How to scrape Google SERP using Python

Scraping Google Search Engine Results Pages (SERPs) can be a useful task for various purposes, such as SEO analysis, data research, or monitoring search engine rankings. However, it's essential to be aware of Google's Terms of Service and respect their policies when scraping. Be mindful of Google's robots.txt file and consider using an official API if available.
In this tutorial, I'll show you how to scrape Google SERPs using Python and the BeautifulSoup library. Remember that web scraping may violate the terms of service of the website you are scraping, so use this knowledge responsibly.
Prerequisites:
Before we begin, make sure you have the following tools and libraries installed:
You can install these libraries using pip:
Python Code to Scrape Google SERP:
Here's a Python script to scrape Google SERP using BeautifulSoup and requests:
Explanation:
We import the necessary libraries, including requests, BeautifulSoup, and fake-useragent for generating a random User-Agent header (optional but recommended to avoid getting blocked).
The scrape_google_serp function takes a search query and the number of results to retrieve as parameters.
We construct the Google Search URL with the provided parameters.
We send an HTTP GET request to the Google Search URL with the appropriate User-Agent header to mimic a real browser.
If the request is successful (status code 200), we parse the HTML content using BeautifulSoup.
We extract search results from the HTML content and print the title, link, and description of each result.
Finally, we take user input for the search query and the number of results and call the scrape_google_serp function.
Please note that Google frequently updates its search page structure, so this code may need adjustments if Google changes its HTML structure. Always check Google's terms of service and robots.txt file before scraping. It's a good practice to use Google's