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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

Final thoughts about design patterns

We have seen the world of design patterns in Python, and in doing so, we have found solutions to common problems, as well as more techniques that will help us achieve a clean design.

All of this sounds good, but it begs the question: how good are design patterns? Some people argue that they do more harm than good, that they were created for languages whose limited type system (and lack of first-class functions) makes it impossible to accomplish things we would normally do in Python. Others claim that design patterns force a design solution, creating some bias that limits a design that would have otherwise emerged, and that would have been better. Let's look at each of these points in turn.

The influence of patterns over the design

A design pattern cannot be good or bad by itself, but rather by how it's implemented, or used. In some cases, there is no need for a design pattern when a simpler solution would do. Trying to force...

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