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August 2, 2023

Screen Scraping: A Comprehensive Guide on What It Is and How to Use It

Screen scraping, a powerful technique for data extraction, is revolutionizing real-time data collection and analysis. From static to dynamic, explore the types, tools, and methods of screen scraping.

Screen scraping is a technique used to automatically collect visual data from computer displays and input it into other programs or systems without requiring human interaction to manually enter the data.

It is also known as terminal emulation. While screen scraping can be used for morally justifiable purposes such as gathering data from multiple accounts on behalf of a customer or automating banking processes, it can also be used for malicious purposes such as stealing data from apps.

At times, the desire for quicker and more efficient development can prompt a developer to duplicate code from another software program. Screen scraping was initially used to present data from outdated mainframe systems and legacy applications on modern applications.

The use of a screen scraper has a long history, beginning with manual processes of copying data or source code from websites and pasting it into spreadsheets or databases.

However, as the internet grew and the need for more efficient data extraction became crucial, screen scraping evolved into an automated process. Today, it has become a popular technique for data extraction and analysis, used in various industries.

How does screen scraping work?

Screen scraping is designed to locate and recognize specific user interface components chosen by the user, and extract data from those UI (User Interface) elements.

For instance, columns in spreadsheets or buttons on websites can be extracted.

There are situations where the screen scraper may use OCR (optical character recognition) to convert unstructured data, like text from images or PDF files, into machine-readable text before sending the data to the relevant application.

This allows the extracted data to be easily used and analyzed

Screen Scraping and Data Extraction

Screen scraping is often used for data extraction, which involves collecting data from multiple sources and consolidating it into a structured format. Data extraction is commonly used in marketing, sales, and research.

Main Types of Screen Scraping

There are three main types of screen scraping: static, dynamic, and hybrid. Each type has its own features, pros, and cons.

Static Screen Scraping

Static screen scraping involves extracting data from a fixed HTML structure. This is the simplest type of screen scraping and is best used for websites that have a predictable structure.

Static screen scraping is also fast and easy to set up. However, it may not work well for websites with dynamic content or complex HTML structures.

Dynamic Screen Scraping

Dynamic screen scraping involves extracting data from a dynamic HTML structure. This is more complex than static screen scraping and requires specialized tools to handle the dynamic content.

Dynamic screen scraping is best used for websites with a lot of dynamic content, such as social media websites or news websites. However, it can be slow and may require a lot of resources.

Hybrid Screen Scraping

Hybrid screen scraping combines the best of both static and dynamic screen scraping. This type of screen scraping is best used for websites with a mix of static and dynamic content.

Hybrid screen scraping can be fast and easy to set up, while still being able to handle dynamic content.

Pros and Cons of Using a Screen Scraper

Using a screen scraper has its advantages and disadvantages. Here are some the pros and cons:


• Can automate repetitive tasks

• Can extract data from multiple sources

• Can be used for data mining and web scraping

• Can provide real-time data


• Can violate website's security concerns

• Can be illegal in some cases

• Can be complex to implement

• Can be unreliable

Common Techniques for Screen Scraping

There are several techniques for screen scraping, including regular expressions, Xpath, CSS selectors, and DOM parsing.

Regular Expressions: Regular expressions are a powerful tool for matching and manipulating text strings. They can be used to extract specific patterns from HTML code, such as email addresses, phone numbers, or URLs.

XPath: XPath is a query language used to select nodes from an XML or HTML document. It can be used to extract specific elements or attributes from HTML code, such as table rows, headings, or links.

CSS Selectors: CSS selectors are a syntax used to select elements from an HTML document based on their style attributes. They can be used to extract specific elements or attributes from HTML code, such as font styles, colors, or sizes.

DOM Parsing: DOM parsing involves traversing the HTML document's DOM tree to locate specific elements and their contents. It can be used to extract specific elements or attributes from HTML code, such as form fields, input values, or text content.

Screen Scraping Tools

There are different screen scraping tools available, and the choice of tool depends on the type of website and the desired output. Here are some of the most common screen scraping tools:

Web Scraping Frameworks: Web scraping frameworks, such as Scrapy and BeautifulSoup, are popular screen scraping tools. They provide a powerful and flexible way to extract data from websites.

Screen Scraping Libraries: Screen scraping libraries, such as Selenium and Puppeteer, are used for dynamic screen scraping. They allow the user to interact with websites, enabling the extraction of data from dynamic content.

Browser Extensions: Browser extensions, such as Web Scraper and Data Miner, are easy-to-use screen scraping tools. They are suitable for simple screen scraping tasks and do not require programming skills.

Online Screen Scraping Services: Online screen scraping services, such as and Parsehub, provide a web-based interface for screen scraping. They are suitable for users who do not want to install software on their computer.

Basic Steps in Screen Scraping

The use of screen scrapers involves four basic steps:

1. Retrieving the Web Page

The first step in screen scraping is to retrieve the web page that you want to scrape. This can be done using a web browser or a programmatic HTTP request.

2. Parsing the HTML Content

The second step is to parse the HTML content of the web page. This involves analyzing the HTML code and identifying the relevant tags and attributes.

3. Extracting the Desired Data

Then, extract the desired data from the HTML content. This can be done using regular expressions, Xpath, CSS selectors, or DOM parsing.

4. Saving the Data in a Structured Format

The final step in screen scraping is to save the extracted data in a structured format, such as CSV, JSON, or XML.

Common Challenges in Screen Scraping

Screen scraping can be challenging due to the following reasons:

Handling Dynamic Content: Websites with dynamic content, such as JavaScript and AJAX, can be difficult to scrape. This is because the content is generated dynamically, which makes it difficult to extract using static screen scraping.

Dealing with CAPTCHAs and Other Obstacles: Some websites use CAPTCHAs and other obstacles to prevent screen scraping. Dealing with these obstacles can be challenging and may require advanced techniques such as OCR.

Avoiding IP Blocking: Using a screen scraper can be detected by websites, and IP blocking can be used to prevent it. Avoiding IP blocking can be challenging and may require the use of proxies or other advanced techniques.


Screen scraping is a powerful technique used to extract data from websites. It has become increasingly popular due to the need for real-time data collection and analysis.

In this article, we have explored what screen scraping is, its history, how it works, its types, techniques, tools, basic steps, and common challenges.

By using screen scraping techniques, businesses can automate data collection, save time and resources, and fuels business growth.

If you are interested in screen scraping, you can start by learning more about the different techniques, tools, and methods.

There are many online resources available that can help you get started. You can also try out Geonode’s pay as you go scraper to see the best data results for your needs.