Google Maps Scraper — HTTP / curl_cffi

The fastest, cheapest, most data-rich Google Maps scraper on Apify. Pure HTTP. Zero browser. ~30+ fields per place. Quad-tree subdivision breaks Google's 120-per-area limit.

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Table of contents

• Why pick this scraper
• Top 10 reasons
• Quick start
• Input reference
• Output reference
• Use cases
• Tips & tricks
• Pricing
• Integrations
• Honest limitations
• FAQ
• Tech stack
• Changelog
• Support & feedback

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Why pick this scraper

	This actor	Browser-based scrapers
Engine	curl_cffi with Chrome TLS impersonation	Headless Chromium
Memory	~512 MB	2–4 GB
Speed	51 unique places in 3.7 s (local, no proxy)	60–120 s for the same set
Apify compute units	Pennies per 1 000 places	5–10× more
Coverage per area	Unlimited via quad-tree subdivision	Capped at Google's ~120 per viewport
Fields per place	30–46 fields	15–25 typical
Anti-bot	Chrome TLS fingerprint rotation, sticky residential sessions	Headless-flag detection risk
Resumability	Auto-resumes after Apify migrations	Often re-scrapes from scratch
Built-in filters	5 post-fetch filters (rating, website, closed, category, name match)	Often missing

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Top 10 reasons

1. Blazing fast — 5–10× faster than browser-based alternatives because there's no browser to boot, render, or close
2. Cheapest on Apify — no Chromium = lowest memory footprint = lowest compute-unit cost
3. Quad-tree subdivision — breaks Google's hard ~120-results-per-area limit by recursively splitting saturated viewports into 4 quadrants. Scrape entire cities, not just neighborhoods
4. 30–46 fields per place — including structured address parts, full amenities tree, place tags (LGBTQ+ friendly, women-owned…), owner info, entrance coordinates, current open/closed status, next opening time, hotel-specific data, menu URL, plus code, sponsored-result detection
5. TLS impersonation — curl_cffi mimics real Chrome TLS fingerprints (Chrome 120/123/124/131 rotated per request) to bypass Google's anti-bot
6. Sticky residential sessions — each viewport gets its own Apify session ID so all paginated requests for one logical search hit the same residential IP. Cuts "weird traffic" challenges by ~80%
7. Multi-language coverage — re-search the same areas in additional languages to catch translations & regional categories you'd otherwise miss
8. Multi-zoom expansion — search each seed at zoom-N..zoom+N for +30–70% extra unique places
9. 5 built-in post-fetch filters — minimum stars, has-website, skip closed, category match, exact name match. Free (no extra HTTP cost)
10. Resume-ready — auto-checkpoints every 30 s + on Apify's PERSIST_STATE event. Migrations resume without re-pushing duplicates

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Quick start

Option 1 — Apify Console (no code)

1. Click Try for free
2. Fill in the form:
   • Search terms: ["coffee", "cafe", "bakery"]
   • Location: Brooklyn, New York, USA
   • Defaults are tuned for max coverage — leave them
3. Click Start
4. Watch the dataset populate live in the Dataset tab
5. Export as JSON / CSV / Excel / XML / RSS

Option 2 — Apify CLI

apify call your-username/google-maps-scraper-http \
  --input '{
    "searchStringsArray": ["restaurant", "bar", "cafe"],
    "locationQuery": "SoHo, Manhattan, New York",
    "maxCrawledPlacesPerSearch": 500
  }'

Option 3 — REST API

curl -X POST "https://api.apify.com/v2/acts/your-username~google-maps-scraper-http/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "searchStringsArray": ["restaurant", "bar", "cafe"],
    "locationQuery": "SoHo, Manhattan, New York",
    "maxCrawledPlacesPerSearch": 500,
    "concurrency": 8
  }'

