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 5. Decorators – Enabling Code Reuse by Decorating

In this chapter, you are going to learn about Python decorators. Decorators are essentially function/class wrappers that can be used to modify the input, output, or even the function/class itself before executing it. This type of wrapping can just as easily be achieved by having a separate function that calls the inner function, or via mixins. As is the case with many Python constructs, decorators are not the only way to reach the goal but are definitely convenient in many cases.

While you can live perfectly without knowing too much about decorators, they give you a lot of "reuse power" and are therefore used heavily in framework libraries such as web frameworks. Python actually comes bundled with some useful decorators, most notably the property decorator.

There are, however, some particularities to take note of: wrapping a function creates a new function and makes it harder to reach the inner function and its properties. One example...