the PyPI module that enhances built-in decorators
• See how coroutines are different from generators and how they can simulate multithreading
• Grasp how the decimal module improves floating point numbers and their operations
• Standardize sub interpreters to improve concurrency
• Discover Python’s built-in docstring analyzer

Who this book is for

Whether you’ve been working with Python for a few years or you’re a seasoned programmer, you’ll have a lot of new tricks to walk away with.

Table of Contents

1. Working with Python Modules
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