Backend Technologies · Python
FastAPI — Free Learning Resources
Free, printable resources for FastAPI — practice problems, quick-reference cheatsheet, and an interview prep sheet. No sign-up required.
FastAPI — Practice Worksheet
Structured exercises and problems to build hands-on FastAPI skills. Work through key concepts step by step.
FastAPI — Cheatsheet
One-page quick-reference for FastAPI — key syntax, commands, patterns, and best practices at a glance.
FastAPI — Interview Sheet
Top FastAPI interview questions with concise answers. Get ready for any technical round with this focused prep sheet.
About FastAPI
FastAPI is a modern, high-performance Python web framework for building APIs with Python 3.8+ based on standard type hints. Built on Starlette and Pydantic, it delivers automatic OpenAPI documentation, request validation, and serialization with zero boilerplate. Benchmarks consistently place FastAPI among the fastest Python frameworks.
FastAPICheat Sheet — What's Covered
- ✓Path parameters, query params, and request body validation with Pydantic
- ✓Dependency injection — reusable dependencies, DB sessions, auth
- ✓Async endpoints with async/await and background tasks
- ✓Automatic OpenAPI (Swagger UI + ReDoc) documentation generation
- ✓OAuth2, JWT authentication, and security schemes
Frequently Asked Questions — FastAPI
How does FastAPI generate documentation automatically?
FastAPI reads Python type hints and Pydantic models from route signatures to generate an OpenAPI 3.0 schema at /openapi.json, then serves Swagger UI at /docs and ReDoc at /redoc — no extra configuration required.
How does FastAPI's dependency injection work?
Declare a function with Depends() as a route parameter. FastAPI calls it and injects the result. Use yield-based dependencies for DB sessions (automatically closed after the request). Dependencies can depend on other dependencies.
When should you use async def vs def in FastAPI?
Use async def for I/O-bound operations using async libraries (asyncpg, httpx). Use plain def for synchronous library calls — FastAPI runs these in a thread pool to avoid blocking the event loop. Mixing sync/async incorrectly causes performance problems.
How does FastAPI validate request data?
Define a Pydantic BaseModel and use it as a parameter type. FastAPI parses the JSON body, validates types and constraints, and returns a 422 Unprocessable Entity with detailed field-level error messages if validation fails.
How does FastAPI compare to Flask?
FastAPI is async-first and delivers 2-3x the throughput of synchronous Flask. It provides automatic validation and docs that Flask lacks. Choose FastAPI for new APIs; Flask when you need its mature ecosystem of extensions or simpler mental model.
Who Is This For?
Python developers building high-performance REST APIs who value auto-generated documentation, type safety, and async-first design.