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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

Tools and patterns for test maintenance

While Clean Architecture’s boundaries help us write focused tests, maintaining a comprehensive test suite presents its own challenges. As our task management system grows, so do our tests. New business rules require additional test cases, infrastructure changes need updated verification, and simple modifications can affect multiple test files. Without careful organization, we risk spending more time managing tests than improving our system.

When a test fails, we need to quickly understand what architectural boundary was violated. When business rules change, we should be able to update tests systematically rather than have to hunt through multiple files. When adding new test cases, we want to leverage existing test infrastructure rather than have to duplicate setup code.

Python’s testing ecosystem, particularly pytest, provides powerful tools that align naturally with Clean Architecture’s goals. We’ll explore...

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