Formula 1 Race Replay and Visualization Library
Project description
f1-replay
A Python toolkit for Formula 1 data analysis and visualization. Built on FastF1 with intelligent caching, circuit plotting, and interactive race replay.
Installation
pip install f1-replay
Quick Start
Race Replay
Watch any historic race with an interactive 2D viewer:
from f1_replay import Manager
mgr = Manager()
mgr.race(2024, "monaco")
Or from the command line:
f1-replay 2024 monaco
The viewer includes animated car positions, live standings with gap times, strategy panel, track status overlays (safety car, VSC, red flags), rain effects, race control messages, and more.
Circuit Plotting
Generate poster-style circuit maps:
mgr = Manager()
weekend = mgr.load_weekend(2024, "monaco")
weekend.plot() # Clean white track
weekend.plot(color_mode="speed") # Colored by speed
weekend.plot(color_mode="sectors") # Marshal sectors
weekend.plot(save_path="monaco.png") # Save to file
Color modes: white, sectors, speed, throttle, brake, height
CLI
f1-replay 2024 monaco # Race replay (shorthand)
f1-replay 2024 8 # By round number
f1-replay race 2024 monaco -p 9000 # Custom port
f1-replay seasons 2024 # List races
f1-replay config --set-cache-dir /data # Set cache location
Documentation
Full documentation at f1-replay.readthedocs.io
- Usage Guide -- Loading data, circuit plots, race viewer, telemetry, CLI, REST API
- Python API Reference -- Auto-generated method documentation
- Architecture -- Data pipeline, caching strategy, frontend design
- Telemetry Reference -- Column definitions, units, processing pipeline
Development
git clone https://github.com/kkollsga/f1-replay.git && cd f1-replay
make install # pip install -e ".[dev,all]"
make check # lint + tests (196 tests)
make docs # build Sphinx documentation
See CONTRIBUTING.md for the full development guide.
Requirements
- Python 3.9+
- FastF1, Flask, Polars, NumPy, SciPy, Pandas
- Optional: matplotlib (circuit plots), orjson (faster JSON), flask-cors
License
MIT
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