Book Image

Mastering Python

By : Rick van Hattem
Book Image

Mastering Python

By: Rick van Hattem

Overview of this book

Python is a dynamic programming language. It is known for its high readability and hence it is often the first language learned by new programmers. Python being multi-paradigm, it can be used to achieve the same thing in different ways and it is compatible across different platforms. Even if you find writing Python code easy, writing code that is efficient, easy to maintain, and reuse is not so straightforward. This book is an authoritative guide that will help you learn new advanced methods in a clear and contextualised way. It starts off by creating a project-specific environment using venv, introducing you to different Pythonic syntax and common pitfalls before moving on to cover the functional features in Python. It covers how to create different decorators, generators, and metaclasses. It also introduces you to functools.wraps and coroutines and how they work. Later on you will learn to use asyncio module for asynchronous clients and servers. You will also get familiar with different testing systems such as py.test, doctest, and unittest, and debugging tools such as Python debugger and faulthandler. You will learn to optimize application performance so that it works efficiently across multiple machines and Python versions. Finally, it will teach you how to access C functions with a simple Python call. By the end of the book, you will be able to write more advanced scripts and take on bigger challenges.
Table of Contents (22 chapters)
Mastering Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
6
Generators and Coroutines – Infinity, One Step at a Time
Index

Summary


This chapter showed us how to create generators and both the strengths and weaknesses that they possess. Additionally, it should now be clear how to work around their limitations and the implications of doing so.

While the paragraphs about coroutines should have provided some insights into what they are and how they can be used, not everything has been shown yet. We saw the constructs of both pure coroutines and coroutines that are generators at the same time, but they are still all synchronous. The coroutines allow sending the results to many other coroutines, therefore effectively executing many functions at once, but they can still freeze Python completely if an operation turns out to be blocking. That's where our next chapter will help.

Python 3.5 introduced a few useful features, such as the async and await statements. These make it possible to make coroutines fully asynchronous and non-blocking, whereas this chapter uses the basic coroutine features that have been available since...