explanation each code line by line experiment 5 - FarhaKousar1601/DATA-SCIENCE-AND-ITS-APPLICATION-LABORATORY-21AD62- GitHub Wiki

Aim

Develop a mini-project for simple web scraping on Instagram to extract post links and image URLs from a profile using Python's requests and BeautifulSoup.

Code Explanation

Here is the revised code for scraping Instagram:

import requests
from bs4 import BeautifulSoup

# URL of the Instagram profile you want to scrape
url = 'https://www.instagram.com/openai/'

# Send a GET request to the URL
response = requests.get(url)

# Check if the request was successful (status code 200)
if response.status_code == 200:
    # Parse the HTML content of the page
    soup = BeautifulSoup(response.text, 'html.parser')

    # Find all post elements
    posts = soup.find_all('div', class_='v1Nh3')

    # Extract data from each post
    for post in posts:
        # Extract post link
        post_link = post.find('a')['href']
        
        # Extract post image URL
        image_url = post.find('img')['src']
        
        print(f"Post Link: {post_link}")
        print(f"Image URL: {image_url}")
        print("------")
else:
    print("Failed to retrieve data from Instagram")

Explanation

  1. Import Libraries

    import requests
from bs4 import BeautifulSoup
    • requests: For sending HTTP requests.
    • BeautifulSoup: For parsing HTML content.

  2. Define URL

    url = 'https://www.instagram.com/openai/'
    • Replace with the URL of the Instagram profile you wish to scrape.

  3. Send GET Request

    response = requests.get(url)

  4. Check Request Status

    if response.status_code == 200:
    • Ensure the request was successful.

  5. Parse HTML Content

    soup = BeautifulSoup(response.text, 'html.parser')

  6. Find Post Elements

    posts = soup.find_all('div', class_='v1Nh3')

  7. Extract and Print Data

    for post in posts:
    post_link = post.find('a')['href']
    image_url = post.find('img')['src']
    print(f"Post Link: {post_link}")
    print(f"Image URL: {image_url}")
    print("------")

  8. Handle Failed Request

    else:
    print("Failed to retrieve data from Instagram")

Output

The expected output should be:

Post Link: /openai/post/1/
Image URL: https://scontent.cdninstagram.com/v/t51.2885-15/1234567890...
------
Post Link: /openai/post/2/
Image URL: https://scontent.cdninstagram.com/v/t51.2885-15/0987654321...
------
...

Notes

  • Instagram Scraping Restrictions: Instagram's HTML structure may change frequently, and scraping is against Instagram's terms of service. Using Instagram's API or other legal methods to access data is recommended.
  • Dynamic Content: Instagram often loads content dynamically with JavaScript, which requests and BeautifulSoup might not handle. For such cases, tools like Selenium or Puppeteer might be needed.

This project demonstrates basic web scraping techniques but always adhere to the website's terms of service and legal guidelines. Here are potential viva questions and answers based on the mini-project for web scraping Instagram:

Viva Questions and Answers

Question 1: What is the purpose of the code you have written?

Answer: The purpose of the code is to perform web scraping on an Instagram profile to extract post links and image URLs. This is done by sending an HTTP GET request to the Instagram profile URL, parsing the HTML content of the page, and then extracting specific elements related to posts.

Question 2: What libraries are used in the code, and what are their purposes?

Answer: The code uses the following libraries:

  • requests: This library is used for sending HTTP requests to the Instagram profile URL.
  • BeautifulSoup: This library is used for parsing the HTML content of the page to find and extract information about posts.

Question 3: Explain the process of sending a GET request and handling its response.

Answer: The process involves:

  1. Sending the GET Request: requests.get(url) is used to send a GET request to the specified Instagram profile URL.
  2. Handling the Response: The response from the server is checked for a status code of 200, which indicates that the request was successful. If successful, the HTML content is parsed; otherwise, an error message is printed.

Question 4: How does the code parse and extract data from the HTML content?

Answer:

  • Parsing HTML: BeautifulSoup(response.text, 'html.parser') is used to parse the HTML content of the response.
  • Extracting Data:
    • soup.find_all('div', class_='v1Nh3') finds all div elements with the class v1Nh3, which are assumed to contain post information.
    • For each post element, the code extracts:
      • Post Link: post.find('a')['href'] gets the link to the post.
      • Image URL: post.find('img')['src'] gets the URL of the image associated with the post.

Question 5: What does the response.status_code check do in the code?

Answer: The response.status_code check ensures that the HTTP request was successful. A status code of 200 indicates that the request was successfully processed by the server. If the status code is not 200, it means there was an issue with retrieving the page, and an error message is printed.

Question 6: What challenges might you face with scraping Instagram, and how could you address them?

Answer: Challenges include:

  • Dynamic Content: Instagram often loads content dynamically using JavaScript, which requests and BeautifulSoup may not handle. To address this, tools like Selenium or Puppeteer, which can interact with JavaScript-rendered content, can be used.
  • Changes in HTML Structure: Instagram’s HTML structure may change, making the scraping code unreliable. Regular updates to the scraping code are necessary to adapt to such changes.
  • Legal and Ethical Issues: Scraping social media sites like Instagram may violate their terms of service. It is important to consider using official APIs or obtaining permission to access data.

Question 7: What would be an alternative approach if the Instagram profile content is dynamically loaded?

Answer: If the content is dynamically loaded, an alternative approach would be to use a tool like Selenium or Puppeteer. These tools can automate a web browser to interact with the page as a user would, allowing them to handle dynamically loaded content and JavaScript.

Question 8: How would you handle the situation if Instagram blocks your IP address due to scraping?

Answer: To handle IP blocking:

  • Respect Robots.txt: Always check and comply with the site's robots.txt file to understand their scraping policies.
  • Use Proxies: Rotate IP addresses by using proxy servers to distribute requests.
  • Rate Limiting: Implement delays between requests to avoid overwhelming the server and reduce the likelihood of getting blocked.

Question 9: How would you improve the current scraping code to handle potential issues more robustly?

Answer: Improvements could include:

  • Error Handling: Add exception handling to manage unexpected issues during requests and parsing.
  • User-Agent: Set a User-Agent header in the request to mimic a real browser and reduce the chance of being blocked.
  • Data Validation: Implement checks to ensure that extracted data is valid and handle missing or unexpected values gracefully.

These questions and answers should help demonstrate a thorough understanding of the web scraping project and its underlying concepts.