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

Decorating class functions


Decorating class functions is very similar to regular functions, but you need to be aware of the required first argument, self—the class instance. You have most likely already used a few class function decorators. The classmethod, staticmethod, and property decorators for example, are used in many different projects. To explain how all this works, we will build our own versions of the classmethod, staticmethod, and property decorators. First, let's look at a simple decorator for class functions to show the difference from regular decorators:

>>> import functools


>>> def plus_one(function):
...     @functools.wraps(function)
...     def _plus_one(self, n):
...         return function(self, n + 1)
...     return _plus_one


>>> class Spam(object):
...     @plus_one
...     def get_eggs(self, n=2):
...         return n * 'eggs'


>>> spam = Spam()
>>> spam.get_eggs(3)
'eggseggseggseggs'

As is the case with regular functions...