from selenium import webdriver
from bs4 import BeautifulSoup
import time
from icecream import ic


# Google scraping for restaurants in Le Fooding
def google_scrap_fooding(df):
    price_ranges = []

    for i in range(len(df['Name'])):
        name = df.iloc[i]['Name']
        address = df.iloc[i]['Address']

        options = webdriver.ChromeOptions()
        options.add_argument("---headless=True")
        driver = webdriver.Chrome(options=options)
        base_url = 'https://www.google.com/search?hl=en&q='

        url = base_url + str(name).replace(' ', '-') + str(address).replace(' ', '-')
        ic()
        ic(name)

        driver.get(url)
        time.sleep(0.1)

        page_source = driver.page_source
        driver.quit()
        soup = BeautifulSoup(page_source, features='html.parser')

        all_span = [_.text for _ in soup.find_all('span')]

        price_range = ''.join([_ for _ in all_span if '€' in _ and '–' in _]).split('...')[-1][1:].split('€')[0]
        ic(price_range)

        if len(price_range) < 8:
            price_ranges.append(price_range)
        else:
            price_ranges.append('')

    df['Price Range'] = price_ranges

    return df


def get_price_range_fute(soup):
    price_range = (''.join([_.text for _ in soup.find_all('span') if 'Reported by' in _.text]).
                   strip().split('R')[0].split('€')[-1])

    if price_range == '':
        all_span = [_.text for _ in soup.find_all('span')]
        price_range = [_ for _ in all_span if '· Prix. de' in _]
        price_range = ''.join(price_range).split('€')[0].split('· Prix. de')[-1].strip()

    return price_range


# Google scraping for restaurants in Petit Fute
def get_mean_price_fute(soup):
    mean_price = [_.text for _ in soup.find_all('span') if '(Les prix ont été fournis par le restaurant)' in _.text]
    mean_price = ''.join(mean_price).split('€')[0].split('Price range: ')[-1].strip()
    return mean_price


def google_scrap_fute(df):
    price_ranges = []
    mean_prices = []

    ic()
    for name, address in zip(df['Name'], df['Address']):
        ic()
        ic(name)
        options = webdriver.ChromeOptions()
        options.add_argument("---headless=True")
        driver = webdriver.Chrome(options=options)
        base_url = 'https://www.google.com/search?hl=en&q='
        try:
            url = base_url + name.replace(' ', '-') + address.replace(' ', '-')
            driver.get(url)
            time.sleep(0.1)

            page_source = driver.page_source
            driver.quit()
            soup = BeautifulSoup(page_source, features='html.parser')

            price_range = get_price_range_fute(soup)
            ic(price_range)
            mean_price = get_mean_price_fute(soup)
            ic(mean_price)
            price_ranges.append(price_range)
            mean_prices.append(mean_price)

        except AttributeError or ConnectionError:
            ic()
            price_ranges.append('NA')
            mean_prices.append('NA')

    df['Price Range'] = price_ranges
    df['Mean Price'] = mean_prices

    return df