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Python FastAPI backend development with async patterns, SQLAlchemy, Pydantic, authentication, and production API patterns.
Python/FastAPI Development Workflow Overview Specialized workflow for building production-ready Python backends with FastAPI, featuring async patterns, SQLAlchemy ORM, Pydantic validation, and comprehensive API patterns. When to Use This Workflow Use this workflow when: Building new REST APIs with FastAPI Creating async Python backends Implementing database integration with SQLAlchemy Setting up API authentication Developing microservices Workflow Phases Phase 1: Project Setup Skills to Invoke app-builder - Application scaffolding python-development-python-scaffold - Python scaffolding fastapi-templates - FastAPI templates uv-package-manager - Package management Actions Set up Python environment (uv/poetry) Create project structure Configure FastAPI app Set up logging Configure environment variables Copy-Paste Prompts Use @fastapi-templates to scaffold a new FastAPI project Use @python-development-python-scaffold to set up Python project structure Phase 2: Database Setup Skills to Invoke prisma-expert - Prisma ORM (alternative) database-design - Schema design postgresql - PostgreSQL setup pydantic-models-py - Pydantic models Actions Design database schema Set up SQLAlchemy models Create database connection Configure migrations (Alembic) Set up session management Copy-Paste Prompts Use @database-design to design PostgreSQL schema Use @pydantic-models-py to create Pydantic models for API Phase 3: API Routes Skills to Invoke fastapi-router-py - FastAPI routers api-design-principles - API design api-patterns - API patterns Actions Design API endpoints Create API routers Implement CRUD operations Add request validation Configure response models Copy-Paste Prompts Use @fastapi-router-py to create API endpoints with CRUD operations Use @api-design-principles to design RESTful API Phase 4: Authentication Skills to Invoke auth-implementation-patterns - Authentication api-security-best-practices - API security Actions Choose auth strategy (JWT, OAuth2) Implement user registration Set up login endpoints Create auth middleware Add password hashing Copy-Paste Prompts Use @auth-implementation-patterns to implement JWT authentication Phase 5: Error Handling Skills to Invoke fastapi-pro - FastAPI patterns error-handling-patterns - Error handling Actions Create custom exceptions Set up exception handlers Implement error responses Add request logging Configure error tracking Copy-Paste Prompts Use @fastapi-pro to implement comprehensive error handling Phase 6: Testing Skills to Invoke python-testing-patterns - pytest testing api-testing-observability-api-mock - API testing Actions Set up pytest Create test fixtures Write unit tests Implement integration tests Configure test database Copy-Paste Prompts Use @python-testing-patterns to write pytest tests for FastAPI Phase 7: Documentation Skills to Invoke api-documenter - API documentation openapi-spec-generation - OpenAPI specs Actions Configure OpenAPI schema Add endpoint documentation Create usage examples Set up API versioning Generate API docs Copy-Paste Prompts Use @api-documenter to generate comprehensive API documentation Phase 8: Deployment Skills to Invoke deployment-engineer - Deployment docker-expert - Containerization Actions Create Dockerfile Set up docker-compose Configure production settings Set up reverse proxy Deploy to cloud Copy-Paste Prompts Use @docker-expert to containerize FastAPI application Technology Stack Category Technology Framework FastAPI Language Python 3.11+ ORM SQLAlchemy 2.0 Validation Pydantic v2 Database PostgreSQL Migrations Alembic Auth JWT, OAuth2 Testing pytest Quality Gates All tests passing (>80% coverage) Type checking passes (mypy) Linting clean (ruff, black) API documentation complete Security scan passed Performance benchmarks met Related Workflow Bundles development - General development database - Database operations security-audit - Security testing api-development - API patterns Limitations Use this skill only when the task clearly matches the scope described above. Do not treat the output as a substitute for environment-specific validation, testing, or expert review. Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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