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

Chapter 9. Documentation – How to Use Sphinx and reStructuredText

Documenting code can be both fun and useful! I will admit that many programmers have a strong dislike for documenting code and understandably so. Writing documentation can be a boring job and traditionally only others reap the benefits of that effort. The tools available for Python, however, make it almost trivial to generate useful and up-to-date documentation with little to no effort at all. Generating documentation has actually become so easy that I create and generate documentation before using a Python package. Assuming it wasn't available already, that is.

In addition to simple text documentation explaining what a function does, it is also possible to add metadata, such as type hints. These type hints can be used to make the arguments and return types of a function or class clickable in the documentation. But more importantly, many modern IDEs and editors, such as VIM, have plugins available that parse the type hints...