import fastf1
import pandas as pd
from pandas import DataFrame
from fastapi import HTTPException
def get_latest_session():
path_parts = []
next_event = fastf1.get_events_remaining().iloc[0]
if next_event["EventFormat"] == "testing":
type_event = "pretest"
n_event = 1
practices = ["1","2","3"]
session = [int(p)-1 for p in practices if p in next_event["Session"]]
else:
type_event = "official"
n_event = int(next_event["RoundNumber"]) - 1
session = "R"
event_date = next_event["EventDate"]
year = event_date.year
path_parts.extend([type_event, year, n_event, session])
return path_parts
def get_session(type_event:str=None, year:int=None, event:int=None, session:str=None, latest_sesion:bool=False):
if latest_sesion:
type_event, year, event, session = get_latest_session()
if type_event == "official":
session = fastf1.get_session(year, event, session)
elif type_event == "pretest":
session = fastf1.get_testing_session(year, event, session)
session.load()
return session
def get_laps(type_event:str, year:int, event:int, session:str, driver:str=None):
session = get_session(type_event, year, event, session)
if len(session.drivers) == 0:
raise HTTPException(status_code=404, detail="No laps found for this session.")
laps = session.laps
laps["LapTime"] = pd.to_timedelta(laps["LapTime"])
if driver: laps = laps.pick_drivers(driver)
return laps
def get_specific_lap(laps:DataFrame, lap_number:int = -1, get_personal_fastest_lap: bool = False, get_general_fastest_lap:bool = False):
if (get_general_fastest_lap or get_personal_fastest_lap) and (lap_number == -1):
lap = laps.pick_fastest()
else:
lap = laps.pick_laps(lap_number)
return lap
