One of the biggest applications of Web Scraping is in scraping hotel listings from various sites. This could be to monitor prices, create an aggregator, or provide better UX on top of existing hotel booking websites.
Here is a simple script that does that. We will use BeautifulSoup to help us extract information and we will retrieve hotel information on Booking.com.
To start with, this is the boilerplate code we need to get the Booking.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.booking.com/searchresults.html?label=gen173nr-1FCAEoggI46AdIM1gEaGyIAQGYATG4AQfIAQzYAQHoAQH4AQKIAgGoAgO4AvTIm_IFwAIB;sid=7101b3fb6caa095b7b974488df1521d2;city=-2109472;from_idr=1&;dr_ps=IDR;ilp=1;d_dcp=1'
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 Booking.com search results for a destination we want. 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 sr_property_block.
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.booking.com/searchresults.html?label=gen173nr-1FCAEoggI46AdIM1gEaGyIAQGYATG4AQfIAQzYAQHoAQH4AQKIAgGoAgO4AvTIm_IFwAIB&sid=eae1a774e77c394c5e69703d37e033a3&sb=1&src=searchresults&src_elem=sb&error_url=https://www.booking.com/searchresults.html?label=gen173nr-1FCAEoggI46AdIM1gEaGyIAQGYATG4AQfIAQzYAQHoAQH4AQKIAgGoAgO4AvTIm_IFwAIB;sid=eae1a774e77c394c5e69703d37e033a3;tmpl=searchresults;city=-2109472;class_interval=1;dest_id=-2109472;dest_type=city;dr_ps=IDR;dtdisc=0;from_idr=1;ilp=1;inac=0;index_postcard=0;label_click=undef;offset=0;postcard=0;room1=A%2CA;sb_price_type=total;shw_aparth=1;slp_r_match=0;srpvid=7df1609ef03a0103;ss_all=0;ssb=empty;sshis=0;top_ufis=1&;&sr_autoscroll=1&ss=Rishīkesh&is_ski_area=0&ssne=Rishīkesh&ssne_untouched=Rishīkesh&city=-2109472&checkin_year=2020&checkin_month=3&checkin_monthday=4&checkout_year=2020&checkout_month=3&checkout_monthday=5&group_adults=2&group_children=0&no_rooms=1&from_sf=1'
response=requests.get(url,headers=headers)
soup=BeautifulSoup(response.content,'lxml')
#print(soup.select('.a-carousel-card')[0].get_text())
for item in soup.select('.sr_property_block'):
try:
print('----------------------------------------')
print('----------------------------------------')
except Exception as e:
#raise e
print('')
And when you run it...
python3 scrapeBooking.py
You can tell that the code is isolating the cards HTML.
On further inspection, you can see that the name of the hotel always has a sr-hotel__name class... Let's also get the number of reviews, pricing, and ratings while we are at it.
for item in soup.select('.sr_property_block'):
try:
print('----------------------------------------')
print(item.select('.sr-hotel__name')[0].get_text().strip())
print(item.select('.hotel_name_link')[0]['href'])
print(item.select('.bui-review-score__badge')[0].get_text().strip())
print(item.select('.bui-review-score__text')[0].get_text().strip())
print(item.select('.bui-review-score__title')[0].get_text().strip())
print(item.select('.hotel_image')[0]['data-highres'])
print(item.select('.bui-price-display__value')[0].get_text().strip())
We have also tried to get the Hotel image and link, all crucial pieces of information.
The whole code looks 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.booking.com/searchresults.html?label=gen173nr-1FCAEoggI46AdIM1gEaGyIAQGYATG4AQfIAQzYAQHoAQH4AQKIAgGoAgO4AvTIm_IFwAIB&sid=eae1a774e77c394c5e69703d37e033a3&sb=1&src=searchresults&src_elem=sb&error_url=https://www.booking.com/searchresults.html?label=gen173nr-1FCAEoggI46AdIM1gEaGyIAQGYATG4AQfIAQzYAQHoAQH4AQKIAgGoAgO4AvTIm_IFwAIB;sid=eae1a774e77c394c5e69703d37e033a3;tmpl=searchresults;city=-2109472;class_interval=1;dest_id=-2109472;dest_type=city;dr_ps=IDR;dtdisc=0;from_idr=1;ilp=1;inac=0;index_postcard=0;label_click=undef;offset=0;postcard=0;room1=A%2CA;sb_price_type=total;shw_aparth=1;slp_r_match=0;srpvid=7df1609ef03a0103;ss_all=0;ssb=empty;sshis=0;top_ufis=1&;&sr_autoscroll=1&ss=Rishīkesh&is_ski_area=0&ssne=Rishīkesh&ssne_untouched=Rishīkesh&city=-2109472&checkin_year=2020&checkin_month=3&checkin_monthday=4&checkout_year=2020&checkout_month=3&checkout_monthday=5&group_adults=2&group_children=0&no_rooms=1&from_sf=1'
response=requests.get(url,headers=headers)
soup=BeautifulSoup(response.content,'lxml')
#print(soup.select('.a-carousel-card')[0].get_text())
for item in soup.select('.sr_property_block'):
try:
print('----------------------------------------')
print(item.select('.sr-hotel__name')[0].get_text().strip())
print(item.select('.hotel_name_link')[0]['href'])
print(item.select('.bui-review-score__badge')[0].get_text().strip())
print(item.select('.bui-review-score__text')[0].get_text().strip())
print(item.select('.bui-review-score__title')[0].get_text().strip())
print(item.select('.hotel_image')[0]['data-highres'])
print(item.select('.bui-price-display__value')[0].get_text().strip())
print('----------------------------------------')
except Exception as e:
#raise e
print('')
And when run.
Produces all the info we need.
In more advanced implementations you will need to even rotate the User-Agent string so Booking.com cant tell its the same browser!
If we get a little bit more advanced, you will realize that Booking.com can simply block your IP ignoring all your other tricks. This is a bummer and this is where most web crawling projects fail.
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