🏎️ RacePace web-app v0.7

A web application for exploring Formula 1 driver data, sessions, lap times, and results — using OpenF1 data.

Application is live on https://f1racepace.vercel.app

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🚀 Features

• ✅ Track F1 events by year and location
• ✅ View session info (FP1, FP2, Qualifying, Race, etc.)
• ✅ Explore driver participation and compare lap times
• ✅ Clean, modular FastAPI backend using SQLModel
• ✅ PostgreSQL database
• ✅ Frontend in React

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📁 Structure

F1Project/
├── backend/
│   ├── main.py           # ✅ FastAPI app entry point
│   ├── models/           # SQLModel ORM classes
│   ├── api/              # API route definitions
│   ├── crud/             # DB access logic
│   ├── db/               # DB definitions and utilities (engine, sessions, populators)
│   ├── schemas/          # Pydantic models for request/response
│   ├── utils/            # Utility files
│   └── __init__.py
├── frontend/
│   ├── app/              # Exports frontend code
│   ├── public/           # Frontend static files
│   ├── src/              # Source code
├── static/               # static files (icons)
├── .env                  # Environment variables (ignored in Git)
├── requirements.txt      # Python dependencies
└── README.md             # Project documentation

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🛠️ Setup & Usage

1. Clone the Repo

git clone git@github.com:estefanotuyama/racepace-web.git
cd racepace-web

2. Create a Virtual Environment

python -m venv venv
source venv/bin/activate  # On macOS/Linux
# or
.\venv\Scripts\activate   # On Windows

3. Install Dependencies

pip install -r dev-requirements.txt

4. Configure the Database

This project uses PostgreSQL for the database. You will need to have PostgreSQL installed and running.

1. Install PostgreSQL: You can download and install PostgreSQL from the official website: https://www.postgresql.org/download/

2. Create a Database and User: Create a new database and a user with privileges to access it. You can do this using the psql command-line tool or a graphical tool like pgAdmin.

3. Create a .env file: In the root of the project, create a file named .env and add the following line, replacing 'user' with your username, 'password' with your password (if set) and 'database' with your database name:

   DATABASE_URL="postgresql://user:password@host:port/database"
   

5. 🗄️ Populate the Database

The project pulls data from the OpenF1 API. To create the database tables and populate them, run:

python -m backend.db.update_db

May take up to 20 minutes.

6. 🧪 Run the API Server

From the root directory (with the venv active), start the development server with:

uvicorn backend.main:app --reload

Now, you can access the API documentation:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

7. Add frontend .env

Add a .env in the frontend directory and point the frontend to the API:

REACT_APP_API_URL=http://localhost:8000

8. Install Frontend dependencies and start frontend server

cd ./frontend
npm install
npm start

Now, you can access the application at http://localhost:3000

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📌 TODO

• Add driver, session, and lap time API routes (in progress)
• Write tests using pytest
• Add Front-End
• Add session stats feature
• Convert to PostgreSQL
• Add lap time comparison feature
• Deploy to a cloud service (frontend deployed in Vercel, backend on Hetzner)

Future goal is to add a live data module so users can view and compare driver data from live races.

👨‍💻 Author

Built by Estéfano Tuyama Gerassi

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⚠️ License

This project is for educational purposes only. Data is sourced from the public OpenF1 API.