Hawkins Cooker Review Scraper
Budget: ₹600 – ₹1,500 INR
I need a Jupyter Notebook that lets me pull customer reviews for the Hawkins pressure cooker from both Flipkart and Amazon at the click of Run. The scraping logic must rely on Selenium for page navigation and BeautifulSoup for parsing, so please wire those two libraries together cleanly.
Structure the notebook so I can keep each marketplace separate—either two standalone functions or one dispatcher that calls scrape_flipkart() and scrape_amazon() internally is fine, as long as I can run them individually when I only need data from a single site. The code must execute end-to-end on my local machine without tweaks, so include everything: WebDriver setup, helpful comments, and any import or path instructions right inside the first cell.
I do not have fixed URLs yet; sometimes I’ll paste a product link, other times I’ll want the code to search “Hawkins cooker” and pick the first matching product page. Please cover both scenarios with optional parameters.
A pandas DataFrame return is enough for now—I can decide later whether to export to CSV, JSON, or Excel—so just make sure the DataFrame includes the reviewer name, rating, and full text.
Deliverables:
• One well-commented .ipynb notebook ready to run in Jupyter
• Clean, reusable Python functions for Flipkart and Amazon scraping built with Selenium + BeautifulSoup
• Clear instructions (inside the notebook) on any driver versions or one-time environment steps
Once I hit Run, I should see the reviews rolled up in a DataFrame without manual intervention.
Structure the notebook so I can keep each marketplace separate—either two standalone functions or one dispatcher that calls scrape_flipkart() and scrape_amazon() internally is fine, as long as I can run them individually when I only need data from a single site. The code must execute end-to-end on my local machine without tweaks, so include everything: WebDriver setup, helpful comments, and any import or path instructions right inside the first cell.
I do not have fixed URLs yet; sometimes I’ll paste a product link, other times I’ll want the code to search “Hawkins cooker” and pick the first matching product page. Please cover both scenarios with optional parameters.
A pandas DataFrame return is enough for now—I can decide later whether to export to CSV, JSON, or Excel—so just make sure the DataFrame includes the reviewer name, rating, and full text.
Deliverables:
• One well-commented .ipynb notebook ready to run in Jupyter
• Clean, reusable Python functions for Flipkart and Amazon scraping built with Selenium + BeautifulSoup
• Clear instructions (inside the notebook) on any driver versions or one-time environment steps
Once I hit Run, I should see the reviews rolled up in a DataFrame without manual intervention.