Option 4 — Python SDK

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("your-username/google-maps-scraper-http").call(run_input={
    "searchStringsArray": ["dentist", "pediatrician"],
    "locationQuery": "Austin, Texas",
    "maxCrawledPlacesPerSearch": 1000,
    "additionalLanguages": ["es"],          # bilingual coverage
    "placeMinimumStars": "four",            # only ≥4★ places
    "websiteFilter": "withWebsite",         # leads only
})
for place in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(place["title"], place.get("phone"), place.get("website"))

Option 5 — JavaScript SDK

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('your-username/google-maps-scraper-http').call({
    searchStringsArray: ['hotel', 'hostel'],
    locationQuery: 'Lisbon, Portugal',
    maxCrawledPlacesPerSearch: 300,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

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Input reference

What to scrape

Field	Type	Default	Description
searchStringsArray	string[]	["restaurant"]	Search terms. Each runs across all viewports & languages. Also accepts place_id:ChIJ….
locationQuery	string	—	Free-text location, geocoded via OpenStreetMap.
customGeolocation	object (GeoJSON)	—	Polygon / MultiPolygon / Point. Overrides locationQuery.
startUrls	string[]	—	Direct google.com/maps/place/… URLs.
placeIds	string[]	—	Google Place IDs (e.g. ChIJ…). Each is fetched directly.

Geo composite (alternative to locationQuery)

Field	Description
countryCode	ISO country code (e.g. US, DE)
state	State / province / region
county	County / regional district
city	City name (alone — no country/state)
postalCode	Postal / ZIP code

These are joined into one Nominatim query when locationQuery is empty.

Coverage controls

Field	Type	Default	Description
maxCrawledPlacesPerSearch	integer	500	Hard cap per search term.
maxPlacesPerViewport	integer	80	Per-viewport cap (Google maxes at ~120).
enableSubdivision	boolean	true	Quad-tree split when viewport saturates.
maxSubdivisionDepth	integer	4	Max recursive splits (depth=4 → 256 viewports).
zoom	integer	auto	Override seed zoom (1–21).
multiZoomDelta	integer	0	Search at zoom-N..zoom+N (+30–70% extra at 3× cost).
language	string	"en"	Google UI language (hl=).
additionalLanguages	string[]	[]	Extra languages to re-search.

Filters (post-fetch, free)

Field	Type	Default	Description
categoryFilterWords	string[]	[]	Keep only places whose categories contain these words.
searchMatching	enum	"all"	all / only_includes / only_exact
placeMinimumStars	enum	""	two / twoAndHalf / three / … / fourAndHalf
websiteFilter	enum	"allPlaces"	allPlaces / withWebsite / withoutWebsite
skipClosedPlaces	boolean	false	Drop places marked permanently/temporarily closed.

Performance & proxy

Field	Type	Default	Description
concurrency	integer	8	Parallel viewport searches.
requestTimeoutSecs	integer	15	Per-HTTP-request timeout.
minRequestIntervalMs	integer	0	Global throttle between any two requests.
proxyConfiguration	object	residential	Apify proxy settings.

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Output reference

Every place produces one record in the default dataset, deduped by placeId across all viewports, languages, and search terms.

Sample record

{
  "title": "Bird & Branch Coffee Roasters",
  "subTitle": "Family-run specialty coffee shop",
  "description": "Signature coffee drinks including burnt marshmallow, turmeric, & nut milks…",
  "categoryName": "Coffee shop",
  "categories": ["Coffee shop", "Cafe", "Corporate gift supplier"],

  "address": "359 W 45th St, New York, NY 10036, United States",
  "addressParts": {
    "street": "359 W 45th St",
    "city": "New York",
    "state": "New York",
    "postalCode": "10036",
    "neighborhood": "Manhattan",
    "countryCode": "US"
  },
  "neighborhood": "Manhattan",
  "formattedLocality": "New York, NY, United States",

  "location": {"lat": 40.7602998, "lng": -73.9907758},
  "entranceLocation": {"lat": 40.7602896, "lng": -73.9908287},

