What problem does it solve? Python developers often default to the same framework or pattern regardless of context, leading to over-engineered or mismatched architectures. This Skill provides decision-making frameworks for choosing between FastAPI, Django, and Flask, deciding async vs sync, and structuring projects correctly. ## Core Features & Use Cases - Framework Selection: Decision trees and comparison tables for choosing FastAPI, Django, or Flask based on project type (API-first, full-stack, scripts, AI/ML serving). - Async vs Sync Guidance: Rules for when to use async def, which async libraries to pick (httpx, asyncpg, aiofiles), and how to avoid mixing sync and async carelessly. - Architecture Principles: Type hint strategies, Pydantic validation, project structure templates, background task selection (Celery, ARQ, BackgroundTasks), error handling, and testing patterns. - Use Case: When starting a new microservice, use this Skill to evaluate whether FastAPI with async SQLAlchemy fits better than Django, then structure the codebase by feature or layer. ## Quick Start Ask the AI to help you choose the right Python framework and architecture for your new API project using the python-patterns skill.
