People often ask about these terms interchangeably. However, there is a distinction. Web Crawling and Web Scraping are frequently used anonymously. Even though these terms share many similarities, they are significant distinctions.
Let’s examine the definitions of these terms and the distinctions between them.
Web crawling, also known as indexing, is used to index the page’s content with the aid of bots known as crawlers. Crawling is the primary function of search engines. It is all about viewing and indexing a page holistically. When a bot crawls a website, it examines every page and links to the last line, searching for ANY information.
Major search engines such as Google, Bing, Yahoo, statistical organizations, and large web aggregators utilize Web Crawlers. Web scraping focuses on specific data set fragments, whereas web crawling primarily collects generic data.
Web scraping often referred to as web data extraction, is comparable to web crawling in that it detects and locates the desired data on web pages. With web scraping, we know the particular data set identifier, such as an HTML element structure, from which data must be scraped from online pages that are being modified.
Web scraping is an automated technique for retrieving specified datasets using scrapers or bots. Once the relevant information has been obtained, it can be used for comparison, verification, and analysis following the demands and objectives of a certain organization.
Web Scraping: Web Scraping is a technique used to extract a vast quantity of data from websites and save it to the local computer in XML, Excel, or SQL format. Web scraping instruments are known as web scrapers. Based on the provided specifications, they can extract data from any website fraction of the time. This operations automation is extremely beneficial for developing data for machine learning and other applications. They operate in four stages:
- Sending the request to the specified page.
- Receiving a response from the page of interest.
- Extracting and parsing the response.
- Download the records.
Different Purposes of Web Crawling and Web Scraping
The aim and operation of these two things diverge significantly upon closer inspection.
In web scraping, the focus is on the data. The data fields that you wish to extract from particular websites. With scraping, you typically know the target websites; you may not know the individual page URLs, but you know the domains at the very least.
With crawling, neither the URLs nor the domains are likely known. And this is the purpose of crawling: to discover URLs so that you can utilize them in the future. For instance, search engines crawl the Internet to index pages and present them in search results.
But another example of data crawling would be when you want to collect data from a single website – you know the domain – but you do not have the page URLs for that website. So you have no idea which pages to scrape. Therefore, you must first develop a crawler that outputs all the URLs of the pages you care about, whether in a given category or a particular website section. Or perhaps the URL must contain a specific term, in which case you would collect all of these URLs and then develop a scraper that collects predefined data fields from the pages.
Common Web Crawling and Web Scraping
Here are some of the most common ways firms use web scraping to achieve their business objectives:
- Data is frequently a vital component of research projects, whether strictly academic or have marketing, financial, or other corporate implications. When attempting to avert a worldwide pandemic or identify a specific target audience, the capacity to collect user data in real-time and recognize behavioral patterns can be crucial.
- Retail / eCommerce: Businesses, particularly in the eCom industry, must do regular market studies to preserve a competitive advantage. Both front- and back-end retail firms collect relevant data sets, such as pricing, reviews, inventory, and special offers.
- Brand Protection: Data collecting is becoming a vital component of protecting against brand fraud and brand dilution, as well as detecting hostile actors that profit illegally from company intellectual property (names, logos, item reproductions). Collecting data enables businesses to monitor, recognize, and take measures against cybercriminals.
Now that you understand the distinction between web crawling and web scraping, all you need to do is select the optimal method for your particular use case. You must assess your budget and whether or not you have an in-house team that can manage the data collection process or whether you would rather outsource this to a data collection network.
Check out: Web Scraping And Its Relation With Python