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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

Design patterns have always been seen as proven solutions to common problems. This is a correct assessment, but in this chapter, we explored them from the point of view of good design techniques, patterns that leverage clean code. In most of the cases, we looked at how they provide a good solution to preserve polymorphism, reduce coupling, and create the right abstractions that encapsulate details as needed—all traits that relate to the concepts explored in Chapter 8, Unit Testing and Refactoring.

Still, the best thing about design patterns is not the clean design we can obtain from applying them, but the extended vocabulary. Used as a communication tool, we can use their names to express the intention of our design. And sometimes, it's not the entire pattern that we need to apply, but we might need to take a particular idea (a substructure, for example) of a pattern from our solution, and here, too, they prove to be a way of communicating more effectively...

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Clean Code in Python
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