刮取网址的CSV列表并将结果输出到不同的CSV

Question

我正试图从'YP_LA_Remodel_urls.csv文件中提取网址（我在下面包含了几个），抓取它们，然后将结果导出到Yp_LA_Remodel_Info.csv。

如果我拿一个网址（不是来自csv）并刮掉它，那么它工作正常。它只是试图以大规模的方式进行，我已经被挂断了。我已经创建了我需要提取的信息列表。

我正在使用我构建的另一个抓取的脚本，它似乎不适用于这个。我是一个蟒蛇菜鸟，所以放轻松。

任何帮助和/或建议表示赞赏。

示例网址：

https://www.yellowpages.com/search?search_terms=remodeling&geo_location_terms=Los%20Angeles%2C%20CA&page=1
https://www.yellowpages.com/search?search_terms=remodeling&geo_location_terms=Los%20Angeles%2C%20CA&page=2

脚本：

import csv
from urllib.request import urlopen
import pandas as pd
from bs4 import BeautifulSoup
from email import encoders
import time
import os
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.base import MIMEBase
import requests


def license_exists(soup):
    contents = []
    with open('YP_LA_Remodel_urls.csv','r') as csvf:
        urls = csv.reader(csvf)
        for url in urls:
            if soup(class_="next ajax-page"):
                return True
            else:
                return False

records = []
with open('YP_LA_Remodel_urls.csv') as f_input, open('Yp_LA_Remodel_Info.csv', 'w', newline='')  as f_output:
    csv_input = csv.reader(f_input)
    csv_output = csv_output_to_csv(f_output, fieldnames=[name for name, result in records])
    csv_output.writeheader()

    for url in csv_input:
        r = requests.get(url[0])        # Assume the URL is in the first column
        soup = BeautifulSoup(r.text, "html.parser")
        results = soup.find_all('div', attrs={'class':'info'})
        csv_output.to_csv('f_output', index=False, encoding='utf-8')


    for result in results:
        biz_name = result.find('span', attrs={'itemprop':'name'}).text if result.find('span', attrs={'itemprop':'name'}) is not None else ''
        biz_phone = result.find('div', attrs={'itemprop':'telephone'}).text if result.find('span', attrs={'itemprop':'telephone'}) is not None else ''
        biz_address = result.find('span', attrs={'itemprop':'streetAddress'}).text if result.find('span', attrs={'itemprop':'streetAddress'}) is not None else ''
        biz_city = result.find('span', attrs={'itemprop':'addressLocality'}).text if result.find('span', attrs={'itemprop':'addressLocality'}) is not None else ''
        biz_zip = result.find('span', attrs={'itemprop':'postalCode'}).text if result.find('span', attrs={'itemprop':'postalCode'}) is not None else ''
        records.append((biz_name, biz_phone, biz_address, biz_city, biz_zip))

df = pd.DataFrame(records, columns=['biz_name', 'biz_phone', 'biz_address', 'biz_city', 'biz_zip'])