Web Scraping A Quick Guide

The method of collecting and processing raw data from the Web is Web scraping, and some of the most useful web scraping tools have been created by the Python community. Web scraping involves collecting information that is available on websites. This can be performed by a human user or a bot manually.  for instance, the latter will capture data even better than a human user, and that is why we would focus on this. Such bots in theory are also able to gather all the data from a website in a matter of minutes.

There are two components required for web scraping: the crawler and the scraper. The crawler is an AI algorithm that browses the web by following the links across the internet to search for the specific data required. Whereas, the scraper is a particular tool created to retrieve the website's data. Depending on the size and scale of the project, the configuration of the scraper can vary considerably to allow the data to be collected rapidly and accurately.


How it Works:

Web Scrapers may retrieve all the details or the basic information that a person needs on specific pages. Ideally, once you decide the details you want, it's better that the web scraper just collects that information easily. For instance, if I wish to scrape a food website for Chinese food, you might just want the data about Chinese food and not other categories of foods.

So, when a web scraper needs to scrape a website, the URLs of the appropriate sites are first provided. Then it loads all the HTML code for those sites and all the CSS and Javascript elements could even be extracted by a more advanced scraper. Then, from this HTML code, the scraper obtains the necessary data and outputs this data in the user-specified format. This is often in the form of an Excel spreadsheet or a CSV file, although it is also possible to store the data in other formats, like a JSON file.

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