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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
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Part 2: Implementing Clean Architecture in Python
11
Part 3: Applying Clean Architecture in Python
16
Other Books You May Enjoy
17
Index

Decoupling for flexibility: inverting dependencies in Python

Upon exploring LSP and its role in creating robust abstractions, we’ve seen how it contributes to the flexibility and maintainability of our Python code. Now let’s turn our attention to the final piece of the SOLID puzzle: the Dependency Inversion Principle (DIP).

DIP serves as a capstone to the SOLID principles, tying together and reinforcing the concepts we explored in the previous principles. It provides a powerful mechanism for structuring the relationships between different components of our system, further enhancing the flexibility and maintainability we’ve been building throughout our journey through SOLID.

While LSP ensures that our abstractions are well-formed and substitutable, DIP focuses on how these abstractions should relate to one another. It guides us in creating a structure where high-level modules aren’t dependent on low-level modules, but both depend on abstractions...

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Clean Architecture with Python
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