Today we’ll discuss how to use the BeautifulSoup library to extract content from an HTML page. After extraction, we’ll convert it to a Python list or dictionary using BeautifulSoup!

What is web scraping, and why do I need it?

The simple answer is this: not every website has an API to fetch content. You might want to get recipes from your favourite cooking website or photos from a travel blog. Without an API, extracting the HTML, or scraping, might be the only way to get that content. I’m going to show you how to do this in Python.

Not all websites take kindly to scraping and some may prohibit it explicitly. Check with the website owners if they're okay with scraping.

How do I scrape a website in Python?

In order for web scraping to work in Python, we’re going to perform 3 basic steps:

  1. Extract the HTML content using the Requests library.
  2. Analyse the HTML structure and identify the tags which have our content.
  3. Extract the tags using BeautifulSoup and put the data in a Python list.

Installing the libraries

Let’s first install the libraries we’ll need. Requests fetches the HTML content from a website. BeautifulSoup parses HTML and converts it to Python objects. To install these for Python 3, run:

pip3 install requests beautifulsoup4

Extracting the HTML

For this example, I’ll choose to scrape the Technology section of this website. If you go to that page, you’ll see a list of articles with title, excerpts, and publishing date. Our goal is to create a list of articles with that information.

The full URL for the Technology page is:

We can get the HTML content from this page using Requests :

import requests

url = ''

data = requests.get(url)


The variable data will contain the HTML source code of the page.

Extracting content from the HTML

To extract our data from the HTML received in data, we’ll need to identify which tags have what we need.

If you skim through the HTML, you’ll find this section near the top:

<div class="col">
  <a href="/2021/08/using-variables-in-jekyll-to-define-custom-content" class="post-card">
    <div class="card">
      <div class="card-body">
        <h5 class="card-title">Using variables in Jekyll to define custom content</h5>
        <small class="card-text text-muted">I recently discovered that Jekyll's config.yml can be used to define custom
          variables for reusing content. I feel like I've been living under a rock all this time. But to err over and
          over again is human.</small>
      <div class="card-footer text-end">
        <small class="text-muted">Aug 2021</small>

This is the section which repeats throughout the page for every article. We can see that .card-title has the article title, .card-text has the excerpt, and .card-footer > small has the publishing date.

Let’s extract these using BeautifulSoup.

import requests
from bs4 import BeautifulSoup
from pprint import pprint

url = ''
data = requests.get(url)

my_data = []

html = BeautifulSoup(data.text, 'html.parser')
articles ='')

for article in articles:

    title ='.card-title')[0].get_text()
    excerpt ='.card-text')[0].get_text()
    pub_date ='.card-footer small')[0].get_text()

    my_data.append({"title": title, "excerpt": excerpt, "pub_date": pub_date})


The above code will extract the articles and put them in the my_data variable. I’m using pprint to pretty print the output but you can skip it in your own code. Save the code above in a file called, and then run it using:


If everything went fine, you should see this:

[{'excerpt': "I recently discovered that Jekyll's config.yml can be used to "
"define custom variables for reusing content. I feel like I've "
'been living under a rock all this time. But to err over and over '
'again is human.',
'pub_date': 'Aug 2021',
'title': 'Using variables in Jekyll to define custom content'},
{'excerpt': "In this article, I'll highlight some ideas for Jekyll "
'collections, blog category pages, responsive web-design, and '
'netlify.toml to make static website maintenance a breeze.',
'pub_date': 'Jul 2021',
'title': 'The evolution of Jekyll, Bootstrap, Netlify, '
'static websites, and responsive design.'},
{'excerpt': "These are the top 5 lessons I've learned after 5 years of "
'pub_date': 'Jul 2021',
'title': '5 key best practices for sane and usable Terraform setups'},

... (truncated)

And that’s all it takes! In 22 lines of code we’ve built a web scraper in Python. You can find the source code in my example repo.


With the website content in a Python list, we can now do cool stuff with it. We could return it as JSON for another application or convert it to HTML with custom styling. Feel free to copy-paste the above code and experiment with your favourite website.

Have fun, and keep coding :)