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Extract JSON from HTML using BeautifulSoup in Python

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In this article, we are going to extract JSON from HTML using BeautifulSoup in Python.

Module needed

  • bs4: Beautiful Soup(bs4) is a Python library for pulling data out of HTML and XML files. This module does not come built-in with Python. To install this type the below command in the terminal.
pip install bs4
  • requests: Request allows you to send HTTP/1.1 requests extremely easily. This module also does not come built-in with Python. To install this type the below command in the terminal.
pip install requests


  • Import all the required modules.
  • Pass the URL in the get function(UDF) so that it will pass a GET request to a URL, and it will return a response.

Syntax: requests.get(url, args)

  • Now Parse the HTML content using bs4.

Syntax: BeautifulSoup(page.text, ‘html.parser’)


  • page.text : It is the raw HTML content.
  • html.parser : Specifying the HTML parser we want to use.
  • Now get all the required data with find() function.

Now find the customer list with li, a, p tag where some unique class or id. You can open the webpage in the browser and inspect the relevant element by pressing right-click as shown in the figure.

  • Create a Json file and use json.dump() method to convert python objects into appropriate JSON objects.

Below is the full implementation:


# Import the required modules
import requests
from bs4 import BeautifulSoup
import json
# Function will return a list of dictionaries
# each containing information of books.
def json_from_html_using_bs4(base_url):
    # requests.get(url) returns a response that is saved
    # in a response object called page.
    page = requests.get(base_url)
    # page.text gives us access to the web data in text
    # format, we pass it as an argument to BeautifulSoup
    # along with the html.parser which will create a
    # parsed tree in soup.
    soup = BeautifulSoup(page.text, "html.parser")
    # soup.find_all finds the div's, all having the same
    # class "col-xs-6 col-sm-4 col-md-3 col-lg-3" that is
    # stored in books
    books = soup.find_all(
        'li', attrs={'class':
                'col-xs-6 col-sm-4 col-md-3 col-lg-3'})
    # Initialise the required variables
    star = ['One', 'Two', 'Three', 'Four', 'Five']
    res, book_no = [], 1
    # Iterate books classand check for the given tags
    # to get the information of each books.
    for book in books:
        # Title of book in <img> tag with "alt" key.
        title = book.find('img')['alt']
        # Link of book in <a> tag with "href" key
        link = base_url[:37] + book.find('a')['href']
        # Rating of book from
<p> tag
        for index in range(5):
            find_stars = book.find(
            'p', attrs={'class': 'star-rating ' + star[index]})
            # Check which star-rating class is not
            # returning None and then break the loop
            if find_stars is not None:
                stars = star[index] + " out of 5"
        # Price of book from
<p> tag in price_color class
        price = book.find('p', attrs={'class': 'price_color'
        # Stock Status of book from
<p> tag in
        # instock availability class.
        instock = book.find('p', attrs={'class':
                        'instock availability'}).text.strip()
        # Create a dictionary with the above book information
        data = {'book no': str(book_no), 'title': title,
            'rating': stars, 'price': price, 'link': link,
            'stock': instock}
        # Append the dictionary to the list
        book_no += 1
    return res
# Main Function
if __name__ == "__main__":
    # Enter the url of website
    # Function will return a list of dictionaries
    res = json_from_html_using_bs4(base_url)
    # Convert the python objects into json object and export
    # it to books.json file.
    with open('books.json', 'w', encoding='latin-1') as f:
        json.dump(res, f, indent=8, ensure_ascii=False)
    print("Created Json File")


Created Json File

Our JSON file output:

My Personal Notes arrow_drop_up
Last Updated : 16 Dec, 2021
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