f1-replay 0.1.14

Formula 1 Race Replay and Visualization Library

f1-replay

A Python toolkit for Formula 1 data analysis and visualization. Built on FastF1 with intelligent caching, schedule tools, circuit plotting, and interactive race replay.

Installation

pip install f1-replay

Quick Start

from f1_replay import Manager

mgr = Manager()

# Launch interactive race replay
mgr.race(2024, "monaco")

# Browse season schedule
mgr.season_schedule(2024)

# Load and explore data
weekend = mgr.load_weekend(2024, "monaco")
session = mgr.load_race(2024, "monaco")

# Access telemetry
session.telemetry["VER"]       # Polars DataFrame
session.drivers                # ["VER", "NOR", "LEC", ...]

# Generate circuit poster
weekend.plot(color_mode="speed")

Features

• 3-Tier Data Management -- Hierarchical caching for seasons, weekends, and sessions with automatic pickle storage
• Schedule Tools -- Query race calendars, browse events, resolve races by name or round number
• Circuit Plotting -- Poster-style track maps with speed, throttle, brake, height, and sector coloring
• Race Replay -- Interactive 2D viewer with animated car positions, live standings, strategy panel, track status overlays, rain effects, and race control messages

CLI

f1-replay race 2024 monaco              # Launch race replay
f1-replay race 2024 8 --port 8080       # By round number
f1-replay seasons 2024                  # List races
f1-replay server                        # API server only
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, CLI reference, 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