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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

Analysis of descriptors

We have seen how descriptors work so far and explored some interesting situations in which they contribute to clean design by simplifying their logic and leveraging more compact classes.

Up to this point, we know that by using descriptors, we can achieve cleaner code, abstracting away repeated logic and implementation details. But how do we know our implementation of the descriptors is clean and correct? What makes a good descriptor? Are we using this tool properly or over-engineering with it?

In this section, we will analyze descriptors in order to answer these questions.

How Python uses descriptors internally

What makes a good descriptor? A simple answer would be that a good descriptor is pretty much like any other good Python object. It is consistent with Python itself. The idea that follows this premise is that analyzing how Python uses descriptors will give us a good idea of good implementations so that we know what to expect from the descriptors...

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