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Preface

Getting Started with Clean Code in Python

Introduction to Clean Code, Code Formatting, and Tools

An Introduction to Clean Code Code Formatting Documentation: Code Comments Documentation: Docstrings Documentation: Annotations Tooling for Type Consistency and General Validations Tooling for Automatic Formatting Quiz on Introduction to Clean Code, Code Formatting, and Tools

Pythonic Code

Indexes and Slices Context Managers Comprehensions and Assignment Expressions Properties, Attributes, and Different Types of Methods for Objects Creating Classes with a More Compact Syntax Iterable Objects Other Properties, Attributes, and Methods Summary of Magic Methods Caveats in Python Quiz on Pythonic Code

General Traits of Good Code

Design by Contract Defensive Programming Best Practices for Exception Handling Using Assertions in Python Separation of Concerns Acronyms to Live By Inheritance in Python Multiple Inheritance in Python Arguments in Functions and Methods Variable Number of Arguments in Python More on How Function Arguments Work in Python Optimizing the Number of Arguments in Functions Final Remarks on Good Practices for Software Design Quiz on General Traits of Good Code

The SOLID Principles

The Single Responsibility Principle The Open/Closed Principle Liskov's Substitution Principle Integration Segregation Principle Dependency Inversion Principle Quiz on the SOLID Principles Challenge: The Single Responsibility Principle Solution: The Single Responsibility Principle

Using Decorators to Improve Our Code

What Are Decorators in Python?Function Decorators Class Decorators More Advanced Decorators Decorators with Default Values Decorators for Coroutines Extended Syntax for Decorators Good Uses for Decorators Effective Decorators—Avoiding Common Mistakes Dealing with Side Effects in Decorators Creating Decorators That Will Always Work Decorators and Clean Code The DRY Principle with Decorators Decorators and Separation of Concerns Analysis of Good Decorators Quiz on Using Decorators to Improve Our Code Challenge: Creating Function Decorators Solution: Creating Function Decorators

Getting More Out of Our Objects with Descriptors

A First Look at Descriptors Get Method of the Descriptor Protocol Set Method of the Descriptor Protocol Delete Method of the Descriptor Protocol Set Name Method of the Descriptor Protocol Types of Descriptors An Application of Descriptors Different Forms of Implementing Descriptors More Considerations for Using Descriptors Analysis of Descriptors Final Remarks About Descriptors Quiz on Getting More Out of Our Objects with Descriptors Challenge: Creating Descriptors Solution: Creating Descriptors

Generators, Iterators, and Asynchronous Programming

What are Generators?

Generator Expressions

Iterating Idiomatically

Simplifying Code through Iterators

The Iterator Pattern in Python

More Advanced Coroutines

Further Uses of the yield from Construction

Asynchronous Programming

Magic Asynchronous Methods

Asynchronous Iteration and Asynchronous Generators

Quiz on Generators, Iterators, and Asynchronous Programming

Challenge: Asynchronous Programming

Solution: Asynchronous Programming

Unit Testing and Refactoring

Design Principles and Unit Testing Forms of Automated Testing Unit Testing and Agile Software Development Unit Testing and Software Design Getting Started with Testing The unittest Module Parameterised Tests Using unittest The pytest Framework Parameterized Tests Using pytest Fixtures in pytest Code Coverage Mock Objects Using Mock Objects Refactoring More about Testing Common Themes in Testing Test-Driven Development Quiz on Unit Testing and Refactoring

Common Design Patterns

Design Patterns Considerations in Python Design Patterns in Action Creational Patterns Shared State The Borg Pattern Adapter Composite Decorator Facade Chain of Responsibility The Template Method Command State The Null Object Pattern Final Thoughts about Design Patterns Quiz on Common Design Patterns

Clean Architecture

From Clean Code to Clean Architecture Separation of Concerns Monolithic Applications and Microservices Abstractions Software Components Packages Managing Dependencies Docker Containers Use Case The Service Analysis of the Architectural Traits Quiz on Clean Architecture

Conclusion

An Overview of the Course Ending Notes

Clean Code in Python/

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Generator Expressions

Generator Expressions

Learn how to utilize generator expressions

We'll cover the following...

How generator expressions work
Point to remember

Before going into the details and nuances of generators, let's take a quick look at how generators relate to a concept that we have already seen: comprehensions. A generator in the form of a comprehension is called a generator expression.

How generator expressions work

Generators save a lot of memory, and since they are iterators, they are a convenient alternative to other iterables or containers that ...