Quickstart

import tif1

# Get the 2025 abu dhabi grand prix race session
session = tif1.get_session(2025, "Abu Dhabi Grand Prix", "Race")

# Load all laps
laps = session.laps

# View driver information
print(session.drivers_df[["Driver", "Team", "DriverNumber"]])

# Get the top 5 fastest laps in the session
fastest_5 = laps.nsmallest(5, "LapTime")
print(fastest_5[["Driver", "LapTime", "Compound"]])

# Get driver data for Max Verstappen
ver = session.get_driver("VER")

# Get his fastest lap
fastest_lap = ver.get_fastest_lap()
print(f"Max's fastest lap: {fastest_lap['LapTime'].iloc[0].total_seconds():.3f}s")

# Get telemetry for lap 19
lap_19 = ver.get_lap(19)
telemetry = lap_19.telemetry

# Check his top speed on that lap
top_speed = telemetry["Speed"].max()
print(f"Top Speed on Lap 19: {top_speed} km/h")

# List all GPs in 2025
events = tif1.get_events(2025)

# List all sessions for a GP
sessions = tif1.get_sessions(2025, "British Grand Prix")
# ['Practice 1', 'Practice 2', 'Practice 3', 'Qualifying', 'Race']

import matplotlib.pyplot as plt
import tif1

# One call: loads the session, computes team maxima, and plots
fig, ax = tif1.plot_top_speeds(2025, "Abu Dhabi Grand Prix", "Qualifying")
plt.show()

# Or save straight to a file — all 22 charts work the same way
tif1.plot_track_speed_map(2025, "Monaco Grand Prix", "Qualifying", save_path="speed_map.png")

import asyncio

async def main():
    session = tif1.get_session(2025, "Monaco Grand Prix", "Race")
    laps = await session.laps_async()
    print(f"Loaded {len(laps)} laps")

asyncio.run(main())