How to Scrape Multiple Pages Using Beautifulsoup

Scrapping data from multiple pages on a website is a common task for many web scrapers and data scientists. While it may seem daunting at first, it can be easily accomplished using the Python Beautifulsoup library. In this comprehensive guide, we‘ll walk through the step-by-step process for scraping multiple pages using Beautifulsoup.

Overview

Beautifulsoup is a popular Python library used for web scraping purposes. It allows you to parse HTML and XML documents and extract data from them.

To scrape multiple pages, we need to:

1. Make a request to the first page and parse it
2. Extract the links to other pages
3. Loop through the links to scrape each page one by one

This process requires us to understand a few key concepts in Beautifulsoup:

• Making requests
• Parsing pages
• Finding elements
• Accessing attributes like href
• Recursion

We‘ll cover all of these in detail throughout this guide.

Import Libraries

Let‘s start by importing the requests and Beautifulsoup libraries:

from bs4 import BeautifulSoup
import requests

Requests will allow us to easily make HTTP requests to pages.
Beautifulsoup will let us parse the pages and extract data.

Make a Request to the First Page

We need to make a GET request to fetch the HTML content of the first page we want to scrape. For example:

first_page = ‘https://www.example.com‘
response = requests.get(first_page)

This will give us a Response object containing the HTML of the page.

Parse the First Page

Next, we need to parse the first page‘s HTML content using Beautifulsoup so we can start finding elements and extracting data:

soup = BeautifulSoup(response.content, ‘html.parser‘)

This creates a BeautifulSoup object that we can use to navigate and search the parsed document.

Extract Links to Other Pages

Now we can use Beautifulsoup to find all the <a> tag elements on the page that link to other pages we want to scrape:

links = soup.find_all(‘a‘)

This gives us a list of all the <a> elements. We‘ll need to filter this down to just the links relevant to our scraping goal.

For example, if we want to follow pagination links, we can filter for <a> tags with a rel="next" attribute:

next_links = soup.find_all(‘a‘, attrs={‘rel‘: ‘next‘})

Or if we want to follow category links, we can filter for <a> tags in a specific div:

category_links = soup.find(‘div‘, {‘id‘: ‘categories‘}).find_all(‘a‘)

Adjust this filtering depending on the types of links you need to follow for your scraping goal.

Loop Through the Links

Now we have a list of <a> element objects representing the links to each page we want to scrape. We need to loop through these and make a request to each link to scrape the associated page.

for link in next_links:
  url = link[‘href‘]

  response = requests.get(url)
  soup = BeautifulSoup(response.content, ‘html.parser‘)

  # Scrape page data here

This will cycle through each link, make a request, parse the response, and then we can use the soup object to find and extract data from each page.

Recursive Web Scraping

A useful technique for scraping pagination or other layered pages is to make the scraping function recursive. This means the function calls itself to scrape additional pages.

Here is an example:

def scrape_pages(url):

  response = requests.get(url)

  soup = BeautifulSoup(response.content, ‘html.parser‘)

  # Scrape page data

  next_link = soup.find(‘a‘, {‘rel‘: ‘next‘})

  if next_link: 
    next_page = next_link[‘href‘]
    scrape_pages(next_page) # Calls itself
  else:
    print(‘Done‘)

This allows us to start from one page, then keep finding the next page and recursively calling the function until there are no more pages to scrape.

Putting It All Together

Here is some example code putting together everything we covered to scrape multiple pages with Beautifulsoup:

import requests
from bs4 import BeautifulSoup

def scrape_pages(url):

  response = requests.get(url)

  soup = BeautifulSoup(response.content, ‘html.parser‘)

  # Scrape page data here

  next_link = soup.find(‘a‘, {‘rel‘: ‘next‘})

  if next_link:
    next_page = next_link[‘href‘]
    print(next_page)
    scrape_pages(next_page)
  else:
    print(‘Done‘)

first_page = ‘https://www.example.com‘  

scrape_pages(first_page)

This will start scraping from the first page, follow links to subsequent pages, scrape each one, and continue recursively until there are no more next page links found.

The key steps are:

• Make a request and parse the initial page
• Find the links to follow
• Loop through and scrape each page
• Recursively call the function on the next page link
• Break out of the loop when no more links are found

By following this pattern, you can expand the scraping to any number of pages on a domain in an automated fashion using Beautifulsoup.

Scraping Best Practices

When scraping multiple pages, here are some best practices to follow:

• Use throttling – add delays between requests to avoid overwhelming servers
• Randomize user agents – rotate user agent strings to appear more human
• Check for bots – if pages are blocking bots, use proxies/rotations
• Handle errors – use try/except blocks and status codes to catch errors
• Limit recursion depth – prevent infinite loops if there is a link chain issue
• Persist data – save scraped data to a database or file for future use

Conclusion

Scraping multiple pages with Beautifulsoup is straightforward once you understand the key steps:

1. Make requests to page links
2. Parse the responses
3. Find the next page links
4. Recursively scrape each page in a loop
5. Handle errors and persist data

The full code puts these pieces together to automatically scrape an entire website section. Beautifulsoup is an invaluable tool for these web scraping tasks.

With some thoughtful design and error handling, you can leverage its features to extract data from virtually any set of pages on the modern web.