Book Image

Mastering Python 2E - Second Edition

By : Rick van Hattem
5 (1)
Book Image

Mastering Python 2E - Second Edition

5 (1)
By: Rick van Hattem

Overview of this book

Even if you find writing Python code easy, writing code that is efficient, maintainable, and reusable is not so straightforward. Many of Python’s capabilities are underutilized even by more experienced programmers. Mastering Python, Second Edition, is an authoritative guide to understanding advanced Python programming so you can write the highest quality code. This new edition has been extensively revised and updated with exercises, four new chapters and updates up to Python 3.10. Revisit important basics, including Pythonic style and syntax and functional programming. Avoid common mistakes made by programmers of all experience levels. Make smart decisions about the best testing and debugging tools to use, optimize your code’s performance across multiple machines and Python versions, and deploy often-forgotten Python features to your advantage. Get fully up to speed with asyncio and stretch the language even further by accessing C functions with simple Python calls. Finally, turn your new-and-improved code into packages and share them with the wider Python community. If you are a Python programmer wanting to improve your code quality and readability, this Python book will make you confident in writing high-quality scripts and taking on bigger challenges
Table of Contents (21 chapters)
19
Other Books You May Enjoy
20
Index

Testing

In Chapter 10, Testing and Logging – Preparing for Bugs, we saw a few of the many testing systems for Python. As you might suspect, at least some of these have setup.py integration. It should be noted that setuptools even has a dedicated test command (at the time of writing), but this command has been deprecated and the setuptools documentation now recommends using tox. While I am a huge fan of tox, for immediate local development it often incurs quite a bit of overhead. I find that executing py.test directly is faster, because you can really quickly test only the bits of the code that you changed.

unittest

Before we start, we should create a test script for our package. For actual tests please look at Chapter 10; 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 has been deprecated, so we will run unittest directly:

$ python3...