import Data_Analysis as DA
import pandas as pd
import os



propIds = DA.getuniquePropIdFromDB()

for propId in propIds:
    name = f"dok/calendarData_prop{propId}.csv"
    if not os.path.exists(name):
        print(propId)
        scrapeDates, calendarData = DA.getDataFromDB(propId)
        if DA.checkForLostProprty(calendarData):
            print(f"Lost Proprty: {propId}")
        else:
            scrapeDates = DA.reformatScrapeDates(scrapeDates)
            HeaderDates = DA.getMinMaxDate(calendarData)
            data = DA.creatDataMatrix(HeaderDates, calendarData)

            # Transform to Dataframe for Plotly
            df = pd.DataFrame(data, columns=HeaderDates)
            df.insert(0, "ScrapeDate", scrapeDates, True)

            df = df.drop(index=0)  # Irregulärer Abstand in den Scraping Zeiten (nur 2 Tage)
            df = df.drop(df.columns[[1, 2]], axis=1)
            df.to_csv(name, index=False)