I need a robust scraper that reliably pulls complete product data from Amazon at scale. The script will accept a list of product URLs and return a single JSON file containing: • title • price (current and list, if available) • average rating and review count • image URLs • full description and bullet points • ASIN • variation details (size, color, etc.) • stock and availability status Technical expectations • Code in Python or Node.js; Playwright or Puppeteer is preferred for browser automation. • Must navigate Amazon’s anti-bot defenses—rotating residential or datacenter proxies, adaptive rate limiting, and CAPTCHA handling—so the scraper stays stable under heavy use. • Structure the logic for easy scaling (modular functions, clear separation of crawler, parser, and output formatter). • Follow clean-code principles with comments and docstrings so another dev can maintain it. Deliverables 1. Fully working scraper script(s) with a straightforward CLI or function call. 2. Sample JSON output from at least one live product page. 3. Read-me with setup, dependency list, proxy configuration notes, and deployment tips (Docker image or virtual-env steps are fine). 4. Brief explanation of how anti-bot measures are handled and how to extend to CSV or additional fields later. A background in Amazon or other e-commerce scraping is a major plus. If this goes smoothly, I have an ongoing pipeline of similar data extraction work and site-specific scrapers. Let me know your relevant experience and estimated turnaround time, and we can get started.