Book Image

Clean Code in Python - Second Edition

By : Mariano Anaya
Book Image

Clean Code in Python - Second Edition

By: Mariano 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)
11
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12
Index

Dependency inversion

This is a really powerful idea that will come up again later when we explore some design patterns in Chapter 9, Common Design Patterns, and Chapter 10, Clean Architecture.

The dependency inversion principle (DIP) proposes an interesting design principle by which we protect our code by making it independent of things that are fragile, volatile, or out of our control. The idea of inverting dependencies is that our code should not adapt to details or concrete implementations, but rather the other way around: we want to force whatever implementation or detail to adapt to our code via a sort of API.

Abstractions have to be organized in such a way that they do not depend on details, but rather the other way around—the details (concrete implementations) should depend on abstractions.

Imagine that two objects in our design need to collaborate, A and B. A works with an instance of B, but as it turns out, our module doesn't control B directly...