python-patterns

Choosing the right Python framework involves applying decision trees to evaluate project context like API, web app, or library requirements. This skill provides principled guidance to select between FastAPI, Django, and Flask based on your specific project structure.

Async vs sync patterns in Python should be chosen based on whether your workload is I/O or CPU bound. This skill provides decision-making guidance to match your concurrency patterns with your specific workload characteristics for optimal performance.

The best way to structure a large Python project is by following principle-based guidance and recommended example structures. This skill helps you apply consistent architecture choices to reduce rework when designing microservices or refactoring monoliths.

Implementing a type hints strategy for Python microservices requires applying principled decisions to ensure consistency across your codebase. This skill offers type hint strategies tailored to different project scales to improve your overall project structure.

Yes, this Python architecture guidance works for refactoring a monolith by providing decision trees and principle-based direction. It helps you apply consistent architecture choices during refactoring to reduce rework and improve design consistency.

Using principle-based design over standard Python patterns prevents blindly copying architectures without understanding the trade-offs. This skill helps you think through architecture decisions deliberately, ensuring your framework selection and async patterns fit your actual workload.