Scrape Housing Society Prices

I need up-to-date price information for Indian housing societies gathered from 99acres, Magicbricks and Housing.com, then exported into a clean Excel file. The workflow is straightforward: the script (Python preferred, and I’m fine with BeautifulSoup, Scrapy or Selenium if dynamic content makes it necessary) should read a list of society names or URLs, visit the relevant pages on those three portals, capture key price fields, and append the results to the spreadsheet.

Key points
• Data fields: current price range, price-per-sq-ft, number of active listings, last-updated date and the direct page URL.
• Input flexibility: I’ll supply a CSV or plain text list of society names; the scraper should map each name to its matching page even when the URL structure differs across portals.
• Output: one Excel workbook with a separate sheet per website, columns consistently labelled and formatted.
• Reliability: handle pagination, gracefully skip captchas or temporarily blocked requests, and log any failed look-ups so I know what needs manual review.
• Re-run ready: when I rerun the script it should overwrite or append data without breaking the existing file.

Deliverables
1. Fully commented source code.
2. A brief README describing setup, libraries used and execution steps.
3. The first successful data pull in Excel so I can verify accuracy.

I’m eager to start as soon as you can outline your approach and estimated turnaround.