Differentiation of Web Scraping and Web Crawling
Most of us get confused between the word’s web scraping and web crawling, and even some people think they are synonyms for each other.
But there is a considerable difference between them which we are going to know in this tutorial.
Based on Definition
Web Scraping:
It is a well-known technique that helps in data extraction from different web pages and stored on a local machine. Web Scrapers are the tools used in Web Scraping, also called web data extraction.
By using this method, we can extract any data from a webpage by targeting the specific HTML elements on the page.
This is an automation process where the extraction of identified datasets in the website happens.
This process includes some steps:
- Requesting the target webpage.
- Collecting responses from the target webpage.
- Extraction of required data from the obtained response.
- Saving the extracted data.
Examples of web scrapers include Scrapy, Scraper API, Pro Web Scraper, etc.
Web Scraping is mainly used in retail and e-commerce companies to analyze the performance and feedback of customers. It is also used in research project works for the identification of trends in marketing or financial applications. It also helps in eliminating cyber-attacks by identifying the data and also by monitoring.
Web Crawling:
It is also known as spider crawling, where crawling happens upon websites used to obtain links and URLs on the webpage. First, after visiting the webpage, reading and analysis of webpages happen, which makes indexing the web pages easier.
Web crawlers or spiders are said to be the tools used for web crawling. A deep search takes place in the process of crawling, where links existing on the webpages are even followed to obtain more links, and related information gets collected.
In this technique, we don’t know the domains or specific URLs to do something, but search engines like Google, Bing, and Yahoo crawl the webpages to provide indexing for them and arrange them in order while searching.
For example, if we want to obtain certain URLs from a webpage and we don’t know the exact pages we are looking for, then we create a web crawler and obtain all the links existing in all the pages and use a web scraper to extract the data fields from those that we specify.
Based on Advantages
Benefits of Web Scraping:
- Optimum cost: This technique can be applied with minimum cost as it can be operated with less staff. It is an automation process where we have complete access and needs no infrastructure at all.
- Accuracy: It eliminates most of the errors that are made by us while performing operations and ensures one hundred percent accuracy for the data.
- Timesaving: As the web scrapers filter the exact information we are looking for from the websites, we can get the job done in less time which saves our resources in the long term.
Benefits of Web Crawling:
- Deep searching: This technique goes on depth indexing of targeted webpage and can cover whole content underlying in the webpage. It returns the whole collected data crawled from the website.
- Practical: It is preferred by the companies dealing with real-time applications with their target data fields so that they can reach current levels.
- Quality: It ends up providing quality data sets consisting of important links and URLs. It is an unfair advantage for crawlers as they are better at performing tasks.
Based on the Output:
Web crawling provides a list of URLs as the main output, and there can be other data sets or information, but links are the primary product.
Web scraping provides data fields specified by the HTML element where the scope can be broader and may consist of links in the output data.
These also include:
- Feedback from customers.
- Product catalogue / ratings.
- Pricing of products.
- Images from different resources.
- Results and queries obtained by search engines.
Generally, in the extraction projects, we need to use both crawling and scraping to discover the URLs and then extract the data from those pages. We may further process the information or store it in the database.
There are some anti-scraping and crawling policies for many web pages, which makes it difficult to collect and analyse the data from them.