3i Data Scraping Services Blogs

  Today, we'll look at a simple and effective way to scrape Groupon deal data using Python and BeautifulSoup. The main objective of this post is to get you started on real-world solving problems while making them as easy as possible so that you can become familiar with them and receive real applications as quickly as feasible. So, the only thing we need to assure is to install Python 3. If not installed, then you can initially install Python 3 and then proceed. Afterward, you can install BeautifulSoup with: Install BeautifulSoup pip3 install beautifulsoup4 To fetch data, split it down to XML, and apply CSS selectors, we'll also require the libraries’ requirements, soupsieve, and LXML. Install them by following these steps: pip3 install requests soupsieve lxml After installation, you need to open an editor and type: # -*- coding: utf-8 -*- from bs4 import BeautifulSoup import requests Now, let us visit the Groupon page and check the information we get. This is how it will look.

  Data You Can Scrape from H&M Product’s Name Pricing Total Reviews Product’s Description Product’s Details The screenshot provided below indicates various data fields, which we scrape at 3i Data Scraping: Requests Google’s Chrome Browser:  You would require to download the Chrome browser and the extension requires the Chrome 49+ version. Web Scraping for Chrome Extension:  Web Scraper extension could be downloaded from Chrome’s Web Store. Once downloaded the extension, you would get a spider icon included in the browser’s toolbar. Finding the URLs H&M helps you to search products that you could screen depending on the parameters including product types, sizes, colors, etc. The web scraper assists you to scrape data from H&M as per the requirements. You could choose the filters for data you require and copy corresponding URLs. In Web Scraper toolbars, click on the Sitemap option, choose the option named “Edit metadata’ to paste the new URLs (as per the filter) as Start URL.