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.

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Table of Contents (12 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Introduction, Code Formatting, and Tools
Introduction, Code Formatting, and Tools
The meaning of clean code
The importance of having clean code
Docstrings and annotations
Summary
2
Pythonic Code
Pythonic Code
Indexes and slices
Context managers
Properties, attributes, and different types of methods for objects
Iterable objects
Container objects
Dynamic attributes for objects
Callable objects
Summary of magic methods
Caveats in Python
Summary
References
3
General Traits of Good Code
General Traits of Good Code
Design by contract
Defensive programming
Separation of concerns
Acronyms to live by
Composition and inheritance
Arguments in functions and methods
Final remarks on good practices for software design
Summary
References
4
The SOLID Principles
The SOLID Principles
Single responsibility principle
The open/closed principle
Liskov's substitution principle
Interface segregation
Dependency inversion
Summary
References
5
Using Decorators to Improve Our Code
Using Decorators to Improve Our Code
What are decorators in Python?
Effective decorators – avoiding common mistakes
The DRY principle with decorators
Decorators and separation of concerns
Analyzing good decorators
Summary
References
6
Getting More Out of Our Objects with Descriptors
Getting More Out of Our Objects with Descriptors
A first look at descriptors
Types of descriptors
Descriptors in action
Analysis of descriptors
Summary
References
7
Using Generators
Using Generators
Technical requirements
Creating generators
Iterating idiomatically
Coroutines
Asynchronous programming
Summary
References
8
Unit Testing and Refactoring
Unit Testing and Refactoring
Design principles and unit testing
Frameworks and tools for testing
Refactoring
More about unit testing
A brief introduction to test-driven development
Summary
References
9
Common Design Patterns
Common Design Patterns
Considerations for design patterns in Python
Design patterns in action
The null object pattern
Final thoughts about design patterns
Summary
References
10
Clean Architecture
Clean Architecture
From clean code to clean architecture
Software components
Use case
Summary
References
Summing it all up
11
Other Books You May Enjoy
Other Books You May Enjoy
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