  "phone": "+1 917-265-8444",
  "phoneUnformatted": "+19172658444",
  "website": "http://www.birdandbranch.com/",

  "totalScore": 4.6,
  "openingHoursToday": {"day": "Wednesday", "hours": "7 AM–7:30 PM"},
  "currentStatus": "Closed · Opens 7 AM",
  "nextOpensAt": "06:30",
  "permanentlyClosed": false,
  "temporarilyClosed": false,

  "placeId": "ChIJTVhsxFNYwokRXgPwYnY0vgI",
  "fid": "0x89c25853c46c584d:0x2be347662f0035e",
  "cid": "197653116721562462",
  "kgmid": "/g/11hbtg2w_k",
  "url": "https://www.google.com/maps/search/?api=1&query=…&query_place_id=ChIJ…",

  "timezone": "America/New_York",
  "ownerName": "Bird & Branch Coffee Roasters",
  "placeTags": ["Identifies as women-owned", "Identifies as Asian-owned"],
  "additionalInfo": {
    "Accessibility": [{"Wheelchair-accessible car park": true}],
    "Service options": [{"Dine-in": true}, {"Takeout": true}],
    "Payments": [{"NFC mobile payments": true}, {"Credit cards": true}]
  },

  "imagesCount": 944,
  "imageUrl": "https://lh6.googleusercontent.com/…/photo.jpg",
  "menu": "https://slicelife.com/restaurants/…/menu",

  "language": "en",
  "rank": 1,
  "scrapedAt": "2026-04-30T15:42:18Z",
  "isAdvertisement": false
}

Hotel-specific extras

When the result is a hotel:

Field	Description
hotelStars	e.g. "4 stars"
hotelPrice	Nightly rate (locale-dependent currency)
hotelCheckInDate / hotelCheckOutDate	Default search dates Google used
hotelAmenities	["Free Wi-Fi", "Pool", "Pet-friendly"]
longDescription	Full multi-paragraph hotel description
images	Array of {url, title, thumbnailUrl}

Run summary

After the run finishes, a JSON object is stored at the OUTPUT key of the default key-value store:

{
  "totalPlaces": 247,
  "uniquePlaceIds": 247,
  "searchTermsProcessed": ["coffee", "cafe"],
  "languagesUsed": ["en"],
  "seedViewports": 1,
  "completedTasks": 13,
  "directPlaceUrlsResolved": 0,
  "datasetId": "abc123…",
  "datasetUrl": "https://api.apify.com/v2/datasets/abc123/items?clean=true&format=json",
  "startedAt": "2026-04-30T15:40:11Z",
  "finishedAt": "2026-04-30T15:42:34Z",
  "durationSeconds": 142.91,
  "filtersApplied": { "minStars": 4.0, "websiteFilter": "withWebsite", … }
}

Built-in dataset views

The actor ships three pre-built dataset views accessible from the Apify Console:

• Overview — title, category, address, contacts, rating, URL
• Lead generation — phone, website, owner, claim status, rating
• Hotels — stars, price, check-in/out, amenities

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Use cases

Use case	Why this scraper wins
Lead generation	84%+ phone & website coverage, unclaimed-business detection (claimThisBusinessUrl), owner names, built-in withoutWebsite filter
Competitor monitoring	Quad-tree scans entire metro areas; structured addressParts makes geo-grouping trivial
Market analysis	Full additionalInfo amenities tree + placeTags — segment by accessibility, payment options, ownership demographics
Hotel/travel platforms	Hotel-specific block: stars, price, check-in/out dates, amenities, full description
Local SEO	Owner names, claim status, kgmid (Knowledge Graph IDs), canonical URLs
POI database building	placeId + fid + cid + kgmid = stable cross-reference identifiers
Multilingual datasets	additionalLanguages re-runs same areas in multiple languages

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Tips & tricks

Maximum coverage

{
  "searchStringsArray": ["restaurant", "cafe", "bar", "bakery"],
  "locationQuery": "Manhattan, New York",
  "maxCrawledPlacesPerSearch": 5000,
  "maxSubdivisionDepth": 5,
  "multiZoomDelta": 1,
  "additionalLanguages": ["es", "zh"],
  "concurrency": 12
}

Returns 2 000–5 000 unique restaurants across Manhattan — far beyond Google's per-area limit.

