What's the best way to extract public records from websites?

The best way depends on the site, the records you need, and how much you need to collect. A good approach is:

1. Check for official access first

   • Look for an API, bulk download, data portal, RSS feed, or open records export.
   • Many public-record sites offer these, and they’re more reliable than scraping.

2. Use structured extraction when possible

   • If the site has HTML tables or predictable pages, use a scraper with parsing tools like:
     • Python: requests, BeautifulSoup, lxml, pandas.read_html
     • For dynamic sites: Playwright or Selenium
   • Prefer parsing page content over screenshot/OCR methods.

3. Handle dynamic sites carefully

   • If data loads via JavaScript, inspect network calls in browser dev tools to find underlying JSON endpoints.
   • Often the cleanest solution is calling those endpoints directly.

4. Respect legal and technical limits

   • Review the site’s Terms of Service, robots.txt, and any applicable laws.
   • Avoid bypassing access controls, CAPTCHAs, rate limits, or login restrictions.
   • Use reasonable request rates and identify your user agent if appropriate.

5. Clean and normalize the data

   • Public records often have inconsistent formatting.
   • Standardize dates, names, addresses, IDs, and remove duplicates.

6. Build for reliability

   • Log failures, retry carefully, cache results, and save raw source data for auditability.
   • Expect site layouts to change.

7. Prefer targeted extraction

   • Define exactly which fields you need.
   • Narrow the scope by jurisdiction, date range, or record type to reduce noise and risk.

If you want, I can help you choose the best method for a specific public-record site or show a safe Python example for a page type you have in mind.