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Conquering Pagination: A Comprehensive Guide to Handling Pagination in Web Scraping

Pagination is ubiquitous across the modern web. By some estimates, over 80% of websites employ some form of content pagination. The reasons are clear – pagination improves site performance, eases navigation, and encourages users to view more pages.

But while beneficial for users, pagination poses challenges for scrapers. To extract complete data, scrapers must detect and handle pagination logic. This comprehensive guide will explore common pagination patterns, demonstrate pagination scraping techniques, and share strategies to master even the most complex pagination-heavy sites.

Why Pagination Matters for Scraping

Before diving in, let‘s look at why pagination handling is so crucial for effective web scraping:

  • Avoid missing data – Without detecting pagination, scrapers will only get content from initial pages. Key data could be lost.
  • Prevent scraping duplicates – Scrapers may re-scrape the same pages without pagination tracking.
  • Scrape efficiently – Crawling pagination shows scraper respect for sites by minimizing duplicate requests.
  • Overcome blocking – Repeated access to initial non-paginated URLs is a red flag for sites trying to detect scrapers. Wise pagination handling helps avoid blocks.
  • Scale data extraction – For sites with thousands of paginated pages, scrapers need pagination to gather complete data.

The rest of this guide will arm you with pagination strategies for overcoming these obstacles. Let‘s survey common pagination patterns first.

Common Pagination Patterns

While each site implements pagination differently in code, UI patterns tend to fall into a few categories:

Page number pagination example

The classic page number interface provides links or buttons to directly access any given page. Page numbers are clear indicators of the total page count.

Next/Previous Buttons

Next/previous pagination

Next and previous buttons allow sequential clicking through pages one-by-one. The presence or absence of a "next" button indicates whether more pages are available.

Infinite Scroll

Scrolling down the page dynamically fetches more content. No direct page links are displayed. Additional data is typically fetched via AJAX calls when scrolling approaches the page bottom.

Load More Buttons

Clicking a "load more" button fetches the next page‘s content and appends to the current page. Like infinite scroll, explicit page numbers are usually hidden.

Now let‘s see how to handle these patterns in real-world Python scrapers.

Handling Pagination in Python

To demonstrate pagination scraping techniques, we‘ll use Python 3 along with the Requests library for fetching pages and Beautiful Soup for parsing HTML.

Let‘s look at a site with numbered page links – Woman and Beauty. Viewing the HTML, we can see the page links:

<div class="paging">
  <a href="/page/1/">1</a>
  <a href="/page/2/">2</a>
  <!-- ...etc -->
</div>

Here‘s how we could scrape across pages:

from bs4 import BeautifulSoup
import requests

url = ‘https://www.womanandbeauty.com‘

# Get first page
res = requests.get(url)
soup = BeautifulSoup(res.text, ‘lxml‘)

# Find all page link elements
pages = soup.find(‘div‘, class_=‘paging‘).find_all(‘a‘)

for page in pages:
  page_url = page[‘href‘]

  # Scrape page contents here

  print(page_url) # Print URLs scraped

We locate the pagination div, extract the page links, then loop through to build the page URLs and scrape each one.

Next/Previous Buttons

For a site like Quotes to Scrape, viewing the page HTML shows us:

<li class="next">
  <a href="/page/2">Next</a>
</li>

We can follow these next page links:

import requests 
from bs4 import BeautifulSoup

url = ‘http://quotes.toscrape.com‘

while True:
  res = requests.get(url)
  soup = BeautifulSoup(res.text, ‘html.parser‘)

  # Scrape page data...

  next_btn = soup.find(‘li‘, {‘class‘: ‘next‘})
  if not next_btn:
    break

  url = next_btn.find(‘a‘)[‘href‘] # Get next page URL

We locate the next button, extract the URL, and continue looping until no more next buttons exist.

Infinite Scroll

For infinite scroll, the key is finding the AJAX calls that fetch additional data.

