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

Testing packages


In Chapter 10, Testing and Logging – Preparing for Bugs, the testing chapter, we saw a few of the many testing systems for Python. As you might suspect, at least some of these have setup.py integration.

Unittest

Before we start, we should create a test script for our package. For actual tests, look at Chapter 10, Testing and Logging – Preparing for Bugs, the testing chapter. In this case, we will just use a no-op test, test.py:

import unittest


class Test(unittest.TestCase):

    def test(self):
        pass

The standard python setup.py test command will run the regular unittest command:

# python setup.py -v test
running test
running "unittest --verbose"
running egg_info
writing Our_little_project.egg-info/PKG-INFO
writing dependency_links to Our_little_project.egg-info/dependency_links.txt
writing top-level names to Our_little_project.egg-info/top_level.txt
writing entry points to Our_little_project.egg-info/entry_points.txt
reading manifest file 'Our_little_project.egg-info...