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  • Book Overview & Buying Clean Code in Python
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Clean Code in Python

Clean Code in Python

By : Mariano Anaya
3.7 (3)
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Clean Code in Python

Clean Code in Python

3.7 (3)
By: Mariano Anaya

Overview of this book

Python is currently used in many different areas such as software construction, systems administration, and data processing. In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them. The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into 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 software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform. By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code.
Table of Contents (12 chapters)
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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...

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Clean Code in Python
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