from bs4 import BeautifulSoup
import requests
import datetime
import os
import pandas as pd
from icecream import ic


def get_names(soup):
    # ic(soup)
    return [_.text.strip() for _ in soup.find_all('h2') if 'manger à' not in _.text][:-1]


def get_number_of_pages(soup):
    return int([_.text for _ in soup.find_all('ul')][13][-3:-1])


def get_prices(soup):
    prices = [_.text.strip() for _ in soup.find_all('div') if ' • €' in _.text]
    prices_v2 = []
    for price in prices:
        x = price.find(' • €')
        prices_v2.append(price[x+3:x+8].strip())
    return [prices_v2[_] for _ in range(0, len(prices_v2[6:])+7, 6)][1:]


def get_url(soup):
    links = [str(_) for _ in soup.find_all('a') if '.html' in str(_) and 'https:' not in str(_)][1:-1]
    links_v2 = []
    for link in links:
        x = link.find('.html')+5
        links_v2.append(link[:x].split('href')[-1][3:])

    links_v3 = []
    for link in links_v2:
        if 'https://www.petitfute.com/' + link not in links_v3:
            links_v3.append('https://www.petitfute.com/' + link)

    return links_v3


def get_addresses(soup):
    urls = get_url(soup)
    addresses = []
    for url in urls:
        # ic()
        page = requests.get(url)
        soup2 = BeautifulSoup(page.text, features='html.parser')

        all_span = [_.text for _ in soup2.find_all('span')]
        try:
            address = (('' + all_span[all_span.index('Paris,')-2] + all_span[all_span.index('Paris,')-1]).
                       replace(',', ' ').replace('  ', ' '))
        except ValueError:
            address = ''

        # Deal with word before the street number
        if not address.split(' ')[0].isdigit():
            address_piece_by_piece = address.split(' ')
            for i in range(len(address_piece_by_piece)):
                try:
                    if address_piece_by_piece[i][0].isdigit():
                        address = ' '.join(address_piece_by_piece[i:])
                        break
                except IndexError:
                    pass

        # Deal with double street numbers (keep only the first number)
        if '-' in address[:5]:
            address = address.split('-')[0] + ' ' + ' '.join(address.split(' ')[1:])

        # Deal with abbreviation
        address = address.replace('Av.', 'avenue').replace('bis ', '')

        # ic(address)
        addresses.append(address)
    return addresses


def scrap(soup):
    ic()
    df = pd.DataFrame(columns=['Name', 'Date', 'Address', 'Price',])
    df['Name'] = get_names(soup)
    # ic(len(get_names(soup)))
    df['Date'] = datetime.date.today()
    try:
        df['Address'] = get_addresses(soup)
        # ic(len(get_addresses(soup)))
    except ValueError:
        ic(get_names(soup))
        ic(get_addresses(soup))
    try:
        df['Price'] = get_prices(soup)
        # ic(len(get_prices(soup)))
    except ValueError:
        ic(get_names(soup))
        ic(get_prices(soup))

    for name in df['Name']:
        newpath = '/Users/oliviermeyer/Desktop/CREST/Web Scraping/HTML/Petit Fute/' + str(datetime.date.today())
        if not os.path.exists(newpath):
            os.makedirs(newpath)

        try:
            html_path = ('/Users/oliviermeyer/Desktop/CREST/Web Scraping/HTML/Petit Fute/' +
                         str(datetime.date.today()) + '/' + name.replace('/', '-') + '.html')

            with open(html_path, 'wt', encoding='utf-8') as html_file:
                for line in soup.prettify():
                    html_file.write(line)
        except AttributeError:
            ic()
    # print(df)
    return df


def complete_scraping():
    url = 'https://www.petitfute.com/d3-paris/c1165-restaurants/'
    page = requests.get(url)
    soup = BeautifulSoup(page.text, features='html.parser')

    df = scrap(soup)

    number_of_pages = get_number_of_pages(soup)
    for i in range(number_of_pages+1):
        # try:
        new_url = url + '?page=' + str(i)
        new_page = requests.get(new_url)
        new_soup = BeautifulSoup(new_page.text, features='html.parser')
        temporary_df = scrap(new_soup)
        df = pd.concat([df, temporary_df], ignore_index=True)
        # print(df.to_string())
        # except ValueError:
        #     pass

    df = df.dropna(subset='Address')

    prices = df['Price']
    for i in range(len(prices)):
        if not pd.isna(prices[i]):
            if prices[i].replace('€', '') != '':
                prices[i] = prices[i].split(' ')[0]

    return df