Web scraping and screen scraping are two terms that are often used interchangeably, but they actually refer to different data extraction techniques. In this post, we‘ll explain what each one is, when to use them, and the key differences between web scraping and screen scraping.
What is screen scraping?
Screen scraping refers to extracting data directly from a user interface (UI) rather than accessing data programmatically through an API or database query. The "screen" being scraped is typically a desktop application or web page displayed on a user‘s screen.
Some examples of screen scraping include:
- Copying data from a legacy desktop application that doesn‘t have an API and pasting it into a spreadsheet.
- Using an automated bot to simulate mouse clicks and keyboard inputs to extract data from a software interface.
- Taking a screenshot of a graph or chart displayed in an application and using OCR to extract the data.
The key aspect of screen scraping is that it focuses on getting data directly from the screen output rather than accessing the underlying data source. Screen scraping tools work by analyzing pixel data and mimicking user interactions.
When to use screen scraping
Screen scraping is commonly used in these situations:
Data migration – Transferring data from legacy systems to newer applications by scraping screens and reformatting the data.
Application integration – Allowing two applications that don‘t have APIs to share data by scraping the UI of one and inputting into the other.
Testing – Scraping on-screen data to verify that the correct information is being displayed by the application.
Data collection – Gathering data from software that doesn‘t have an accessible database or API. Useful for things like pricing data, inventory levels, etc.
Overall, screen scraping is best for getting data out of desktop software, business applications, and web apps where you don‘t have access to the backend data source or API. It‘s a last resort when there are no other options available.
Drawbacks of screen scraping
Some downsides to screen scraping include:
Fragile – Susceptible to breaking when the UI changes, requiring constant maintenance.
No access to full data – Limited to whatever data is displayed on-screen.
Questionable legality – Potential copyright issues around replicating full displays and logs.
Higher complexity – Requires simulating user interactions instead of direct data access.
Due to these drawbacks, screen scraping is a last-ditch tactic when no better options exist. Where possible, it‘s better to access data through a sanctioned API or database query.
What is web scraping?
Web scraping refers to the automated extraction of data from websites. It works by parsing HTML code to extract the relevant data into a structured format like a spreadsheet.
Some examples of web scraping include:
- Extracting product listings from an e-commerce site to monitor pricing.
- Compiling company contact details from multiple sites into a lead list.
- Aggregating news articles from different sources into a single feed.
The key difference from screen scraping is that web scraping focuses directly on the underlying HTML code rather than what the user sees on their screen.
When to use web scraping
Here are some of the most common use cases for web scraping:
Price monitoring – Tracking prices for products across competitor websites. Useful for dynamic pricing.
Lead generation – Building lists of prospects from directories and compiling contact info and other data.
Market research – Analyzing trends, sentiment, reviews, and discussions from various forums and websites.
News monitoring – Scraping articles and press releases from news sites to stay current.
Data aggregation – Combining related data from various websites into a single API or database.
Overall web scraping is useful anytime you need to harvest unstructured public data from websites. It allows you to tap into publicly available data at scale.
Benefits of web scraping
Some key advantages of web scraping include:
Wide data access – Able to extract large amounts of public website data.
Cost efficient – Much cheaper than manual data entry and faster than human extraction.
Automated – Can run 24/7 and adapt to site changes using self-healing scrapers.
Scalable – Can extract from tens of thousands of sites and millions of pages.
Structured data – Returns clean structured data ready for analysis unlike PDFs and screenshots.
When done correctly, web scraping provides an efficient way to leverage publicly available web data.
Key differences between web scraping and screen scraping
Now that we‘ve covered the basics, let‘s summarize the main differences:
|Accesses raw HTML code behind the UI
|Accesses pixel data displayed on the screen
|Focuses on content
|Focuses on presentation/layout
|Structures data using HTML parsers
|Uses OCR and computer vision to extract data
|Wide access to full web
|Limited to application front-end
|Higher success rate
|Prone to breaking on UI changes
|Higher maintenance if UI changes
|Legal gray area due to IP concerns
|Potential copyright issues
The core difference comes down to web scraping targeting raw HTML code while screen scraping focuses on the user interface presentation.
As a rule of thumb:
Use web scraping when you need to extract data from websites. This is the best option in most cases.
Use screen scraping only when there‘s no direct data access and you have to get data via the UI.
Web scraping tools
There are many tools available to handle web scraping tasks:
For one-off manual scraping, browser extensions provide the easiest way to get started. For large projects, APIs and cloud services provide scalability without coding. And for advanced use cases, programming libraries open up limitless possibilities for custom scrapers.
Screen scraping tools
Common screen scraping tools include:
OCR software – Optical character recognition programs like ABBYY FineReader extract text and data from images and PDFs.
Data capture automation – Tools like Kapow record and replay user interactions to simulate screen scraping.
Screen recording – Recording user sessions and then extracting data from the video with OCR and vision APIs.
Custom coding – Languages like Python allow building screen scrapers leveraging image processing and automation libraries.
For one-off manual extraction, OCR software provides the easiest method. But for automation and scalability, commercial data capture platforms and custom coding are better options.
Web scraping focuses on extracting raw HTML data from websites. Screen scraping extracts data from user interfaces.
Web scraping is better for aggregating web data. Screen scraping is a last resort for getting data out of applications.
There are a variety of tools available for both, ranging from browser extensions to programming libraries.
In most cases, it‘s preferable to access data through a direct database query or API instead of resorting to scraping techniques. But when that isn‘t possible, web and screen scraping provide a means to liberate "locked" data.
I hope this breakdown has helped explain these two terms and how their use cases differ. When done ethically, scraping can open up valuable data sources. Just be sure to understand the legal considerations and potential impacts.
Let me know if you have any other questions!