How to handle pagination in eBay search results when scraping?

Handling pagination in eBay search results when scraping is a crucial step to ensure you collect data from all available pages of search results. eBay search results are typically paginated to limit the amount of data displayed on a single page, prompting users to navigate through multiple pages to view all items. To scrape paginated results effectively, you need to identify how the site's pagination works and then loop through the pages accordingly.

Below are steps to handle pagination in eBay search results when scraping:

Step 1: Analyze the Pagination Structure

Before writing any code, manually navigate the eBay search results and observe the URL changes as you go through the pages. This will help you understand the pagination pattern. For example, eBay may use query parameters like ?_pgn=2 to indicate page number 2.

Step 2: Write a Loop to Iterate Through Pages

Once you understand the pagination pattern, you can write a loop in your scraping code that increments the page number and fetches the contents of each page until there are no more pages to scrape.

Python Example with requests and BeautifulSoup

Below is a Python example using requests to make HTTP requests and BeautifulSoup to parse HTML:

import requests
from bs4 import BeautifulSoup

base_url = ""
search_query = "laptop" # Your search term
params = {
    "_nkw": search_query,
    "_pgn": 1 # Start with page 1

while True:
    response = requests.get(base_url, params=params)
    soup = BeautifulSoup(response.text, 'html.parser')

    # Process the search results on the current page
    # For example, let's print titles of the items
    for item in'.s-item__title'):

    # Check if there is a "Next" page button/link, and update `_pgn` parameter
    next_page = soup.select_one('.pagination__next')
    if next_page and 'disabled' not in next_page.get('class', []):
        params["_pgn"] += 1
        break # No more pages

JavaScript Example with node-fetch and cheerio

Below is a JavaScript (Node.js) example using node-fetch to make HTTP requests and cheerio to parse HTML:

const fetch = require('node-fetch');
const cheerio = require('cheerio');

const base_url = "";
let search_query = "laptop"; // Your search term
let page_number = 1; // Start with page 1

const scrapePage = async () => {
    const params = new URLSearchParams({ "_nkw": search_query, "_pgn": page_number });
    const response = await fetch(`${base_url}?${params}`);
    const body = await response.text();
    const $ = cheerio.load(body);

    // Process the search results on the current page
    // For example, let's print titles of the items
    $('.s-item__title').each((index, element) => {

    // Check if there is a "Next" page button/link
    const next_page = $('.pagination__next');
    if (next_page.length && !next_page.hasClass('disabled')) {
        scrapePage(); // Recursively call to scrape next page


Important Considerations

  • Respect eBay's Terms of Service: Web scraping may not be allowed or may be restricted by eBay's terms of service. Ensure that you are compliant with their policies before scraping their site.
  • Rate Limiting: To avoid being blocked, make sure to not send requests too quickly. Implement delays or use proxies if necessary.
  • User Agent: Set a proper user-agent to simulate a real browser request.
  • Error Handling: Implement error handling for network issues or unexpected changes in the page structure.
  • Data Extraction: The examples above only print item titles. You'll need to modify the selector to extract other details like price, shipping information, etc.

Always use web scraping ethically and legally. If eBay provides an API for obtaining the data you need, it is recommended to use their API instead of scraping, as it is more reliable and respects eBay's service structure.

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