import best_restaurants_scraping_v2
import gault_et_millau_scraping_v2
import le_fooding_scraping
import petit_fute_scraping_v2
import resto_de_paris_scraping
import google_scraping

import datetime
from icecream import ic


def main():
    # Choose desired path to export scraped data
    desired_path = '/Users/oliviermeyer/Desktop/'

    # Initial scraping
    df1 = best_restaurants_scraping_v2.complete_scraping()
    # df2 = gault_et_millau_scraping_v2.complete_scraping()
    df3_1 = le_fooding_scraping.complete_scraping()
    df4_1 = petit_fute_scraping_v2.complete_scraping()
    df5 = resto_de_paris_scraping.complete_scraping()

    # Google scraping for dataframe without menus
    df3_2 = google_scraping.google_scrap_fooding(df3_1)
    df4_2 = google_scraping.google_scrap_fute(df4_1)

    # Get today's date in string
    date = str(datetime.date.today())

    # Export all the dataframes
    df1.to_csv(desired_path + 'best_restaurants_' + date + '.csv', index=False, header=True, escapechar='\\')
    # df2.to_csv(desired_path + 'gault_et_millau_' + date + '.csv', index=False, header=True, escapechar='\\')
    df3_2.to_csv(desired_path + 'le_fooding_' + date + '.csv', index=False, header=True, escapechar='\\')
    df4_2.to_csv(desired_path + 'petit_fute_' + date + '.csv', index=False, header=True, escapechar='\\')
    df5.to_csv(desired_path + 'resto_de_paris_' + date + '.csv', index=False, header=True, escapechar='\\')


# List of days that have been processed
done_dates = []

# Call the main function every new day
while True:
    today = datetime.date.today()
    if today not in done_dates:
        ic()
        main()