Scraping Google Maps: Extracting Business Data at Scale

Why Google Maps Data Is Valuable Google Maps contains the most comprehensive database of local businesses on the planet. For lead generation, market research, and competitive analysis, this data is gold. Names, addresses, phone numbers, reviews, ratings, hours — all structured and queryable. Let's build a scraper that extracts business data from Google Maps at scale. The Challenge Google Maps is a JavaScript-heavy single-page application. Traditional HTTP requests won't work — you need either browser automation or a specialized API proxy. Approach 1: Using ScraperAPI with Google Maps The simplest approach is using ScraperAPI which handles rendering and anti-bot protection: import requests import csv from urllib.parse import quote from bs4 import BeautifulSoup import time class GoogleMapsScraper : def __init__ ( self , api_key ): self . api_key = api_key self . base = " https://api.scraperapi.com " def search_places ( self , query , location ): """ Search Google Maps for businesses. """