How to Scrape Google Maps in 2026: API and Python Guide

The fastest way to scrape Google Maps in 2026 is to call a structured Maps API that returns normalized JSON — business name, address, phone, website, rating, reviews, and coordinates — instead of driving a headless browser yourself. You can still build a DIY scraper in Python, but Maps' infinite scroll, frequent layout changes, and anti-bot defenses make it expensive to maintain. This guide covers all three approaches, what each returns, where each breaks, and the legal basics.

Is it legal to scrape Google Maps?

Scraping public Google Maps data (business names, addresses, ratings, reviews) sits in the same general category as other public-web scraping. In the US, the hiQ Labs v. LinkedIn litigation held that accessing publicly available data does not violate the Computer Fraud and Abuse Act. That said, Google's Terms of Service prohibit automated access, so you can still face account blocks or cease-and-desist letters, and personal data triggers privacy laws such as GDPR and CCPA. Rules of thumb:

• Collect only public business data; avoid personal data and anything behind a login.
• Respect rate limits and don't degrade the service.
• Review Google's terms and your own compliance requirements.

This is not legal advice — when in doubt, talk to a lawyer.

Option 1: DIY in Python (and why it breaks)

A hand-rolled scraper usually means a headless browser (Playwright or Selenium), because Maps renders results with JavaScript and loads more via infinite scroll:

from playwright.sync_api import sync_playwright

with sync_playwright() as p:
    browser = p.chromium.launch()
    page = browser.new_page()
    page.goto("https://www.google.com/maps/search/coffee+shops+in+Austin")
    # scroll the results panel repeatedly, then parse each card's DOM...

It works in a demo and then fights you in production:

• Infinite scroll — you have to script the results panel scrolling until no new cards load.
• Layout churn — Google changes the DOM and your selectors silently break.
• Anti-bot — CAPTCHAs and IP bans push you into proxy rotation and fingerprinting.
• Scale — one browser per query is slow, so you end up running and monitoring a browser cluster.

Most of the cost is not the first scrape — it is keeping it alive.

Option 2: Ready-made scraper tools

No-code extractors and marketplace actors handle the browser for you and export CSV or JSON. They are great for one-off lists, but less convenient when you need Maps data inside a product or pipeline, on a schedule, with predictable fields.

Option 3: A structured Google Maps API

For repeatable, in-product workflows, a Google Maps scraping API gives you a documented endpoint that returns normalized JSON — no browser, no selectors, no proxy pool to run. Search by query and location:

curl -X POST https://api.crawlora.net/api/v1/google/map/search \
  -H "x-api-key: $CRAWLORA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"query": "coffee shops in Austin, TX", "limit": 20}'

The same call in Python:

import requests

resp = requests.post(
    "https://api.crawlora.net/api/v1/google/map/search",
    headers={"x-api-key": "YOUR_API_KEY"},
    json={"query": "coffee shops in Austin, TX", "limit": 20},
)
for place in resp.json()["data"]:
    print(place["name"], place.get("rating"), place.get("address"))

A response is normalized JSON you can store directly (fields shown are illustrative — check the docs for the current schema):

{
  "code": 200,
  "msg": "OK",
  "data": [
    {
      "name": "Example Coffee",
      "place_id": "ChIJ...",
      "category": ["coffee_shop"],
      "address": "123 Example St, Austin, TX",
      "phone": "+1 512-555-0100",
      "website": "https://example.com",
      "rating": 4.6,
      "reviews": 318,
      "latitude": 30.2672,
      "longitude": -97.7431
    }
  ]
}

Need the full profile for a specific place? Enrich it with the place details endpoint:

curl https://api.crawlora.net/api/v1/google/map/place/CHIJ_PLACE_ID \
  -H "x-api-key: $CRAWLORA_API_KEY"

What you can collect

Where the public profile exposes them, fields typically include business name, category, address, phone, website, opening hours, rating, review count, place ID, and coordinates — plus the query and location context you searched.

Where this gets used

Structured Maps data powers a few common workflows:

• Lead generation — build local business lists and enrich a CRM. See the Google Maps lead generation and lead generation API use cases.
• Local market intelligence — map competitor density, ratings, and website presence by area.
• Local SEO research — track categories and ratings across locations.

FAQ

Can I scrape Google Maps without getting blocked? With a structured API, proxy routing and browser execution are handled behind the endpoint, so you don't manage blocks yourself. With a DIY scraper you need proxies and careful pacing.

What data can I get from Google Maps? Public business fields: name, address, phone, website, hours, rating, review count, place ID, and coordinates, where available.

How often can I refresh the data? As often as your plan and responsible-use constraints allow. Most teams run scheduled snapshots and compare each run against the previous one.

Is this the official Google Places API? No. This extracts public Google Maps data and is independent of Google's official Places API.

Start collecting

Test the search endpoint in the Playground, check the response schema in the API docs, and review credit costs on the pricing page. For the bigger picture, see how to choose a web scraping API and the web scraping API overview.