Web scraping is now an absolute necessity because the Internet is a vast repository of information valuable to researchers, companies, and government agencies. Information ranging from reviews of customers of products to human feelings on social issues and even IoT-generated information can be found on the Internet.
There are, however, intricately composed HTML documents that appear complex and messy. Extracting information from them is a challenging job. No matter how messy an HTML document is, you can get information from them using the proper tools and skills. Through this tutorial, you’ll learn the methods to extract HTML data.
How to Scrape HTML data for Coders?
If you’re a coder, options are abundant in scraping HTML data. This is because there is an abundance of tools you can choose from. Specific tools offer complete scraping capabilities, while others provide an instrument you have to utilize. Let’s look at these below.
Web Scraping Libraries and Framework
Many programming languages can be utilized to extract data from the web. All you need is the ability to make HTTP requests as well as a way to decode data from the raw HTML data. If you can figure out the method to accomplish these two tasks in your programming language, you’ll be capable of scraping HTML data.
Interestingly, many of the most popular programming languages have frameworks and libraries that allow users to extract information from the Internet. One of the issues these frameworks and libraries have in common is that they depend on the language.
The libraries available to Python developers are different from those Java programmers can access. This is why it’s impossible to complete the libraries and frameworks available in any programming language.
However, we can look over the most popular frameworks and libraries available for some of the most well-known programming languages.
Python Libraries and Framework for Web Scraping
Python is among the top well-known web scraping software due to its easy syntax, easy-to-learn nature, and extensive library support in web scraping. Here are a few most well-known web scraping tools you can employ for scraping data out of HTML.
Beautifulsoup and Requests
Two tools exist. The request library is user-friendly and allows you to send HTTP requests. It is used to download HTML websites. Beautifulsoup library is an extraction library. It is based on parsers and allows easy navigation of HTML elements to extract crucial information points. The two programs are the simplest method to master and utilize.
A simple sample of this is here.
You’ll require an online scraping library or framework such as BeautifulSoup, LXML, or Selenium to scrape HTML data. Here’s an example of how you can make use of BeautifulSoup library to extract HTML data from a website:
Installation of the BeautifulSoup library with pip:
pip install beautifulsoup4
2 Import the modules you need in the Python script:
from bs4 import BeautifulSoup
3 Use the request module to send a GET call to the website you wish to extract information. For instance:
url = “http://www.example.com”
response = requests.get(url)
4 Make use of the BeautifulSoup module, to decode the HTML contents from the request. Examples:
soup = BeautifulSoup(response.content, “html.parser”)
5 Utilize the BeautifulSoup object to get the data you require. For instance, if you would like to scrape all the hyperlinks on this page, then you can use search_all() method such as this:
links = soup.find_all(“a”)
6 Make use of a for loop repeatedly, go through all the links, and print the URL and text of each one. For instance:
for link in links:
This is a basic example, but it’ll provide a great base to scrape HTML data with BeautifulSoup library.
HTML data scraping refers to removing essential data elements from HTML websites. It involves using specialized web automation robots referred to as web scrapers. These are used to download the original HTML pages and then use parsers to scan and extract key information points that interest you from the pages.