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Clean Code in Python

Clean Code in Python - Second Edition

By : Anaya
4.6 (34)
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Clean Code in Python

Clean Code in Python

4.6 (34)
By: Anaya

Overview of this book

Experienced professionals in every field face several instances of disorganization, poor readability, and testability due to unstructured code. With updated code and revised content aligned to the new features of Python 3.9, this second edition of Clean Code in Python will provide you with all the tools you need to overcome these obstacles and manage your projects successfully. The book begins by describing the basic elements of writing clean code and how it plays a key role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. The book discusses object-oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve problems by implementing software design patterns in your code. In the concluding chapter, we break down a monolithic application into a microservices-based one starting from the code as the basis for a solid platform. By the end of this clean code book, you will be proficient in applying industry-approved coding practices to design clean, sustainable, and readable real-world Python code.
Table of Contents (13 chapters)
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11
Other Books You May Enjoy
12
Index

Summary

Unit testing is a really interesting and deep topic, but more importantly, it is a critical part of the clean code. Ultimately, unit tests are what determine the quality of the code. Unit tests often act as a mirror for the code—when the code is easy to test, it's clear and correctly designed, and this will be reflected in the unit tests.

The code for the unit tests is as important as production code. All principles that apply to production code also apply to unit tests. This means that they should be designed and maintained with the same effort and thoughtfulness. If we don't care about our unit tests, they will start to have problems and become defective (or problematic) and, as a result of that, useless. If this happens, and they are hard to maintain, they become a liability, which makes things even worse, because people will tend to ignore them or disable them entirely. This is the worst scenario because once this happens, the entire production code...

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Clean Code in Python
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