I need a robust web-scraper that can harvest spare-parts catalogue data for Toyota, Hyundai, and Chevrolet vehicles sold in Middle-Eastern markets. The script should visit the publicly available online catalogues, work through every model and trim that appears for our region, and return a clean JSON file containing three fields per part: part number, part description, and price (in the currency shown on the source site). Please make the scraper fully automated—once I point it at the target URLs it should crawl, paginate, and store the results without manual intervention. Rate-limiting, captcha handling, and user-agent rotation are important so the source sites remain accessible throughout the run. Deliverables • Production-ready scraper script (Python preferred, but I’ll accept another language if it fits better) • Sample JSON output for a small model set so I can verify structure • Quick README explaining environment setup and how to launch the crawl Acceptance criteria 1. All three requested fields appear and are non-empty for at least 95 % of scraped rows. 2. Output validates as proper JSON and imports without errors. 3. Script completes a full Toyota model crawl without being blocked or flagged. If you can optionally extend the coverage to Nissan later, mention it in your bid; it isn’t required for this phase but might become a follow-up task.