I need a robust Google Maps / Google Business scraping solution that can sweep the entire country for retail stores and pull three specific data points for each result: store name, phone number, and full street address. The scraper must: • Work at a national scale without manual city-by-city input. • Respect Google’s limits through smart delay, proxy, or captcha-handling so it can run unattended. • Export the clean dataset to CSV (Excel-ready) with clearly labeled columns for Name, Phone, and Address. • Be handed over as well-documented Python code (Selenium, Scrapy, BeautifulSoup or similar are fine) so I can rerun or modify it later. Deliverables 1. Working script with all dependencies. 2. One sample CSV showing at least a few hundred rows to prove accuracy. 3. Brief README outlining setup, usage, and any environment variables (e.g., proxy keys). Acceptance Criteria • Script completes a full nationwide pass and captures at least 95 % of visible retail listings. • No duplicates; phone numbers match the store listed; addresses are correctly parsed into a single field. • Runtime logs show error handling for captchas, timeouts, or missing data. If you can optionally capture store websites or opening hours in a future iteration, mention it—right now my priority is the trio above delivered quickly, cleanly, and repeatably.