Scraping Yellow pages with Python and BeautifulSoup

Today lets look at scraping Yellow pages data using Beautiful soup and the requests module in python.

Here is a simple script that does that. BeautifulSoup will help us extract information and we will retrieve crucial pieces of information.

To start with, this is the boilerplate code we need to get the Yellowpages.com search results page and set up BeautifulSoup to help us use CSS selectors to query the page for meaningful data.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests
headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url = 'https://www.yellowpages.com/los-angeles-ca/dentists'
response=requests.get(url,headers=headers)
soup=BeautifulSoup(response.content,'lxml')

We are also passing the user agent headers to simulate a browser call so we dont get blocked.

Now let’s analyze the Yellow pages search results. This is how it looks.

And when we inspect the page we find that each of the items HTML is encapsulated in a tag with the class v-card.

We could just use this to break the HTML document into these cards which contain individual item information like this.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests
headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url = 'https://www.yellowpages.com/los-angeles-ca/dentists'
response=requests.get(url,headers=headers)
soup=BeautifulSoup(response.content,'lxml')
for item in soup.select('.v-card'):
try:
print('----------------------------------------')
print(item)

And when you run it.

python3 scrapeYellow.py

You can tell that the code is isolating the v-cards HTML.

On further inspection, you can see that the name of the place always has the class business-name. So let’s try and retrieve that.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests
headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url = 'https://www.yellowpages.com/los-angeles-ca/dentists'
response=requests.get(url,headers=headers)
soup=BeautifulSoup(response.content,'lxml')
for item in soup.select('.v-card'):
try:
print('----------------------------------------')
print(item.select('.business-name')[0].get_text())
except Exception as e:
#raise e
print('')

That will get us the names.

Bingo!

Now let’s get the other data pieces.

# -*- coding: utf-8 -*-
from bs4 import BeautifulSoup
import requests
headers = {'User-Agent':'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_2) AppleWebKit/601.3.9 (KHTML, like Gecko) Version/9.0.2 Safari/601.3.9'}
url = 'https://www.yellowpages.com/los-angeles-ca/dentists'
response=requests.get(url,headers=headers)
soup=BeautifulSoup(response.content,'lxml')
for item in soup.select('.v-card'):
try:
print('----------------------------------------')
print(item.select('.business-name')[0].get_text())
print(item.select('.rating div')[0]['class'])
print(item.select('.rating div span')[0].get_text())
print(item.select('.phone')[0].get_text())
print(item.select('.adr')[0].get_text())
#print(item.select('.business-name')[0].get_text())
print('----------------------------------------')
except Exception as e:
#raise e
print('')

And when run.

Produces all the info we need including ratings, reviews, phone, address, etc.

In more advanced implementations you will need to even rotate the User-Agent string so Yellow pages cant tell its the same browser!

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The blog was originally posted at https://www.proxiesapi.com/blog/scraping-yellow-pages-with-python-and-beautifulsou.html.php