Book Image

Secret Recipes of the Python Ninja

Book Image

Secret Recipes of the Python Ninja

Overview of this book

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.
Table of Contents (17 chapters)
Title Page
Copyright and Credits
Packt Upsell
Foreword
Contributors
Preface
Index

Simulating multithreading with coroutines


Where generators can generate data from a function via yield, they can also be used to accept data if they are used on the right-hand side of the = sign in a variable assignment. This creates a coroutine.

A coroutine is a type of function that can suspend and resume execution, via yield, at predefined locations within its code. In addition to yield(), coroutines also have send() and close() functions for processing data. The send() function passes data to a coroutine (the acceptance part of the function) and close() terminates the coroutine (as there is no way for garbage collection to inherently close it for us).

Using the asyncio module allows coroutines to be used to write single-threaded, concurrent programs. As they are single-threaded, they still only perform one job but the concurrency simulates multithreading. More information about concurrency and parallel programming can be found in the next section, When to use parallel processing.

How to...