prix_restos/main.py
2024-06-28 10:37:57 +02:00

47 lines
1.6 KiB
Python

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()