Prompt Title: Scraping Justdial Data with Python

To scrape data from Justdial using Python, you can follow these steps:

1. Install the necessary libraries:
   • BeautifulSoup: Used for parsing HTML data
   • requests: Used to send HTTP requests

You can install these libraries using pip:

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pip install beautifulsoup4
pip install requests

2. Import the required libraries in your Python script:

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import requests
from bs4 import BeautifulSoup

3. Send a GET request to the Justdial website's search page:

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def scrape_justdial_data():
    url = 'https://www.justdial.com/Mumbai/Restaurants'
    response = requests.get(url)
    if response.status_code == 200:
        return response.content
    else:
        return None

4. Parse the HTML content using BeautifulSoup:

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def scrape_justdial_data():
    # ...
    if response.status_code == 200:
        soup = BeautifulSoup(response.content, 'html.parser')
        return soup
    else:
        return None

5. Find and extract the relevant data from the parsed HTML:

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def scrape_justdial_data():
    # ...
    if response.status_code == 200:
        soup = BeautifulSoup(response.content, 'html.parser')
        
        # Find the container elements that hold the desired data
        containers = soup.find_all('div', class_='col-sm-5 col-xs-8 store-details sp-detail paddingR0')
        
        for container in containers:
            # Extract specific data from each container
            name = container.find('span', class_='lng_cont_name').text.strip()
            phone = container.find('span', class_='mobilesv').text.strip()
            address = container.find('span', class_='cont_fl_addr').text.strip()
            
            # Print or store the extracted data as needed
            print('Name:', name)
            print('Phone:', phone)
            print('Address:', address)
            print('---')
    else:
        return None

Please note that web scraping should be done responsibly and in compliance with the website's terms of service. Make sure to read and understand the website's terms of use before scraping their data. Additionally, consider incorporating delays in your code to avoid overwhelming the website's server with too many requests.