调用text.strip()时出现以下错误：

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-278-135ac185ec3f> in <module>
     20         if isinstance(b, Tag):
     21 
---> 22             location = [a.text.strip() for a in b.find('span', attrs = {'class': 'location'})]
     23             job_title = [a.text.strip() for a in b.find('a', attrs = {'data-tn-element':'jobTitle'})]
     24 

TypeError: 'NoneType' object is not iterable

请看下面的代码：

import requests
from bs4 import BeautifulSoup, NavigableString, Tag, Comment
import pandas as pd

    df = pd.DataFrame(columns=["location", 'company', 'job_title', 'salary'])

    for start in range(1,100,10):
        url = 'https://www.indeed.com/jobs?q=python+sql&l=San+Francisco&start={}'

        #format url above to request the various search pages
        new_url = url.format(start)

        #conducting a request of the stated URL above:
        page = requests.get(new_url)

        #specifying a desired format of “page” using the html parser - this allows python to read the various components of the page, rather than treating it as one long string.
        soup = BeautifulSoup(page.text, 'html.parser')

        #loop through the tag elements
        for b in soup.find_all(name = 'div', attrs={'class':'jobsearch-SerpJobCard'}):
            print(type(b))
            if isinstance(b,NavigableString):
                continue
            if isinstance(b, Tag):    

                location = [a.text.strip() for a in b.find('span', attrs = {'class': 'location'})]
                job_title = [a.text.strip() for a in b.find('a', attrs = {'data-tn-element':'jobTitle'})]

                try:
                    company = [a.text.strip() for a in b.find('span', attrs = {'class':'company'})]
                except:
                    company = 'NA'
                try:
                    salary = [a.text.strip() for a in b.find('span', attrs = {'class' : 'salaryText'}).find('nobr')]
                except:
                    salary = 'NA'
                df = df.append({"location":location,"company":company, "job_title": job_title, "salary": salary}, ignore_index=True)