How to Deal with Web Scraping Pagination: Types and Techniques

When we talk about data collection, one of the main challenges many users face is web scraping pagination — dividing content into multiple pages. Depending on how a website implements pagination, the approach to scraping it can vary significantly.

In this article, we will examine the main types of pagination and the methods for handling them in detail so that you can efficiently collect data from any website, regardless of its content structure.

What is Pagination?

Pagination is dividing content into multiple pages for better display and navigation. On websites, web pagination is often used to organize large amounts of data, such as product listings, articles, or comments, allowing users to move from one page to another to view the content in sections.

Common Types of Web Pagination

Let's break down the types of pagination and how to identify them on websites.

Static Web Pagination

This web pagination is found on many websites, especially online stores and catalogs. Each page has a unique URL that contains parameters that indicate the page number.

The page may have "next" and "back" buttons and numbered links (1, 2, 3, ...). When a user clicks on the next page, the user goes to a different URL, and the site loads a new data set.

The page address might look like this:

• example.com/products?page=1
• example.com/products?page=2
• example.com/products?page=3

Dynamic Web Pagination

With this type of website pagination, the data is not loaded immediately when you go to a new page. Instead, the page sends a request to the server and receives the data in the background without refreshing the page. For example, the user can click the "next page" button, but instead of loading a new page, the content is loaded directly into the current page.

Here's how it works in stages:

1. The page displays some of the data.
2. When you click "Next," the page requests data from the server via AJAX.
3. The server sends back a new list of products/content to be added to the page.

In this case of web scraping pagination, the URL may not change when the data is loaded, and the user may lose where they left off.

Infinite Scroll

This type of web pagination is commonly found on social media platforms, news websites, and catalogs with large amounts of content. When the user reaches the end of the visible area, the browser sends a request to the server. The server responds with a new batch of data, which is appended to the end of the list, and the process repeats as long as there is more content to load.

This web page pagination process is convenient for users because no additional actions are required to load more content.

“Load More” Buttons

This pagination type can be considered an intermediate option between dynamic web pagination and infinite scrolling. The page displays a fixed number of elements and a "Load More" button. When the button is clicked, the next batch of data is loaded.

This approach allows users to control the loading process while conserving server resources by preventing unnecessary data from being loaded simultaneously.

Difficulties with Web Scraping Pagination

When data is spread across multiple pages, you need different strategies to collect it efficiently. While traditional website pagination is relatively straightforward, dynamic approaches can put your scraping skills to the test.

Many websites impose rate limits, restricting the number of requests from a single IP address within a specific timeframe. If you send requests too frequently, the server may block access or temporarily limit page views by returning a 429 (Too Many Requests) error. This is especially problematic when dealing with deep pagination, where you must load hundreds of pages in a row.

Some websites don’t use standard web pagination formats like ?page=1,2,3.... Instead, they rely on cursor-based tokens, offset parameters, or dynamically changing URLs. In such cases, simply incrementing the page number won’t work — you’ll need to analyze how the site loads new data.

Certain platforms artificially limit access to deep pages, making web scraping pagination even more challenging. For example, search engines or product catalogs might only show the first 10–20 pages before requiring filtering or user authentication. This adds an extra layer of complexity to large-scale data extraction.

Website developers frequently update page designs and web pagination mechanisms. Today, you might have static page links, but tomorrow, pagination could become dynamic and hidden within JavaScript. This makes scraping scripts vulnerable to changes and requires continuous monitoring.

Even if you successfully extract the data, its format may not be easy to process. Some sites use HTML tables, others return JSON API responses, while some encrypt or encode their data. This means additional data analysis is necessary before it can be used effectively.

Tools and Libraries for Web Pagination

When you understand precisely how the site feeds data, you can choose the right tool to collect the information.

• Python Requests + BeautifulSoup (Python) 

This combination is the simplest and fastest solution if a website uses static pagination. Requests allow you to send HTTP requests and retrieve HTML pages, while BeautifulSoup helps parse the HTML and extract the necessary data.

When to use: If the site has traditional web pagination using ?page=1,2,3....

