Web Scraping With Python Using Beautiful Soup
This article is focused on web scraping using Python. We’re going to use the Beautiful Soup 4 library. The article intends to detail the simple steps required to scrape data from a webpage. We’ll be writing sample code to extract data from the website.
Let’s take a look at the required Python libraries:
requestlibrary to make network requests
To scrape data from a website, we need to extract the content of the webpage. Once the request is made to a website, the entire content of the webpage is available, and we can then evaluate the web content to extract data out from it. The content is made available in the form of plain text.
html5lib library for parsing HTML
Once the content is available, we need to specify the library that represents the parsing logic for the text available. We’ll be using the
html5lib library to parse the text content to HTML DOM-based representation.
beautifulsoup4 library for navigating the HTML tree structure
beautifulsoup4 takes the raw text content and parsing library as the input parameters. In our example, we have exposed
html5lib as a parsing library. It can then be used to navigate and search for elements from the parsed HTML nodes. It can pull data out from the HTML nodes and extract/search required nodes from HTML structure.
Making the Request for the Web Content
Let's make the web request for the website to be scraped. We will be using the
requests library. To start using the
requests library, we need to install the third-party library using the following command
pip install requests
request.get makes a request to the webpage, which returns back the raw HTML content.