Book Image

Clean Code in Python

By : Mariano Anaya
2 (1)
Book Image

Clean Code in Python

2 (1)
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)

Summary

The SOLID principles are key guidelines for good object-oriented software design.

Building software is an incredibly hard task—the logic of the code is complex, its behavior at runtime is hard (if even possible, sometimes) to predict, requirements change constantly as well as the environment, and there are multiple things that can go wrong.

In addition, there are multiple ways of constructing software with different techniques, paradigms, and a lot of different designs, which can work together to solve a particular problem in a specific manner. However, not all of these approaches will prove to be correct as time passes, and requirements change or evolve. However, by this time, it will already be too late to do something about an incorrect design, as it is rigid, inflexible, and therefore hard to change a refactor into the proper solution.

This means that, if we...