Update main.py

main.py

@@ -1,89 +1,20 @@
 import fastf1
 import pandas as pd
 from fastapi import FastAPI
-from fastapi.responses import FileResponse, HTMLResponse
-from pydantic import BaseModel
 
-app = FastAPI()
-
-
-# class Laps(BaseModel):
-#     Time: pd.Timedelta
-#     Driver: str
-#     DriverNumber: str
-#     LapTime: pd.Timedelta
-#     LapNumber: int
-#     Stint: int
-#     PitOutTime: pd.Timedelta
-#     PitInTime: pd.Timedelta
-#     Sector1Time: pd.Timedelta
-#     Sector2Time: pd.Timedelta
-#     Sector3Time: pd.Timedelta
-#     Sector1SessionTime: pd.Timedelta
-#     Sector2SessionTime: pd.Timedelta
-#     Sector3SessionTime: pd.Timedelta
-#     SpeedI1: float
-#     SpeedI2: float
-#     SpeedFL: float
-#     SpeedST: float
-#     IsPersonalBest: bool
-#     Compound: str
-#     TyreLife: float
-#     FreshTyre: bool
-#     Team: str
-#     LapStartTime: pd.Timedelta
-#     LapStartDate: pd.Timestamp
-#     TrackStatus: str
-#     IsAccurate: bool
-#     # https://stackoverflow.com/questions/65412984/using-pandas-data-frame-as-a-type-in-pydantic
 
-#     class Config:
-#         arbitrary_types_allowed = True
 
-
-class Laps(BaseModel):
-    Time: pd.core.frame.DataFrame
-    Driver: pd.core.frame.DataFrame
-    DriverNumber: pd.core.frame.DataFrame
-    LapTime: pd.core.frame.DataFrame
-    LapNumber: pd.core.frame.DataFrame
-    Stint: pd.core.frame.DataFrame
-    PitOutTime: pd.core.frame.DataFrame
-    PitInTime: pd.core.frame.DataFrame
-    Sector1Time: pd.core.frame.DataFrame
-    Sector2Time: pd.core.frame.DataFrame
-    Sector3Time: pd.core.frame.DataFrame
-    Sector1SessionTime: pd.core.frame.DataFrame
-    Sector2SessionTime: pd.core.frame.DataFrame
-    Sector3SessionTime: pd.core.frame.DataFrame
-    SpeedI1: pd.core.frame.DataFrame
-    SpeedI2: pd.core.frame.DataFrame
-    SpeedFL: pd.core.frame.DataFrame
-    SpeedST: pd.core.frame.DataFrame
-    IsPersonalBest: pd.core.frame.DataFrame
-    Compound: pd.core.frame.DataFrame
-    TyreLife: pd.core.frame.DataFrame
-    FreshTyre: pd.core.frame.DataFrame
-    Team: pd.core.frame.DataFrame
-    LapStartTime: pd.core.frame.DataFrame
-    LapStartDate: pd.core.frame.DataFrame
-    TrackStatus: pd.core.frame.DataFrame
-    IsAccurate: pd.core.frame.DataFrame
-    # https://stackoverflow.com/questions/65412984/using-pandas-data-frame-as-a-type-in-pydantic
-
-    class Config:
-        arbitrary_types_allowed = True
+app = FastAPI()
 
 
 @app.get("/")
 async def root():
     return {"message": "Hello World"}
 
-
-# create a function that returns laps dataframe given year, race ,session from fastf1
-
 @app.get("/{year}/{race}/{session}", response_model=None)
 async def get_data(year: int, race: int, session: str) -> any:
+
+    fastf1.Cache.enable_cache('/Cache')
     
     f1session = fastf1.get_session(year, race, session)
     f1session.load(telemetry=False, weather=False, messages=False)
@@ -93,16 +24,6 @@ async def get_data(year: int, race: int, session: str) -> any:
     laps['Sector2Time'] = laps['Sector2Time'].dt.total_seconds()
     laps['Sector3Time'] = laps['Sector3Time'].dt.total_seconds()
     laps['LapTime_in_seconds'] = laps['LapTime'].dt.total_seconds()
-    laps['laptime_sum_sectortimes'] = laps.Sector1Time + laps.Sector2Time + laps.Sector3Time
-
-    # # convert laps to csv
-    # laps.to_csv('laps.csv', index=False)
-    # return laps
-
-    # in laps replace NaN with ""
-    laps = laps.fillna(" ")
+    laps['laptime_sum_sectortimes'] = laps.Sector1Time + laps.Sector2Time + laps.Sector3Time      
     
-    return {"laps": laps.to_dict(orient='records')}
-
-    # return FileResponse(path='laps.csv', filename='laps.csv')
-    # return HTMLResponse(content=laps.to_html(), status_code=200)
+    return {"laps": laps.to_json(orient='records')}