我需要抓取一个存储在CSV文件中的URL列表并导出到另一个CSV文件中。我必须犯一些错误，因为我不能运行它。所以，如果有人能帮助我，我很感激。
我是Python的新手，也合并了一些代码，所以我有一些问题要找出问题在哪里。我混合了一个导入CSV的代码和另一个需要字符串搜索的代码。

import scrapy
    from scrapy import Spider
    from scrapy import Request
    from scrapy.crawler import CrawlerProcess
    from bs4 import BeautifulSoup
    from urllib.parse import urlparse
    import requests
    import pandas as pd
    from bs4 import BeautifulSoup
    from urllib.request import urlopen,urlparse, Request,HTTPError
    import re
    import numpy as np
    import csv
    from http.client import BadStatusLine
    import ssl

下面是我目前所拥有的代码。

phn_1 = []
    zipcode_1 = []
    err_msg_zipcode = []
    err = []

    class Spider:
      name = 'spider'

        # read csv with just url per line
      with open('urls.csv') as file:
          start_urls = [line.strip() for line in file]

      def start_request(self):
          request = Request(url = self.start_urls, callback=self.parse)
          yield request

      def parse(self, response):

          s = response.body
          soup = BeautifulSoup(html, 'lxml')
          text = soup.get_text()

          df2=pd.DataFrame()

          phn_1 = []    #store all the extracted Phn numbers in a List
          mail_1 = []    #store all the extracted Zipcode in a List
          for line in df2.iterrows():  # Parse through each url in the list.
              try:
                  try:
                      req1 = Request(row[1]['URL'], headers={'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.75 Safari/537.36'})
                      gcontext = ssl.SSLContext(ssl.PROTOCOL_SSLv23) # Bypass SSL certification verification
                      f = urlopen(req1, context=gcontext)
                      url_name = f.geturl() #extract URL name 
                      s = f.read()
                      phone = re.findall(r'\d{3}-\d{3}-\d{4}', s, re.MULTILINE)
                      zipcode = re.findall(r'(?<=, [A-Z]{2} )\d{5}', s, re.MULTILINE)

                      if len(phone) == 0:
                          print("No phone number found.")
                          err_msg_phn = "No phone number found."
                          phn_1.append((url_name, err_msg_phn))

                      else:
                          count = 1
                          for item in phone:
                              phn_1.append((url_name,item))
                              count += 1
                          print(phn_1)

                      if len(zipcode) == 0:
                          print("No zipcode found.")
                          err_msg_zipcode = "No zipcode address found."
                          zipcode_1.append((url_name,err_msg_zipcode))

                      else:
                          count = 1
                          for item in zipcode:
                              mail_1.append((url_name,item))
                              count += 1
                          print(mail_1)

                  except BadStatusLine: # Catch if invalid url names exist
                      print("could not fetch %s" % url_name)

              except urllib3.request.HTTPError as err: # catch HTTP 404 not found error
                  if err == 404:
                      print("Received HTTPError on %s" % url_name)

    df_p = pd.DataFrame()
    df_m = pd.DataFrame()
    df_final = pd.DataFrame()

    df_p = pd.DataFrame(phn_1,columns=['URL','Phone_No']) # Dataframe for url and Phn number
    df_phn = df_p.drop_duplicates(subset=['URL', 'Phone_No'], keep='first') #remove duplicates

    df_m = pd.DataFrame(zipcode_1,columns=['URL','Zipcode']) # Dataframe for url and Zipcode
    df_mail = df_m.drop_duplicates(subset=['URL','Zipcode'], keep='first') #remove duplicates

    df_final = pd.merge(df_phn,df_mail, on = 'URL', how = 'inner') #Merge two dataframes on the common column
    #df_final.groupby(['URL'], as_index=False)
    df_final.to_csv('result_contact.csv', index=False, encoding='utf-8')

    #convert the csv output to json
    with open('result_contact.csv') as f:
         reader = csv.DictReader(f)
         rows = list(reader)

谢谢你们！