Парсинг сайта для сбора данных. Есть код который должен партсить сайт, но при его запуске ничего не происходит

import os
import csv
import requests
import json

import numpy as np

from bs4 import BeautifulSoup
from multiprocessing import Pool
from pathlib import Path
from datetime import datetime

GRABBER_ROOT = './Data'
CORES_NUMBER = 20
TRIP_ADVISOR_URL_TEMPLATE = 'https://tripadvisor.com{}'


def parse_ratings_and_reviews(node, result):
    rating_block = node.find('div').findAll('div', recursive=False)
    if len(rating_block) < 3:
        return result
    rating_block = rating_block[2].findAll('div', recursive=False)
    if len(rating_block) < 2:
        return

    ratings = rating_block[1].findAll('div')
    for rating in ratings:
        spans = rating.findAll('span', recursive=False)
        title = spans[1].text.lower()
        value = spans[2].find('span').attrs['class'][1].split('_')[1]
        result[title] = int(value)


def parse_location_and_contact(node):
    location_block = node.find('div').find('div')
    location_block = location_block.findAll('div', recursive=False)[1]
    distance_el = location_block.find('b')
    if distance_el is None:
        return np.NaN
    return float(distance_el.text.split()[0])


def parse_details_block(node, result):
    if node is None:
        return

    result['is_verified'] = 1 if node.find(
        'span', {'class': 'ui_icon verified-checkmark'}) is not None else 0
    result['has_phone_number'] = 1 if node.find(
        'a', string='+ Add phone number') is None else 0
    result['has_hours'] = 1 if node.find(
        'a', string='+ Add hours') is None else 0
    result['has_website'] = 1 if node.find(
        'a', string='+ Add website') is None else 0
    result['has_menu'] = 1 if node.find('a', string='Menu') is not None else 0


def collect_page_data(html, result):
    soup = BeautifulSoup(html, features="lxml")
    overview_tabs = soup.find('div', {'data-tab': 'TABS_OVERVIEW'})
    if overview_tabs is None:
        return

    overview_columns = overview_tabs.findAll('div', {'class': 'ui_column'})
    parse_ratings_and_reviews(overview_columns[0], result)
    parse_details_block(overview_columns[1], result)

    result['distance'] = parse_location_and_contact(overview_columns[2])
    result['has_tcAward'] = 1 if soup.find(
        'img', {'class': 'tcAward'}) is not None else 0


def grab_pages(records):
    for record in records:
        ta_url = TRIP_ADVISOR_URL_TEMPLATE.format(record['ta_url'])
        print(ta_url)
        r = requests.get(ta_url, stream=True)
        collect_page_data(r.text, record)
    return records


def parallelize_processing(records):
    pool = Pool(CORES_NUMBER)
    splitted_recs = np.array_split(records, CORES_NUMBER)
    grabbed_data = pool.map(grab_pages, splitted_recs)
    pool.close()
    pool.join()
    return np.concatenate(grabbed_data)


def read_records(filrname):
    file_path = '{}/{}/{}'.format(GRABBER_ROOT, 'urls', filename)
    records = list()
    with open(file_path) as csvfile:
        filereader = csv.reader(csvfile)
        for row in filereader:
            row_obj = {}
            row_obj['id'] = row[0]
            row_obj['ta_id'] = row[1]
            row_obj['ta_url'] = row[2]
            records.append(row_obj)
    return records


def process_file(filename):
    if not filename.endswith('.csv'):
        return

    print(filename)

    data_file_name = '{}_d.json'.format(
        filename.split('/')[-1].split('.')[0])
    data_file_path = '{}/{}'.format(GRABBER_ROOT, data_file_name)

    records = read_records(filename)
    records_data = parallelize_processing(records)

    with open(data_file_path, "w") as write_file:
        json.dump(records_data.tolist(), write_file)


for dirname, _, filenames in os.walk('{}/{}'.format(GRABBER_ROOT, 'urls')):
    for filename in filenames:
        process_file(os.path.join(dirname, filename))