Let‘s try an example from Codewall using Chrome DevTools:
blank
We can see /resources?page= calls being made on scroll. Let‘s scrape:

import requests
import json

base = ‘https://codewall.co.uk/resources?‘
url = base + ‘page={}‘  

for page in range(1, 4):
  res = requests.get(url.format(page))
  data = json.loads(res.text)

  # Scrape data...

  print(f‘Scraped {len(data)} items from page {page}‘)

We cycle through page numbers until a given cutoff, scraping the AJAX responses.

Load More Buttons

Load more buttons function similarly to infinite scroll. We need to click the buttons and scrape the dynamically loaded content.

Looking at the Gousto Recipes site, we see a "Load more recipes" button at the page bottom.

When clicked, it makes a request to /cookbook/recipes?page=2 to get the next page HTML.

Here‘s one approach to scrape page by page:

from bs4 import BeautifulSoup
import requests 

BASE_URL = ‘https://www.gousto.co.uk/cookbook/recipes‘
res = requests.get(BASE_URL) # First page

last_page = False
page = 2 # Page counter

while not last_page:
  soup = BeautifulSoup(res.text, ‘html.parser‘)

  # Scrape page contents 

  button = soup.select_one(‘.load-more-simple‘)
  if not button:
    last_page = True
  else:  
    url = BASE_URL + ‘?page=‘ + str(page) 
    res = requests.get(url)
    page += 1

We check for existence of the load more button to determine if pagination finished.

Strategies for Robust Pagination Handling

On complex sites like ecommerce, forums, or social media, pagination can become very tricky to handle reliably. Here are some more advanced tactics to consider:

Save and Reuse Session Cookies

Retaining browser session cookies across page requests preserves logged in state, shopping cart contents, pagination context, and more:

import requests

session = requests.Session()

res = session.get(‘https://first-page.com‘)
# Save session cookies 

for page in range(2, 10):
  res = session.get(f‘https://paginated.com/page-{page}‘, cookies=session.cookies) 

Track Total Page Counts

Calculate the total number of expected pages based on items per page:

# Site has 15 items per page
total_items = 500 

expected_pages = total_items / 15 # = 33 pages

Then we can iterate up to this calculated page count.

Watch for Page Layout Shifts

Monitor page HTML for changes indicating a shift from paginated pages to a single page listing all items.

Use Proxies and Rotation

Rotating different proxies or IP addresses for each request can help avoid blocks when pounding sites with pagination requests:

from proxy_libs import ProxyManager  

pms = ProxyManager([‘http://proxy1‘, ‘http://proxy2‘]) 

for page in range(1, 10):
  proxy = pms.get_proxy() 
  res = requests.get(url, proxies=proxy)

Set Random Delays Between Requests

Adding randomized delays of 1-3 seconds helps pagination requests appear more human:

import time
from random import randint

# Scrape page 1

time.sleep(randint(1, 3)) 

# Scrape page 2

time.sleep(randint(1, 3))

# etc...

These are just a few common tactics for robust pagination logic. The optimal solution depends on your scraping needs and the target site.

Detecting the End of Pagination

Knowing when to stop scraping pagination is crucial. Here are some strategies:

  • Check for an empty result set – no more products, articles, etc.
  • Watch for a page layout change to a single page listing.
  • Validate against a known maximum page count.
  • Look for the absence of a "next" or "load more" element.
  • See if the current page number exceeds the total count.
  • Check APIs for a pagination termination flag like has_more: false.
  • Handle 404 errors from invalid pagination requests.

Include one or more fallback detection mechanisms to avoid infinite scraping loops.

Conclusion

Handling pagination is a key skill for web scraping professionals. By understanding common patterns like page numbers, next buttons, and infinite scroll, scrapers can locate and iterate through paginated content.

Robust pagination logic couples with strategies like proxies and request delays enables scraping even the largest, most complex sites reliably and efficiently.

With the techniques explored in this guide, you now have an arsenal of tools to conquer pagination and take your scrapers to the next level. The entire web is now within your grasp!

Further Reading

To learn more about web scraping, refer to these additional resources:

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