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Found 201 Skills
Modern Python API development with FastAPI covering async patterns, Pydantic validation, dependency injection, and production deployment
FastAPI integration testing specialist. Covers synchronous TestClient, async httpx AsyncClient, dependency injection overrides, auth testing (JWT, OAuth2, API keys), WebSocket testing, file uploads, background tasks, middleware testing, and HTTP mocking with respx, responses, and pytest-httpserver. USE WHEN: user mentions "FastAPI test", "TestClient", "httpx async test", "dependency override test", "respx mock", asks about testing FastAPI endpoints, authentication in tests, or HTTP client mocking. DO NOT USE FOR: Django - use `pytest-django`; pytest internals - use `pytest`; Container infrastructure - use `testcontainers-python`
Shared conventions for Next.js 16 + FastAPI full-stack projects. Architecture, code quality, testing, styling, and commands. Referenced by nextjs-fastapi-implementor and nextjs-fastapi-reviewer.
Comprehensive guide for building production-ready microservices with FastAPI including REST API patterns, async operations, dependency injection, and deployment strategies
FastAPI best practices, async patterns, and Pydantic validation
Review FastAPI security audit patterns for dependencies and middleware. Use for auditing auth dependencies, CORS configuration, and TrustedHost middleware. Use proactively when reviewing FastAPI apps. Examples: - user: "Audit FastAPI route security" → check for Depends() and Security() usage - user: "Check FastAPI CORS setup" → verify origins when allow_credentials=True - user: "Review FastAPI middleware" → check TrustedHost and HTTPSRedirect config - user: "Secure FastAPI API keys" → move from query params to header schemes - user: "Scan for FastAPI footguns" → check starlette integration and dependency order
Expert guidance for building production-ready FastAPI applications with modular architecture where each business domain is an independent module with own routes, models, schemas, services, cache, and migrations. Uses UV + pyproject.toml for modern Python dependency management, project name subdirectory for clean workspace organization, structlog (JSON+colored logging), pydantic-settings configuration, auto-discovery module loader, async SQLAlchemy with PostgreSQL, per-module Alembic migrations, Redis/memory cache with module-specific namespaces, central httpx client, OpenTelemetry/Prometheus observability, conversation ID tracking (X-Conversation-ID header+cookie), conditional Keycloak/app-based RBAC authentication, DDD/clean code principles, and automation scripts for rapid module development. Use when user requests FastAPI project setup, modular architecture, independent module development, microservice architecture, async database operations, caching strategies, logging patterns, configuration management, authentication systems, observability implementation, or enterprise Python web services. Supports max 3-4 route nesting depth, cache invalidation patterns, inter-module communication via service layer, and comprehensive error handling workflows.
Guides FastAPI backend design using Domain-Driven Design (DDD) and Onion Architecture in Python. Use when structuring a FastAPI app (routes/handlers, Pydantic schemas, Depends-based DI), modeling domain Entities/Value Objects, defining repository interfaces, implementing SQLAlchemy infrastructure adapters, or writing use cases, based on the dddpy reference.
FastAPI framework mechanics and advanced patterns. Use when configuring middleware, creating dependency injection chains, implementing WebSocket endpoints, customizing OpenAPI documentation, setting up CORS, building authentication dependencies (JWT validation, role-based access), implementing background tasks, or managing application lifespan (startup/shutdown). Does NOT cover basic endpoint CRUD or repository/service patterns (use python-backend-expert) or testing (use pytest-patterns).
Build production-grade FastAPI backends with SQLModel, Dapr integration, and JWT authentication. Use when building REST APIs with Neon PostgreSQL, implementing event-driven microservices with Dapr pub/sub, scheduling jobs, or creating CRUD endpoints with JWT/JWKS verification. NOT when building simple scripts or non-microservice architectures.
Build FastAPI applications using Clean Architecture principles with proper layer separation (Domain, Infrastructure, API), dependency injection, repository pattern, and comprehensive testing. Use this skill when designing or implementing Python backend services that require maintainability, testability, and scalability.
Plan and build production-ready FastAPI endpoints with async SQLAlchemy, Pydantic v2 models, dependency injection for auth, and pytest tests. Uses interview-driven planning to clarify data models, authentication method, pagination strategy, and caching before writing any code.