FastAPI Learning Guide

A hands-on, beginner-to-production path for learning Python + FastAPI. You start from Python basics and finish with a real server-side application: database, authentication, background jobs, caching, tests, Docker, and CI/CD.

Everything is built around one example app that grows lesson by lesson. The finished version lives in app/ so you can always peek ahead or check your work.

Who this is for

• You know little or no Python and want a clear route to shipping backend APIs.
• You learn best by running code, breaking it, and fixing it.

No prior web or backend experience assumed.

What you'll build

A small "notes" API where users can register, log in, and manage their own private items. Along the way it gains:

• A SQL database via SQLModel (SQLAlchemy + Pydantic in one)
• Schema migrations with Alembic
• Token auth with JWT / OAuth2 password flow
• Background jobs with Celery + Redis, plus response caching
• A pytest suite, a Dockerfile + docker-compose, and a GitHub Actions CI pipeline

The lessons

Work through docs/ in order:

#	Lesson	You'll learn
00	Setup	Install Python, create a virtual environment, run the project
01	Python fundamentals	Variables, types, functions, classes, type hints, async
02	Your first FastAPI app	Routes, path/query params, auto docs
03	Pydantic & validation	Request/response models, settings from env
04	Database with SQLModel	Models, sessions, CRUD, dependencies
05	Migrations with Alembic	Evolving your schema safely
06	Auth: JWT & OAuth2	Hashing, tokens, protected routes
07	Background tasks: Redis & Celery	Offloading slow work
08	Caching with Redis	Faster responses, cache invalidation
09	Testing with pytest	Fixtures, the test client, isolation
10	Docker	Containerizing the app and its services
11	CI/CD with GitHub Actions	Automated tests on every push
12	Next steps	Where to go from here

Quick start

# 1. Clone and enter the project
git clone <your-fork-url> fastapi-learning-guide
cd fastapi-learning-guide

# 2. Create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate        # Windows: .venv\Scripts\activate

# 3. Install dependencies
pip install -r requirements.txt

# 4. Copy the example environment file
cp .env.example .env

# 5. Run the API
uvicorn app.main:app --reload

Open http://127.0.0.1:8000/docs for interactive API documentation. Try it out: register a user, click Authorize, and call the protected endpoints.

Run the tests:

pytest

Project layout

fastapi-learning-guide/
├── app/                 # The example application (grows across lessons)
│   ├── main.py          # App entrypoint
│   ├── config.py        # Settings from environment
│   ├── database.py      # Engine + session
│   ├── models.py        # Database tables (SQLModel)
│   ├── schemas.py       # Request/response shapes
│   ├── security.py      # Password hashing + JWT
│   ├── deps.py          # Reusable dependencies
│   ├── cache.py         # Redis cache (with in-memory fallback)
│   ├── tasks.py         # Celery background jobs
│   └── routers/         # Route modules: auth, users, items
├── tests/               # pytest suite
├── alembic/             # Database migrations
├── docs/                # The lessons
├── Dockerfile
├── docker-compose.yml
└── .github/workflows/ci.yml

How to use this repo

Each lesson explains a concept, points at the relevant file(s) in app/, and gives commands to run. You don't have to type everything from scratch — read the code, run it, then change something and see what happens. That loop is where the learning happens.

License

MIT — see LICENSE. Free to use, share, and adapt for your own study or teaching.