How to Scrape Google Maps Business Data in 2026: A Complete Python Guide

Scraping Google Maps for business data is one of the most valuable skills for marketers, sales teams, and researchers in 2026. Whether you're building a leads database, analyzing competitors, or researching commercial real estate — Google Maps holds a goldmine of structured business information. In this guide, I'll walk you through extracting business data from Google Maps using Python , including names, addresses, phone numbers, hours, ratings, reviews, coordinates, and categories. You'll get working code you can run today. Why Scraping Google Maps Is Hard in 2026 Google Maps is one of the hardest websites to scrape on the internet. Here's why: Heavy JavaScript rendering : The page content loads dynamically via JavaScript. A simple requests.get() returns an empty shell — the actual business data isn't in the initial HTML. Aggressive anti-bot detection : Google uses CAPTCHAs, fingerprinting, rate limiting, and behavioral analysis to detect automated access. Frequent DOM changes : Googl