There are lots of need and various aspects for scrapping web for gather information about target values. Web scrapping has different use cases depends upon working domains.
Most of the use cases lie in the e-commerce, market research, real estate and travel areas.
Here are some use cases:
- Understand customer sentiment and feedback by extracting reviews from e-commerce portals.
- Compare prices of different products from different sites.
- News aggregation sites scrap different new channels website and store it in own database.
- Fueling job boards with job listings.
- Market research using web data.
- Scrapping blogs and forums to keep up trends and news.
- Scrapping top trends on Twitter and Facebook to know about the hot topic of the day and it is very helpful in case of news agencies.
- Perform sentimental analysis in different scenarios as for e-commerce products, movie reviews, hospitality services etc.
What is Web Scrapping?
Web scrapping also termed as web harvesting, web data extracting from different websites and save the data into local computer system or a database(spreadsheet ).
Web scraping is a programming or software(you can use software like import.io) technique of extracting information from websites. This technique mostly focuses on the transformation of unstructured data on the web into structured data.
How to perform web scrapping
There are three ways to implementing web scrapping
- API(Application Programming Interface): By use of web API we can extract data from website, for example, Facebook Graph API by which we can extract Facebook data like trending data, post data etc
- By accessing HTML code webpage for extracting data
- By using some online software like import.io, webscraper.io etc.
Web scrapping is used for contact scrapping and as a component used for web application indexing, web mining and data mining.Online price changing and price comparison, product comparison, product review scraping (to watch the competition), gathering real estate listings, weather data monitoring, research, tracking online presence and reputation, and web data integration.
Step involved in web scrapping
- Send an HTTP request to the URL of the web pages you want to access.The server response the request by returning HTML content of the webpage for this task we use a third party HTTP library like request,urllib etc
- Once we have accessed the HTML content, we are left with the task of parsing the data. Since most of the HTML data is nested, we cannot extract data simply through string processing. One needs a parser which can create a nested/tree structure of the HTML data
- Now, all we need to do is navigating and searching the parse tree that we created, i.e. tree traversal. For this task, we can use another third-party python library, Beautiful Soup. It is a Python library for pulling data out of HTML and XML files.
Libraries used for web scrapping purpose
In this article, we knew about web scrapping technique. Did you find this article helpful? Please share your thoughts in the comment section.