The terms "web scraping" and "web crawling" are frequently interchanged. After all, aren’t both used for data mining? The truth is that although they are similar, they are not the same.
In this article, we'll go through the fundamental distinctions between web crawling and web scraping, and we'll help you determine which one is right for you and your company.
What is Web Crawling?
Web crawling is essentially the use of an internet bot - also known as crawlers or spiders - that “crawls” the internet and gathers pages and data to index or create collections.
In simple terms, a crawler visits a website, reads the page’s content, and then follows all the links within that page to crawl even more pages in order to create entries for search engine indexing.
Resulting in a deep search for information extraction. Online crawling is done by well-known search engines like Google and Bing, and this information is used to index websites.
How Does Crawling Work?
Web crawling uses a spider (or crawling agent) that locates and obtains information from the deeper layers of the World Wide Web by crawling through every nook and cranny of the Internet. If we were to crawl an eCommerce web page, the procedure would be as follows:
- The crawler navigates to the URL you specified, also known as a seed URL – http://example.com.
2. It gathers all the data from the page and follows all the links it can find in the navigation menu, the body of the page, and the footer.
3. Product, content, and category pages are discovered.
4. All the data inside the product pages (price, description, title, etc.), content pages, and category pages are gathered and indexed or stored in a database.
So web crawlers sift through massive amounts of data and information to find and collect all the data from websites relevant to your project.
When to Use a Web Crawler?
More technical industries will most likely take advantage of web crawling vs scraping. If you want to look through massive data sets and crawl websites in-depth, you'll want to employ a web crawler. This means that you’ll be able to do what search engines do — go around the web seeking any information and clicking on every link available and indexing data in the same way that Google does, and collecting as much information as possible.
The crawler will also sort the pages to organize the data the way you prefer, plus performing other functions that allow users to find what they’re looking for within the database. As you’ll see later on, it is also an essential component of web scraping.
Tools for Web Crawling
Scrapy
Scrapy is a must-have among the web crawling technologies available on the market. It is a high-performance web crawling and scraping framework that is commonly used for web crawling. It can be used for data mining, monitoring, and automated testing, among other things. Scrapy is rather simple to use if you are familiar with Python. It is compatible with Linux, Mac OS X, and Windows.
Heritrix
Heritrix is a popular, quick, and scalable Java web crawler that is free and open-source. You can crawl/archive a group of websites in a matter of minutes. It's also built to comply with robots.txt exclusion directives and META robots tags.
Apache Nutch
Apache Nutch is a fantastic web crawler software project that you can use to scale out your website. It is particularly well-known for its use in data mining, and it's a JAVA-based cross-platform solution. It is widely used by data analysts, data scientists, application developers, and web text mining engineers for a variety of applications.
What is Web Scraping?
Web scraping is a technique for extracting specific data from websites and exporting it to a local workstation in XML, Excel, JSON, or SQL format. The scripts used to automate this process are called web scrapers which can extract data from any website in a fraction of the time a person would, base on the requirements provided. This task automation is quite beneficial for gathering data for machine learning and other purposes.
How Does Scraping Work?
The first step of web scraping is to request the contents of a specified URL from the target website. In exchange, the scraper receives the desired data in HTML format.
Then, the crawler will parse* the HTML DOM to find the data you specified on your scripts using CSS or XPath selectors.
Note: *HTML parsing is the process of processing HTML code and extracting relevant information such as the page title, links, headings, and so on.
The final step involves downloading and saving the data in a CSV, JSON, or any other database format so that it can be retrieved and utilized manually or in any other software.
We can break the web scraping process into four stages:
- The crawler sends an HTTP request to the server and downloads the target URL’s HTML DOM.
2. Then it will parse the DOM to find the specified elements within the page and ignore the rest of the content.
3. All elements are now extracted.
4. The data is added into the specified database.
Of course, scraping one page isn’t exactly the most useful implementation. So we can add an extra step to this process by adding a web crawling functionality to the web scraper to find and follow specific links within the page.
This will allow you to scrape an entire product category or catalog within a website using navigation links, for example.
When to Use a Web Scraper?
If you want to download the data acquired, web scraping is the way to go because it's a more targeted approach if you consider scraping vs crawling.
For example, to work out how to place their new product in the market, a corporation might take product details from laptops offered on Amazon by scraping Amazon’s data. Using scraping proxies, you can alter the commands and scrape particular information from your target website. After that, you can save the results in a useful format (e.g., JSON, Excel).
In some circumstances, however, web scraping vs web crawling isn’t a debate. In fact, you may want to use both web crawling and scraping to achieve a single goal.
By effectively treating them like step one and step two in your process, you may use a crawler to gather vast amounts of data from prominent websites while using a scraper to extract and retrieve the precise data you require from each crawled page.
Tools for Web Scraping
Cheerio and Puppeteer
Cheerio is a powerful tool for parsing virtually any HTML or XML document implementing a subset of JQuery, designed specifically for the server. It allows you to use CSS and XPath selectors to quickly find elements within the markup, making it a perfect tool for web scraping with Node.js.
Because it does not render the HTML document nor execute JavaScript files, Cheerio’s performance is blazing fast. However, because of this, it’s not the best choice for scraping dynamic pages.
That’s where Puppeteer can shine. By combining Puppeteer’s headless browser manipulation to execute JS, click on links/buttons, scroll down, and more, with the parsing capabilities of Cheerio, you’ll be able to scrape any information you want.
Rvest
Rvest is a library/package (inspired by frameworks like Beautiful Soup ) designed to make web scraping in R simpler.
The beauty of this library is that not only it allows you to scrape specific data from web pages but it can also create high-quality data visualizations, import to several data formats with just a simple command, and manipulate that within the dataframe.
Scraper API
Scraper API is a sophisticated solution that uses third-party proxies, machine learning, enormous browser farms, and years of statistical data to ensure that bot security tactics never stop you.
The web scraping API takes care of proxy rotation, geotargeting, and CAPTCHAs, allowing developers to scrape any page with only one API call.
With over 20 million residential IPs scattered over 12 countries and software capable of rendering JavaScript and solving CAPTCHAs, you’re able to scrape massive amounts of data quickly and without the concern of being blocked by any servers.
Differences Between Web Scraping and Web Crawling
|
Web Scraping |
Web Crawling |
|---|---|
|
It's a tool for obtaining specific elements or data from web pages |
It's a tool for indexing web pages |
|
These types of scripts are called web scrapers |
These types of scripts are called web crawlers, spiders, or bots |
|
It looks for specific elements within a particular page or set of pages |
It goes over each and every page, looking for information till the very last line |
|
It can be done on a small or large scale |
It's primarily used in large-scale projects |
|
In most circumstances, a Web Scraper disregards robots.txt |
Robots.txt is always obeyed |
|
Web scrapers are mainly using data in retail, marketing, equity search, real estate, and machine learning |
Search engines mostly use web crawlers to find new websites or web pages, sort the data and provide users with search results |
|
All scrapers need a parser to locate the information and a crawler to scrape information at scale |
Crawlers just necessitate the use of a crawl agent |
Using Web Crawling and Scraping for Scalability
Since crawling and scraping include related activities, it's easy to get them mixed up. However, web scraping and web crawling have drastic differences and are used to their own unique goals.
By now, it should be obvious that web scraping is critical to a company's success, whether it's for client acquisition or revenue development.
The future of web crawling and web scraping also looks advantageous with high scalability and effective data integration. As the internet becomes the primary source of intelligence for businesses, more publicly available data will be required to scrape in order to gain business insights and stay ahead of the competition.
Don’t miss out on the efficiency of gathering data with web crawling and web scraping.
