GET /itemsQuery: limit (integer)Response: Item[]Status: 200 OK
FastAPI BackendHigh-performance async Python APIs
FastAPI is our choice for Python microservices and AI endpoints — async I/O, automatic OpenAPI docs, and Pydantic validation from a single function signature. Fast to write, fast to run.
FastAPI is the fastest-growing Python web framework, built for modern async API development. Define your endpoints with Python type hints and get automatic request validation, OpenAPI documentation, and high-performance async I/O — all from a single function signature. At A Major, we use FastAPI for microservices, AI/ML inference endpoints, and any API where performance and developer speed both matter. FastAPI runs on Starlette (ASGI) and Pydantic, combining async request handling with runtime data validation. It's the natural choice for Python services that need to handle concurrent I/O efficiently — database queries, external API calls, and LLM inference in parallel.
Quick start
pip install fastapi uvicorn
uvicorn main:app --reloadRead the full documentation at fastapi.tiangolo.com
Async I/O performance
Native async/await with Starlette — handle thousands of concurrent connections without thread pool bottlenecks.
Auto OpenAPI docs
Swagger UI and ReDoc generated automatically from your type hints — interactive API docs with zero config.
Pydantic validation
Request and response validation via Pydantic models — type coercion, nested objects, and clear error messages.
AI & ML endpoints
Python-native framework ideal for serving ML models — integrate PyTorch, TensorFlow, or LangChain directly.
Dependency injection
Built-in DI system for database sessions, auth, and shared services — clean, testable endpoint signatures.
ASGI ecosystem
Full ASGI compatibility — deploy with Uvicorn, add middleware from Starlette, or mount sub-applications.
Why it's hard
No built-in ORM or database layer
FastAPI is intentionally minimal — you need to bring your own ORM (SQLAlchemy, Tortoise) and handle migrations (Alembic) separately.
Async ecosystem gaps
Not all Python libraries support async. Mixing sync and async code requires careful handling to avoid blocking the event loop.
Project structure is up to you
FastAPI doesn't prescribe a project layout. Without clear conventions, larger codebases can become disorganized quickly.
Best practices
Use dependency injection for shared resources
FastAPI's Depends() system handles database sessions, auth, and configuration — compose dependencies cleanly.
Define response models explicitly
Set response_model on every endpoint to control serialization, exclude sensitive fields, and generate accurate OpenAPI docs.
Use Alembic for database migrations
Pair SQLAlchemy models with Alembic for auto-generated, reviewable migration scripts. Never modify production schemas manually.
Run with Uvicorn behind Gunicorn in production
Gunicorn manages worker processes while Uvicorn handles async I/O — the recommended production deployment pattern.
Useful resources
Frequently asked questions
Related technologies
Related services
Looking for end-to-end delivery? These services complement FastAPI projects.
Web App Development
Full-stack web applications built for real users and real scale
Enterprise Software Development
Internal tools, dashboards, and integrations built for real business complexity
SaaS Development
Subscription software built to scale from day one
Technical Consultancy
Not sure what you need? We'll help you figure it out before you spend a dollar
Want to build with FastAPI?
Talk to our engineering team about your FastAPI architecture. We'll respond within 24 hours.
We limit intake each month so every project gets the focus it deserves.