F1 Analytics is a full-stack dashboard for tracking race weekends, comparing drivers, and reviewing team performance. The backend is FastAPI + SQLite, the frontend is React + Vite, and the data pipeline is powered by FastF1.
- Season calendar tracking (next race, completed rounds, progress).
- Driver comparison with points, average finishes, wins, podiums, and total laps.
- Race results with finishing order, grid position, points, and status.
- Team performance and pit stop analytics.
- Data source: FastF1 (session data cached locally).
- Storage: SQLite database at
data/database.db. - Refresh cadence: run the pipeline manually when you want fresh data; cached pulls live in
notebook/cache.
- Backend: FastAPI, SQLAlchemy, SQLite
- Frontend: React 19, Vite, React Router
- Data: FastF1, Pandas
backend/
api/
main.py
routes/
drivers.py
races.py
laps.py
teams.py
data_collection/
extract.py
transform.py
load.py
pipeline.py
models/
database.py
data/
frontend/
src/
components/
pages/
services/
styles/
notebook/
explore_data.ipynb
cache/
Create a virtual environment, install dependencies, initialize the database, load data, then start the API:
python -m venv .venv
source .venv/bin/activate
pip install -r backend/requirements.txt
pip install -r requirements.txt # optional: notebooks + data tooling
python backend/models/database.py
python backend/data_collection/pipeline.py
uvicorn backend.api.main:app --reload
The API runs at http://localhost:8000.
cd frontend
npm install
npm run dev
The app runs at http://localhost:5173 by default.
The frontend reads VITE_API_URL from your environment. If not set, it defaults to http://localhost:8000.
The ETL pipeline pulls session data from FastF1, cleans it, and loads it into SQLite at data/database.db.
Run the pipeline:
python backend/data_collection/pipeline.py
Exploratory analysis lives in notebook/explore_data.ipynb.