Data or the web scraping is the process of extracting data from a web page on the internet.
Why is data scraping so essential?
Web scraping makes it easy to retrieve data from a webpage. Any kind of user can access the data with the help of web scraping. Without web scraping, the internet would be less useful and small.
What is the difference between Web scraper and Web crawler?
A web crawler is used for storing and downloading a huge amount of data by following the links. Search engines depend on the web crawler.
Meanwhile, a web scraper is particularly built to handle a specific website. It uses this specific structure to extract the data which could be the address, images, prices, etc.
Where could web scraper possibly be used?
Web scrapers can be used to automate things. Web scraper can be used to order a pizza or to book a ticket automatically the moment they are available. Some of the uses of a web scraper are given below:-
- Search engines
The entire search engine business is based on the web scraping.
Web scrapers are used to monitor the price on the e-commerce website. Web scrapers gather the data from these sites and then compare the products or inform about the price drops.
- Research Purposes
Researchers work a lot on gathering and cleaning the data from the websites. A web scraper can help them to automate the manual work.
Web scraper works by downloading the content or data from the website and then it extracts the data from it.
A web Scraper has the following components
- Web crawling
Web crawling is the process where the navigation happens by making an HTTP request. The request is made using a pattern. The crawler then downloads the response in the form of HTML and passes it to the extractor.
The downloaded HTML is then processed by the parsers that extract the valuable data from the techniques like HTML parsing, Artificial Intelligence or regular expressions.
- Data cleaning followed by the transformation
This component filters the data into a more structured form and fits it to be saved in the database, JSON, etc. this takes the records and fits it in a queue which is then later read by the data writer.
- Serialization of the data and its storage.
Reads the data from the queues and writes it into the format like JSON, CSV, etc. or it can also load it in the non-relational or relational database depending upon the format.
How to build a data scraper
A data scraper can be made by writing codes for each of the module listed above. A framework equipped with the abstracted layers of this framework can also be used.
Writing code from the start helps to build a small data scraper but when the project is large, the use of the framework is much beneficial.