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 Web Scrapers and Web Crawlers: what’s the difference?

The internet is huge, it consists of around 66 zettabytes, which is the same as 66 trillion gigabytes. That’s a lot of data… If you were looking for specific information on the internet it could be a very time consuming task and so Data-Scrapers and WebCrawlers were born. While these tools serve distinct purposes, they are often misunderstood or used interchangeably.

In this article I will clarify their differences, talk about their applications and the key considerations for creating web scrapers.

 What Are Web Crawlers?

A web crawler, sometimes referred to as a bot or spider, is a program that systematically browses the web to index pages for search engines or gather broad datasets. Crawlers follow links from one webpage to another, creating a comprehensive map of websites and their interconnections.

In other words, Web Crawlers are a sort of internet scouts. 

The first web crawler, known as "World Wide Web Wanderer", was created by Matthew Gray in 1993. Gray, a researcher at MIT, developed the Wanderer to measure the growth of the World Wide Web by indexing web servers and tracking their activity.

While its main goal was to gather statistics about the web, it also laid the groundwork for modern web crawlers. The Wanderer was followed by other early crawlers like WebCrawler (created by Brian Pinkerton in 1994), which was the first search engine to index entire web pages instead of just titles.

While its main goal was to gather statistics about the web, it also laid the groundwork for modern web crawlers. 

Common Uses of Web Crawlers:

Search Engines: Search engines like Google use crawlers to index websites, enabling users to find relevant information quickly.

Data Analysis: Organizations utilize crawlers for market research, trend analysis, and competitor benchmarking.

Archiving: Projects like the Wayback Machine, which is site on which you can look at websites from the past, rely on crawlers to archive the internet.

What are Webscrapers?      

A web scraper is a tool designed to extract specific data from a website. Instead of indexing all pages, scrapers target particular elements, such as product details, pricing information, or user reviews.

Web scraping often involves accessing a webpage, parsing its content, and saving the extracted data in a structured format like CSV or JSON.

Common Uses of Web Scrapers:

E-commerce: Collecting product prices and availability across multiple platforms.

Research: Collecting large datasets for academic, scientific, or business analysis. Content

Monitoring: Tracking updates on blogs, news websites, or social media.  

And: dentifying Bot accounts on your favourite meme site and then blocking them.

Web scrapers are more focused and selective compared to web crawlers. 

Considerations When Creating Web Scrapers

While web scraping is a powerful tool, it’s not always legal or ethical:

1. Understand Website Terms of Service Many websites outline acceptable usage in their Terms of Service (ToS). Violating these terms may lead to legal action or restrictions. Always review the ToS to confirm that scraping is permitted.

2. Respect Robots.txt The robots.txt file on a website specifies which areas of the site can be accessed by automated tools. While it’s not legally binding, ignoring these rules can be viewed as bad practice and could lead to blocking.

3. Avoid Overloading Servers Excessive requests to a server can disrupt its functionality, potentially resulting in bans. Implement rate limiting in your scraper to prevent overloading the server with frequent requests, which is in a way similar to a DDOS attack. You can avoid overloading servers by setting a timer on your requests.

4. Use Proxies and User-Agent Rotation Websites often block IP addresses showing repetitive, bot-like behavior. Using proxies and rotating your User-Agent string (which mimics different browsers or devices) can help bypass these restrictions.

5. Handle Captchas Gracefully Some sites deploy CAPTCHAs to differentiate between bots and humans. Integrating CAPTCHA-solving mechanisms or limiting access to CAPTCHA-protected pages can mitigate interruptions.

6. Focus on Ethical Data Usage Scraping personal or sensitive data without consent violates privacy laws, such as the General Data Protection Regulation (GDPR) in Europe or the California Consumer Privacy Act (CCPA). Ensure your scraper only collects publicly available and non-sensitive information.

7. Implement Error Handling Websites can change their structure or content, potentially breaking your scraper. Design your scraper to handle errors gracefully and adjust to changes dynamically.

Want to build you own web scraper? Check out my projects and github to build one that automatically blocks users that show bot like behaviour.