How does this skill help with code complexity?

It provides frameworks like KISS (Keep It Simple) and the Rule of Three to prevent over-engineering and ensure abstractions are only added when they solve concrete problems.

Is it compatible with frameworks like FastAPI or Flask?

Absolutely. While framework-agnostic, these patterns are specifically designed to organize logic within Python web frameworks and API services.

Can I use this for existing projects?

Yes, the skill includes specific patterns for refactoring complex codebases into clean, separated layers like Services and Repositories.

Does it focus on testing?

Yes, it emphasizes Dependency Injection and Composition Over Inheritance, which are critical patterns for creating highly testable and mockable Python units.

Python Design Patterns & Architecture

Name: Python Design Patterns & Architecture
Author: wshobson

bywshobson

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27,605

API Development

Applies fundamental software design principles like KISS, SRP, and composition to build maintainable and scalable Python applications.

About

This skill empowers Claude to architect Python systems using industry-standard design patterns and clean code principles. It provides actionable guidance on when to abstract, how to separate concerns into distinct layers (API, Service, Repository), and how to choose composition over inheritance for more testable code. By implementing patterns like the Rule of Three and Dependency Injection, it helps developers reduce technical debt and build modular systems that are easy to modify, test, and understand.

Key Features

Decision frameworks for abstraction and refactoring tasks
Architectural guidance for multi-layered service design (API, Service, Repo)
Implementation of SOLID principles optimized for Python syntax
Best practices for avoiding common Python anti-patterns and code smells
27,605 GitHub stars
Dependency injection patterns for improved unit testing

Use Cases

Refactoring monolithic or tangled legacy code into modular services
Evaluating when to implement abstractions versus keeping code simple and readable
Designing a new backend API architecture with clear separation of concerns

About

Key Features

Decision frameworks for abstraction and refactoring tasks
Architectural guidance for multi-layered service design (API, Service, Repo)
Implementation of SOLID principles optimized for Python syntax
Best practices for avoiding common Python anti-patterns and code smells
27,605 GitHub stars
Dependency injection patterns for improved unit testing

Use Cases

Refactoring monolithic or tangled legacy code into modular services
Evaluating when to implement abstractions versus keeping code simple and readable
Designing a new backend API architecture with clear separation of concerns