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

Mock objects


When writing tests, this regularly occurs: you are testing not only your own code but also the interaction with external resources, such as hardware, databases, web hosts, servers, and others. Some of these can be run safely, but certain tests are too slow, too dangerous, or even impossible to run. In those cases, mock objects are your friends; they can be used to fake anything, so you can be certain that your code still returns the expected results without having any variation from external factors.

Using unittest.mock

The unittest.mock library provides two base objects, Mock and MagicMock, to easily mock any external resources. The Mock object is just a general generic mock object and MagicMock is mostly the same, but it has all the magic methods such as __contains__ and __len__ defined. In addition to this, it can make your life even easier. This is because in addition to creating mock objects manually, it is possible to patch objects directly using the patch decorator/context...