Beautiful Soup - Overview


In today’s world, we have tons of unstructured data/information (mostly web data) available freely. Sometimes the freely available data is easy to read and sometimes not. No matter how your data is available, web scraping is very useful tool to transform unstructured data into structured data that is easier to read & analyze. In other words, one way to collect, organize and analyze this enormous amount of data is through web scraping. So let us first understand what is web-scraping.

What is web-scraping?

Scraping is simply a process of extracting (from various means), copying and screening of data.

When we do scraping or extracting data or feeds from the web (like from web-pages or websites), it is termed as web-scraping.

So, web scraping which is also known as web data extraction or web harvesting is the extraction of data from web. In short, web scraping provides a way to the developers to collect and analyze data from the internet.

Why Web-scraping?

Web-scraping provides one of the great tools to automate most of the things a human does while browsing. Web-scraping is used in an enterprise in a variety of ways −

Data for Research

Smart analyst (like researcher or journalist) uses web scrapper instead of manually collecting and cleaning data from the websites.

Products prices & popularity comparison

Currently there are couple of services which use web scrappers to collect data from numerous online sites and use it to compare products popularity and prices.

SEO Monitoring

There are numerous SEO tools such as Ahrefs, Seobility, SEMrush, etc., which are used for competitive analysis and for pulling data from your client’s websites.

Search engines

There are some big IT companies whose business solely depends on web scraping.

Sales and Marketing

The data gathered through web scraping can be used by marketers to analyze different niches and competitors or by the sales specialist for selling content marketing or social media promotion services.

Why Python for Web Scraping?

Python is one of the most popular languages for web scraping as it can handle most of the web crawling related tasks very easily.

Below are some of the points on why to choose python for web scraping:

Ease of Use

As most of the developers agree that python is very easy to code. We don’t have to use any curly braces “{ }” or semi-colons “;” anywhere, which makes it more readable and easy-to-use while developing web scrapers.

Huge Library Support

Python provides huge set of libraries for different requirements, so it is appropriate for web scraping as well as for data visualization, machine learning, etc.

Easily Explicable Syntax

Python is a very readable programming language as python syntax are easy to understand. Python is very expressive and code indentation helps the users to differentiate different blocks or scoopes in the code.

Dynamically-typed language

Python is a dynamically-typed language, which means the data assigned to a variable tells, what type of variable it is. It saves lot of time and makes work faster.

Huge Community

Python community is huge which helps you wherever you stuck while writing code.

Introduction to Beautiful Soup

The Beautiful Soup is a python library which is named after a Lewis Carroll poem of the same name in “Alice’s Adventures in the Wonderland”. Beautiful Soup is a python package and as the name suggests, parses the unwanted data and helps to organize and format the messy web data by fixing bad HTML and present to us in an easily-traversible XML structures.

In short, Beautiful Soup is a python package which allows us to pull data out of HTML and XML documents.