average_race_pace.py

import json
import os

import fastf1
import numpy as np
import pandas as pd
import requests

YEAR = 2021


events = [
    'Bahrain Grand Prix', 

  'Emilia Romagna Grand Prix', 
    'Portuguese Grand Prix', 'Spanish Grand Prix', 'Monaco Grand Prix', 
    'Azerbaijan Grand Prix', 'French Grand Prix', 'Styrian Grand Prix',
    'Austrian Grand Prix', 'British Grand Prix', 'Hungarian Grand Prix', 
    'Belgian Grand Prix', 'Dutch Grand Prix', 'Italian Grand Prix',
    'Russian Grand Prix', 'Turkish Grand Prix', 
    'United States Grand Prix',
    'Mexico City Grand Prix', 
    'São Paulo Grand Prix', 'Qatar Grand Prix', 
    'Saudi Arabian Grand Prix', 'Abu Dhabi Grand Prix', 
]

def average_race_pace(
    year: int,
    event: str | int,
    session: str,
) -> any:
    f1session = fastf1.get_session(
        year,
        event,
        session,
        # backend="fastf1",
        # force_ergast=False,
    )
    f1session.load(telemetry=False, weather=False, messages=False)
    laps = f1session.laps

    laps = laps.loc[laps.LapNumber > 1]
    laps = laps.pick_track_status(
        "1",
    )
    laps["LapTime"] = laps.Sector1Time + laps.Sector2Time + laps.Sector3Time

    # convert LapTime to seconds
    laps["LapTime"] = laps["LapTime"].apply(lambda x: x.total_seconds())

    laps = laps.loc[laps.LapTime < laps.LapTime.min() * 1.07]

    df = laps[["LapTime", "Driver"]].groupby("Driver").mean().reset_index(drop=False)
    df = df.sort_values(by="LapTime").reset_index(drop=True)
    df["LapTime"] = df["LapTime"].round(3)
    df["Diff"] = (df["LapTime"] - df["LapTime"].min()).round(3)
    teams = laps[["Driver", "Team"]].drop_duplicates().reset_index(drop=True)
    # join teams and df
    df = df.merge(teams, on="Driver", how="left")

    # car_colors = utils.team_colors(year)

    # df["fill"] = df["Team"].map(car_colors)

    df_json = df.to_dict("records")

    return {"racePace": df_json}


# Your list of events
events_list = events

# Loop through each event
for event in events_list:
    session = "Race"

    race_pace_dict = average_race_pace(YEAR, event, session)

    # Specify the file path where you want to save the JSON data
    file_path = f"{event}/{session}/average_race_pace.json"

    # Save the dictionary to a JSON file
    with open(file_path, "w") as json_file:
        json.dump(race_pace_dict, json_file)

    print(f"Dictionary saved to {file_path}")