Web Scraping Project - Flipkart Apple Mobiles data

It is the path toward get-together information from the Internet. In fact, even copy sticking the sections of your primary tune is a kind of web scratching! Regardless, the words “web scratching” by and large imply a connection that incorporates computerization. A couple of destinations could do without it when customized scrubbers collect their data, while others would not worry.

Expecting you are scratching a page deliberately for informative items, you are presumably not going to have any issues. Considering everything, it is a keen idea to do some assessment isolated and guarantee that you’re not ignoring any Terms of Service before you start a gigantic degree project. To get comfortable with the legal pieces of web scratching, take a gander at Legal Perspectives on Scraping Data from The Modern Web.

We will be scraping Flipkart

Flipkart is one such eCommerce company that promotes online sales in India. It is not only for accessories, but for a wide range of other daily use items as well, that Flipkart remains as the leading choice of online shoppers. Flipkart, the most prominent eCommerce website in India and is empowering tons of Indian businesses to venture into the competitive online shopping industry. This multi-vendor website serves as the platform for vendors to display their product to the website’s visitors. It was initiated in 2007 and recently achieved a similarweb ranking of 133 globally and 9th amongst the top Indian websites. Flipkart is the first eCommerce website in India that has reached the $1 billion mark.

We will be scraping inside the Mobile section and specifically try to get all the information about Apple Mobiles.

Here is an outline of all the steps we will follow:

1. Download the webpage using "request library
2. Parse the HTML source code using beautiful soup
3. Extract items description, rating, prices, review and image Urls from 8 pages
4. Compile and extracted information into Python lists and dictionaries
5. Extract and combine data from multiple pages
6. Save the extracted information to a CSV file.

By the end of the project, we will created a CSV file in the similar format:

• Each record is located on a separate line, delimited by a line break (CRLF).
  For example:
  
  aaa,bbb,ccc CRLF
  
  zzz,yyy,xxx CRLF