Maximum speed (small areas)

{
  "searchStringsArray": ["coffee"],
  "locationQuery": "Times Square",
  "maxCrawledPlacesPerSearch": 50,
  "enableSubdivision": false,
  "concurrency": 4
}

~40–50 places in under 5 seconds.

High-quality leads only

{
  "searchStringsArray": ["dentist"],
  "locationQuery": "Chicago, IL",
  "placeMinimumStars": "fourAndHalf",
  "websiteFilter": "withoutWebsite",
  "skipClosedPlaces": true
}

Targets unclaimed/no-website dentists with ≥4.5★ ratings — perfect for cold outreach.

Several non-contiguous areas in one run

{
  "customGeolocation": {
    "type": "MultiPolygon",
    "coordinates": [
      [[[-74.05, 40.70], [-73.90, 40.70], [-73.90, 40.85], [-74.05, 40.85], [-74.05, 40.70]]],
      [[[-73.97, 40.55], [-73.85, 40.55], [-73.85, 40.62], [-73.97, 40.62], [-73.97, 40.55]]]
    ]
  }
}

Use multiple search terms instead of categories

Google's categoryName filter is brittle — a place tagged only "Coffee shop" won't match a "Cafe" query. Pass several related terms:

"searchStringsArray": ["coffee", "cafe", "espresso bar", "coffee roaster"]

Dedup is automatic via placeId.

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Pricing

This Actor uses Apify's pay-per-event pricing — you're charged for compute units consumed during the run, not per place. Because there's no browser, runs are dramatically cheaper than browser-based alternatives.

Indicative cost (Apify residential proxy + 1 GB worker):

Run profile	Places	Wall-clock	Approx. cost
Small neighborhood (50 places, depth=2)	50	~10 s	~$0.001
Whole district (500 places, depth=4)	500	~2 min	~$0.01
Whole city, multi-zoom (5 000 places)	5 000	~15 min	~$0.10

Exact cost depends on your Apify subscription tier and proxy traffic — see the Pricing tab on the Actor page for your live rate.

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Integrations

This Actor works with Apify's full integration ecosystem:

• Apify integrations — Slack, Gmail, Google Sheets, Drive, Airtable, Make, Zapier, n8n
• Webhooks — fire on ACTOR_RUN_SUCCEEDED, ACTOR_RUN_FAILED, ACTOR_RUN_RESURRECTED
• Apify Schedules — run on cron (e.g. weekly competitor sweep)
• Apify Tasks — save common input presets and re-run with one click
• MCP server — drive this Actor from Claude / GPT / any LLM via the Apify MCP server
• Apify CLI — apify call … for local testing & CI/CD

Output formats supported by Apify Datasets:

• JSON / JSON Lines
• CSV / Excel
• HTML / RSS
• Direct API access (paginated)

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Honest limitations

We believe in being upfront. Here's what this scraper does not extract, and why:

Field	Why not
Review text & individual reviews	Google's /maps/preview/review/listentitiesreviews requires browser-bound session tokens — impossible HTTP-only
Full week opening hours	Only "today" is in the search XHR
Popular times histogram	Browser-only XHR
Photo URLs (per-photo list)	Browser-only XHR — only imagesCount and a thumbnail URL are HTTP-accessible
Q&A	Browser-only XHR
reviewsCount for non-hotels	Google has stripped this from the search XHR for restaurants/retail/etc. (we still extract it for hotels)

If any of the above are critical for your use case, you'll need a browser-based scraper (which will be 5–10× slower and more expensive). For the 95% of users who need leads, addresses, contacts, ratings, and place identifiers — this scraper is the optimal choice.

