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Clean Code in Python

You're reading from   Clean Code in Python Develop maintainable and efficient code

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Product type Paperback
Published in Jan 2021
Publisher Packt
ISBN-13 9781800560215
Length 422 pages
Edition 2nd Edition
Languages
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Author (1):
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Mariano Anaya Mariano Anaya
Author Profile Icon Mariano Anaya
Mariano Anaya
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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction, Code Formatting, and Tools 2. Pythonic Code FREE CHAPTER 3. General Traits of Good Code 4. The SOLID Principles 5. Using Decorators to Improve Our Code 6. Getting More Out of Our Objects with Descriptors 7. Generators, Iterators, and Asynchronous Programming 8. Unit Testing and Refactoring 9. Common Design Patterns 10. Clean Architecture 11. Other Books You May Enjoy
12. Index

Tools for testing

There are a lot of tools we can use for writing our unit tests, all of them with pros and cons and serving different purposes. I'll present the two most common libraries used for unit testing in Python. They cover most (if not all) use cases, and they're very popular, so knowing how to use them comes in handy.

Along with testing frameworks and test running libraries, it's often common to find projects that configure code coverage, which they use as quality metrics. Since coverage (when used as a metric) is misleading, after seeing how to create unit tests, we'll discuss why it's not to be taken lightly.

The next section starts by introducing the main libraries we're going to use in this chapter for unit testing.

Frameworks and libraries for unit testing

In this section, we will discuss two frameworks for writing and running unit tests. The first one, unittest, is available in the standard library of Python, while the...

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