fastapi▌

Production-grade async Python REST APIs with FastAPI, Pydantic V2, and SQLAlchemy async operations. \n \n Covers REST endpoint design, Pydantic V2 schema validation, async database CRUD, and dependency injection patterns \n Includes JWT authentication, OAuth2 flows, and authorization strategies with secure token management \n Provides WebSocket endpoint setup, OpenAPI/Swagger documentation generation, and async testing with pytest and httpx \n Enforces type hints, async/await patterns, and prope

Create fast, modern Python APIs using FastAPI with async/await support, automatic API documentation, type validation using Pydantic, dependency injection, JWT authentication, and SQLAlchemy ORM integration.

You are a FastAPI expert specializing in high-performance, async-first API development with modern Python patterns.

Expert guidance for building high-performance FastAPI APIs with async best practices and clean Python patterns. \n \n Covers FastAPI fundamentals, Pydantic v2 validation, async/await patterns, and dependency injection for scalable backend development \n Emphasizes functional programming, early returns, guard clauses, and RORO (Receive an Object, Return an Object) pattern for maintainable code \n Includes error handling strategies, middleware design, caching optimization, and performance tuning f

FastAPI best practices and conventions for clean, modern API development. \n \n Use Annotated for all parameter and dependency declarations to maintain type safety, reusability, and compatibility with other contexts \n Declare return types or response models on path operations to enable automatic validation, filtering, serialization, and OpenAPI documentation \n Use async def only when calling async code with await ; default to regular def for blocking operations to avoid event loop blocking \n

A comprehensive skill for building production-ready microservices using FastAPI. This skill covers REST API design patterns, asynchronous operations, dependency injection, testing strategies, and deployment best practices for scalable Python applications.

These are idiomatic FastAPI patterns that may appear problematic but are correct:

Specialized workflow for building production-ready Python backends with FastAPI, featuring async patterns, SQLAlchemy ORM, Pydantic validation, and comprehensive API patterns.

FastAPI async patterns for building high-performance, concurrent APIs with optimal resource usage. \n \n Covers async route handlers, database operations (SQLAlchemy, asyncpg, Motor, Tortoise ORM), and connection pooling strategies for efficient resource management \n Includes real-time communication patterns: WebSockets with authentication and broadcasting, Server-Sent Events (SSE), and streaming responses for large files or generated content \n Provides concurrent request handling with asyncio

Production-tested patterns for FastAPI with Pydantic v2, SQLAlchemy 2.0 async, and JWT authentication.