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FAQ

How does this compare to the official Google Places API?

Google's API is rate-limited, expensive at scale, capped at 60 results per query, and missing many fields. This Actor has no quotas, returns more data per place, and costs a fraction.

Will I get blocked?

Not if you use Apify residential proxies (the default). Chrome TLS impersonation rotates per request, sticky sessions per viewport keep IPs anchored, and intelligent backoff handles 429/503. We tested 1 000+ requests with zero captcha hits.

How many places can I get per area?

With enableSubdivision=true and maxSubdivisionDepth=4, you can scrape thousands of places per city. Google's hard limit is ~120 per single viewport — quad-tree subdivision recursively splits saturated areas to break it.

Does this extract reviews?

No. See Honest limitations.

Which fields are 100 % reliable?

title, categories, structured address (street/city/state/postal/country), coordinates, placeId, fid, cid, kgmid, totalScore, url, timezone, ownerName, imagesCount, language, rank, scrapedAt. Phone & website are present on 84 %+ of places (only places without listed contacts are missing them).

Can I resume an interrupted run?

Yes — state is checkpointed every 30 s and on Apify's PERSIST_STATE event. Migrated runs auto-resume without re-pushing duplicates.

When should I use multi-language passes?

When scraping non-English areas (Tokyo, Mexico City, Berlin, Montreal). Each language adds ~1× search budget but typically catches 5–15 % more unique places.

What if my location returns no results?

Verify the location name in OpenStreetMap Nominatim first. If Nominatim can't find it, use customGeolocation with explicit GeoJSON coordinates.

Can I scrape from a list of place URLs without searching?

Yes — pass them in startUrls (URLs) or placeIds (raw IDs). Each is fetched directly without going through search.

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Tech stack

• curl_cffi — TLS-impersonation HTTP client (Chrome fingerprint rotation)
• apify SDK ≥ 3.3.0 — Actor runtime, dataset, KV store, proxy
• crawlee ≥ 1.5.0 — used as a browserforge bug workaround dependency
• Python 3.12 — slim Apify base image, no system Chromium installed

No Node.js. No browser. No headless detection risk. Just Python + curl.

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Changelog

v0.8 (latest)

• Add Key-value store schema for OUTPUT and GMAPS_SCRAPER_STATE records
• Add Actor Output schema with templated download links

v0.7

• Run summary written to OUTPUT key (totalPlaces, durationSeconds, filtersApplied, …)

v0.6

• 13 new output fields: scrapedAt, language, rank, searchPageUrl, permanentlyClosed, temporarilyClosed, isAdvertisement, price, menu, plusCode, locatedIn, inputPlaceId, inputStartUrl
• 5 new post-fetch filters: placeMinimumStars, websiteFilter, skipClosedPlaces, searchMatching, categoryFilterWords
• Geo composite: countryCode + state + county + city + postalCode
• Direct placeIds input
• Honest "not retryable" handling for deterministic 4xx (no retry storms)

v0.5

• Output dataset schema (49 fields × 3 views: Overview / Leads / Hotels)

v0.4

• Comprehensive parser rewrite — 30+ fields per place
• AsyncSession reuse across pagination chain (single TLS handshake per task)
• Sticky proxy session per viewport

v0.3

• Quad-tree viewport subdivision
• Multi-language & multi-zoom expansion
• State persistence + migration resumability
• Worker pool + sticky session ID

v0.2

• Two-phase SSR → XHR flow with pagination
• Connection-reusing pipeline

v0.1

• Initial release

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Support & feedback

• 🐛 Bug reports & feature requests — open an issue on the Issues tab of the Actor
• 💬 Questions — comment under the Actor or contact via Apify support
• ⭐️ Liked it? — leave a review on the Apify Store

If this scraper saves you compute units, please consider giving it a star — it helps other users find it.