• Selenium / Playwright / Puppeteer

If the site renders content via JavaScript or dynamic loading, HTTP requests won't help. This is where browser tools come in. Selenium emulates user actions and is suitable for complex sites. Playwright, a faster and more convenient analog of Selenium, supports working with different browsers. And Puppeteer is convenient for rendering JavaScript. How to choose between Playwright and Puppeteer?

When to use: If the site loads content via AJAX or uses infinite scrolling.

• Scrapy

When you need to scrape large volumes of pages, Scrapy helps automate the process. It supports asynchronous requests, session management, and API handling for dynamic content extraction.

When to use: If a large project requires data collection from multiple pages.

• Proxy and anti-detect browsers

If a website blocks requests or uses anti-scraping techniques, proxies and antidetect browsers help mask your traffic. Integrating rotating proxies into your scraper can save you from dealing with bans.

By the way, Froxy provides access to 10M+ clean IPs, making it easier to avoid detection.

When to use: If your IP gets blocked or the site has strong scraping protection.

Methods of Working with Web Pagination

Scraping paginated data requires different approaches depending on how a site implements content loading. Some sites use classic page numbering, while others load data dynamically via AJAX or infinite scrolling. Let's look at each of the options!

Static Web Pagination

This is the simplest case. Each page has its own URL with a numeric parameter (?page=1, ?page=2, and so on). To scrap this structure, it is enough to change the page number in the link, so simply:

1. Define the base URL and find the parameter that changes.
2. Run a loop where we increase the page number until we reach the end.
3. Check if there is a “Next Page” button or the data has run out.

Python + BeautifulSoup code example:

This method is good for sites where page numbers are in order, and the URL structure is easy to predict.

Dynamic Web Pagination

Some sites use AJAX to load data without reloading the page. This means that regular HTTP requests don't do anything - the data appears only after JavaScript code is executed.

The plan of action is as follows:

1. Use Selenium or Playwright to emulate a browser.
2. Find network requests (in DevTools → Network) to understand where content is being downloaded from.
3. Connect to the API and directly request data without rendering the page.

Python + Selenium code example:

This method is suitable for sites where content is dynamically loaded and cannot be retrieved by standard GET requests.

Infinite Scroll

Data is automatically loaded when scrolling down on sites with infinite scrolling (e.g., Twitter or TikTok). Therefore, it is necessary to simulate the user scrolling with browser automation.

Recommended:

1. Use Selenium or Playwright to emulate scrolling.
2. Intercept network requests (using DevTools or traffic monitoring tools).
3. Determine when new data is no longer available.

Python + Selenium code example:

This web pagination method is helpful for social networks, news aggregators, and marketplaces, providing an endless product feed.

“Load More” Buttons

Some sites don't use classic web pagination or scrolling, but you must click the “Load More” button to load new data. 

To deal with web scraping pagination, you need to:

1. Find the download button in the page code.
2. Programmatically click on it using Selenium or Playwright.
3. Wait for new data to be loaded and repeat the process.

Python + Selenium code example:

This method can be used when scraping online stores and catalogs where content is not automatically loaded.

Conclusion and Recommendations

What can we conclude about web scraping pagination? Web pagination comes in different forms, and each type requires a unique scraping approach. If a website uses static web pagination, you can simply change the page number in the URL and load data in a loop. This is the easiest and fastest method, requiring minimal tools.

When data is loaded dynamically via AJAX, you’ll need to either emulate a browser using Selenium or Playwright or analyze network requests to extract JSON responses directly from the API. While this approach is more complex, it effectively bypasses HTML rendering.

Websites with infinite scrolling require simulating user actions — scrolling down and waiting for new elements to load. It's crucial to track when data runs out to prevent your script from getting stuck in an endless loop.

If content is loaded by clicking a "Load More" button, you must locate it in the HTML and keep clicking until all data is retrieved. This method is beneficial for e-commerce sites and marketplaces.

Remember anti-scraping measures! Some websites block frequent requests, so adding delays or using proxies is essential. The best solution? Residential proxies from Froxy. With over 10 million clean IPs and access to 200+ locations worldwide, they ensure smooth and uninterrupted data collection.