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Clean Architecture with Python

Clean Architecture with Python

By : Sam Keen
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Clean Architecture with Python

Clean Architecture with Python

5 (1)
By: Sam Keen

Overview of this book

In the rapidly evolving tech industry, software applications struggle to keep pace with changing business needs, leaving developers grappling with complex codebases that resist change, ultimately reducing productivity and increasing technical debt. Clean Architecture with Python offers a powerful approach to address these challenges. Drawing from his extensive experience architecting cloud-native systems, Sam Keen helps you transform complex architectural challenges into digestible, implementable solutions. This book teaches essential principles for effective development, emphasizing the Pythonic implementation of Clean Architecture. Through practical examples, you'll learn how to create modular, loosely coupled systems that are easy to understand, modify, and extend. The book covers key concepts such as the Dependency Rule, separation of concerns, and domain modeling, all tailored for Python development. By the end of this book, you'll be able to apply Clean Architecture principles effectively in your Python projects. Whether you're building new systems or managing existing ones, you'll have the skills to create more maintainable and adaptable applications. This approach will enhance your ability to respond to changing requirements, setting you up for long-term success in your development career.
Table of Contents (18 chapters)
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Part 1: Foundations of Clean Architecture in Python
5
Part 2: Implementing Clean Architecture in Python
11
Part 3: Applying Clean Architecture in Python
16
Other Books You May Enjoy
17
Index

From rigid to flexible: rethinking inheritance and interfaces in Python

As we’ve explored the Single Responsibility, Open–Closed, and Interface Segregation Principles, we’ve built a foundation for creating modular, extensible, and focused code. These principles guide us in structuring our classes and interfaces to be more maintainable and adaptable. Now, we turn our attention to the Liskov Substitution Principle (LSP), which complements and reinforces the principles we’ve discussed.

While SRP guides us in creating focused, cohesive classes, OCP allows us to extend our code without modifying existing components, and ISP promotes the creation of specific, client-tailored interfaces. LSP ensures that our abstractions are well-formed, and our components are truly interchangeable. This principle is crucial for creating robust, flexible systems by ensuring that our inheritance hierarchies behave predictably.

In the context of Clean Architecture, LSP plays...

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Clean Architecture with Python
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