Web scraping is a technique using which the webpages from the internet are fetched and parsed to understand and extract specific information similar to a human being. Web scrapping consists of two parts:  Web Crawling  Accessing the webpages over the internet and pulling data from them.  HTML Parsing  Parsing the HTML content of the webpages obtained through web crawling and then extracting specific information from it. Hence, web scrappers are applications/bots, which automatically send requests to websites and then extract the desired information from the website output. Let’s take an example:
how do we search for images online?  We go to a website that shows images, and then we enter the keyword to search for the photos.  The website shows us the images.  We decide to download the image(s). What if there is a computer program that can do all of these for us? That’s what web scrappers necessarily do. They try to understand the webpage content as a human would do. Let’s take an example where we need thousands of images to train our object detection/classification model. It is an excellent use case for implementing an image scraper.

The things needed before we start building a python based web scraper are:  Python installed.  A Python IDE (Integrated Development Environment): like PyCharm, Spyder, or any other IDE of choice (Explained Later)  Flask Installed. (A simple command: pip install flask)  MongoDB installed (Explained Later).  Basic understanding of Python and HTML.  Basic understanding of Git (download Git CLI from https://gitforwindows.org/ )