Beautiful Soup – Overview

In today’s world, we have a vast amount of unstructured data/information (primarily web data) freely available. Sometimes, this freely available data is easy to read, and sometimes it’s not. Regardless of how your data is obtained, web scraping is a very useful tool for transforming unstructured data into structured data that is easier to read and analyze. In other words, one way to collect, organize, and analyze this vast amount of data is through web scraping. So, let’s first understand what web scraping is.

What is Web Scraping

Scraping is simply the process of extracting (from various sources), copying, and filtering data.

When we scrape or extract data or information from the web (such as from web pages or websites), it is called web scraping.

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

Why Web Scraping?

Web scraping provides a great tool for automating much of what humans do when browsing. Web scraping is used in a variety of ways within businesses, including:

Data for Research

Instead of manually collecting and cleaning data from websites, smart analysts (such as researchers or journalists) use web scrapers.

Product Price and Popularity Comparison

There are services that use web scrapers to collect data from many online websites and use it to compare product popularity and prices.

SEO Monitoring

There are many SEO tools, such as Ahrefs, Seobility, and SEMrush, that are used for competitive analysis and extracting data from client websites.

Search Engines

There are some large IT companies whose businesses rely entirely on web scraping.

Sales and Marketing

The data collected through web scraping can be used by marketers to analyze different niches and competitors, or by sales professionals to sell content marketing or social media promotion services.

Why Use Python for Web Scraping

Python is one of the most popular languages for web scraping because it can easily handle most web scraping-related tasks.

Here are some key reasons why Python is a good choice for web scraping:

Ease of Use

Most developers agree that Python is very easy to code in. We don’t have to use any curly braces ({ }) or semicolons (;), making it more readable and easier to use when developing web scraping tools.

Extensive Library Support

Python offers a wide range of libraries for different needs, making it suitable for web scraping, data visualization, machine learning, and more.

Easy-to-understand Syntax

Python is a very readable programming language because its syntax is easy to understand. Python is very expressive, and code indentation helps users distinguish between different blocks or sections of the code.

Dynamically Typed Language

Python is a dynamically typed language, meaning that the data assigned to a variable tells you what type it is. This saves a lot of time and makes work faster.

Large Community

The large Python community is here to help you with any problems you encounter while writing code.

Introduction to Beautiful Soup

Beautiful Soup is a Python library named after the poem of the same name by Lewis Carroll in “Alice’s Adventures in the Wonderland.” Beautiful Soup is a Python package that, as the name suggests, parses unsolicited data and helps organize and format messy web data by fixing poorly written HTML and presenting it in an easy-to-use XML structure.

In short, Beautiful Soup is a Python package that allows us to extract data from HTML and XML documents.