# Google Maps Scraper (HTTP / curl\_cffi) (`kitcunemia/google-maps-scraper-http`) Actor Lightning-fast HTTP Google Maps scraper for lead generation. No browser = 5–10Γ— cheaper. Returns 30+ fields per place: phone, website, address, owner, ratings, amenities. Quad-tree subdivision unlocks unlimited results per area. Chrome TLS impersonation bypasses Google anti-bot. - **URL**: https://apify.com/kitcunemia/google-maps-scraper-http.md - **Developed by:** [Kitcune Mia](https://apify.com/kitcunemia) (community) - **Categories:** Lead generation, Developer tools, Automation - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $1.60 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## πŸ—ΊοΈ Google Maps Scraper β€” HTTP / curl_cffi > **The fastest, cheapest, most efficient Google Maps scraper on Apify.** > Pure HTTP. No Chromium. No Playwright. No Selenium. Just raw speed and 30+ fields per place. --- ### ⚑ Why this scraper | | This actor | Typical browser-based scrapers | |---|---|---| | **Engine** | curl_cffi with TLS impersonation | Headless Chromium | | **Memory** | ~512 MB is plenty | 2–4 GB minimum | | **Speed** | **51 unique places in 3.7 seconds** (local, no proxy) | 60–120 seconds for the same set | | **Cost on Apify** | Pennies per 1,000 places | 5–10Γ— more compute units | | **Coverage per area** | **Unlimited** via quad-tree subdivision | Capped at Google's ~120 per viewport | | **Fields per place** | **30–40 fields** (full address parts, amenities tree, owner info, hotel data, etc.) | 15–25 typical | | **Anti-bot** | Chrome TLS fingerprint, sticky residential sessions, fresh impersonation per request | Headless flag detection risk | | **Resumability** | Auto-resumes after Apify migrations | Often re-scrapes from scratch | --- ### πŸš€ Top 10 reasons to pick this scraper 1. **πŸ”₯ Blazing fast** β€” runs 5–10Γ— faster than browser-based alternatives because there's no browser to boot, render, or close 2. **πŸ’° Cheapest on Apify** β€” no Chromium = lowest memory footprint = lowest compute-unit cost 3. **🌍 Quad-tree subdivision** β€” breaks Google's hard ~120-results-per-area limit by recursively splitting saturated viewports into 4 quadrants. Scrape entire cities, not just neighborhoods 4. **πŸ“Š Maximum data per place** β€” 30+ 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, and rich hotel data 5. **πŸ₯· TLS impersonation** β€” 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** β€” 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** β€” re-search the same areas in additional languages to catch translations & regional categories you'd otherwise miss 8. **πŸ” Multi-zoom expansion** β€” search each seed at zoom-N..zoom+N for +30–70% extra unique places 9. **♻️ Resume-ready** β€” auto-checkpoints every 30s + on Apify's `PERSIST_STATE` event. Migrations resume without re-pushing duplicates 10. **πŸ›  Battle-tested error handling** β€” detects consent-page redirects, captcha, 429s, and rotates intelligently. Fast-fails on deterministic 4xx (no retry storms) --- ### πŸ“¦ What you get β€” full output schema Every place returns this rich JSON object (real example from a coffee shop in Manhattan): ```json { "title": "Bird & Branch Coffee Roasters", "subTitle": "Family-run specialty coffee shop", "description": "Signature coffee drinks including burnt marshmallow, turmeric, & nut milks with pastries & toasts.", "categoryName": "Coffee shop", "categories": ["Coffee shop", "Cafe", "Corporate gift supplier", "Dessert shop"], "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", "street": "359 W 45th St", "city": "New York", "postalCode": "10036", "state": "New York", "countryCode": "US", "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/", "websiteDisplay": "birdandbranch.com", "totalScore": 4.6, "openingHoursToday": {"day": "Wednesday", "hours": "7 AM–7:30 PM"}, "currentStatus": "Closed Β· Opens 7 AM", "nextOpensAt": "06:30", "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", "ownerId": "105862650674626077989", "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" } ```` #### Hotel-specific extras When the result is a hotel, you also get: ```json { "hotelStars": "4 stars", "hotelPrice": "BYN 695", "hotelCheckInDate": "2026-04-30", "hotelCheckOutDate": "2026-05-01", "hotelAmenities": ["Free Wi-Fi", "Pool", "Pet-friendly"], "longDescription": "On renowned 42nd Street, this relaxed 44-story hotel is set amid Times Square's bustling theaters, shops and restaurants…" } ``` *** ### 🎯 Use cases | Use case | Why this scraper wins | |---|---| | **Lead generation** | 84%+ phone & website coverage, unclaimed-business detection (`claimThisBusinessUrl`), owner names | | **Competitor monitoring** | Quad-tree scans entire metro areas; structured `addressParts` makes geo-grouping trivial | | **Market analysis** | `additionalInfo` amenities tree + `placeTags` enables segmentation by accessibility, payment options, ownership demographics | | **Hotel/travel platforms** | Hotel-specific block: stars, price, check-in/out dates, amenities, full description | | **SEO/local SEO** | Owner names, claim status, kgmid (Knowledge Graph IDs), canonical URLs | | **POI database building** | placeId + fid + cid + kgmid = stable cross-reference identifiers | *** ### 🏁 Quick start #### Option 1 β€” Apify Console (no code) 1. Click **Try for free** on the actor page 2. Fill in the input form: - **Search terms**: `["coffee", "cafe", "bakery"]` - **Location**: `Brooklyn, New York, USA` - Leave defaults for everything else (they're tuned for max coverage) 3. Click **Start** 4. Watch the dataset populate live in the **Dataset** tab 5. Export as JSON, CSV, Excel, or pull via API #### Option 2 β€” API call ```bash curl -X POST https://api.apify.com/v2/acts/YOUR_USERNAME~google-maps-scraper-http/runs \ -H "Content-Type: application/json" \ -H "Authorization: Bearer YOUR_APIFY_TOKEN" \ -d '{ "searchStringsArray": ["restaurant", "bar", "cafe"], "locationQuery": "SoHo, Manhattan, New York", "maxCrawledPlacesPerSearch": 500, "maxSubdivisionDepth": 4, "concurrency": 8 }' ``` #### Option 3 β€” Python SDK ```python 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 }) for place in client.dataset(run["defaultDatasetId"]).iterate_items(): print(place["title"], place.get("phone"), place.get("website")) ``` *** ### πŸŽ› Input parameters #### What to scrape | Field | Type | Default | Description | |---|---|---|---| | **`searchStringsArray`** | string\[] | `["restaurant"]` | Search terms. Each runs across all viewports & languages. | | **`locationQuery`** | string | `"Times Square, …"` | Free-text location, geocoded via OpenStreetMap. | | **`customGeolocation`** | object | β€” | Optional GeoJSON Polygon/MultiPolygon/Point that overrides `locationQuery`. | | **`startUrls`** | string\[] | β€” | Direct `google.com/maps/place/…` URLs to scrape without going through search. | #### Coverage controls | Field | Type | Default | Description | |---|---|---|---| | **`maxCrawledPlacesPerSearch`** | int | `500` | Hard cap per search term across all viewports. | | **`maxPlacesPerViewport`** | int | `80` | Cap per single viewport (Google maxes at ~120). | | **`enableSubdivision`** | bool | `true` | Quad-tree split when a viewport saturates β€” **leave on**. | | **`maxSubdivisionDepth`** | int | `4` | Max recursive splits. depth=4 β†’ up to 256 viewports per seed. | | **`zoom`** | int | auto | Override the seed viewport's Google Maps zoom level (1–21). | | **`multiZoomDelta`** | int | `0` | Search each seed at zoom-N..zoom+N. delta=1 β†’ +30-70% extra places at 3Γ— cost. | | **`language`** | string | `"en"` | Google UI language (`hl=`). | | **`additionalLanguages`** | string\[] | `[]` | Extra languages to re-search in. Useful for bilingual cities. | #### Performance & proxy | Field | Type | Default | Description | |---|---|---|---| | **`concurrency`** | int | `8` | Parallel viewport searches. Each on its own sticky proxy session. | | **`requestTimeoutSecs`** | int | `15` | Per-HTTP-request timeout. | | **`minRequestIntervalMs`** | int | `0` | Global throttle (ms) between any two requests. Useful without residential proxies. | | **`proxyConfiguration`** | object | Apify residential | Proxy settings. **Residential is strongly recommended.** | *** ### πŸ“ˆ Tips for maximum coverage & speed #### 🎯 Maximum coverage ```json { "searchStringsArray": ["restaurant", "cafe", "bar", "bakery"], "locationQuery": "Manhattan, New York", "maxCrawledPlacesPerSearch": 5000, "maxSubdivisionDepth": 5, "multiZoomDelta": 1, "additionalLanguages": ["es", "zh"], "concurrency": 12 } ``` This will likely return **2,000–5,000 unique restaurants** across Manhattan β€” far beyond Google's per-area limit. #### ⚑ Maximum speed (small areas) ```json { "searchStringsArray": ["coffee"], "locationQuery": "Times Square", "maxCrawledPlacesPerSearch": 50, "enableSubdivision": false, "concurrency": 4 } ``` Returns ~40-50 places in **under 5 seconds**. #### πŸ’Ž Use multiple search terms instead of categories Google's `categoryName` filter is brittle β€” a place tagged only `"Coffee shop"` won't match a `"Cafe"` query. Pass several related terms instead: ```json "searchStringsArray": ["coffee", "cafe", "espresso bar", "coffee roaster"] ``` The actor automatically deduplicates by `placeId` so overlapping results are free. #### 🏘 Scrape multiple non-contiguous areas Use `customGeolocation` with a `MultiPolygon` to scrape, e.g., all five NYC boroughs in one run: ```json { "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]]] ] } ``` *** ### πŸ“€ Output Results stream into the actor's **default dataset** as you scrape β€” no waiting until the end. Three pre-built dataset views are available: - **Overview** β€” title, category, address, contacts, rating - **Lead generation** β€” for sales: phone, website, owner, claim status - **Hotels** β€” stars, price, check-in/out, amenities Export formats supported by Apify: - πŸ“„ JSON / JSON Lines - πŸ“Š CSV / Excel - 🌐 HTML / RSS - πŸ“‘ API (paginated) *** ### ❓ FAQ **Q: How does this compare to the official Google Places API?** A: 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. **Q: Will I get blocked?** A: Not if you use Apify residential proxies (the default). The actor uses chrome TLS impersonation (rotated per request), sticky sessions per viewport, and intelligent backoff. We tested 1000+ requests with zero captcha hits. **Q: How many places can I get per area?** A: With `enableSubdivision=true` and `maxSubdivisionDepth=4`, you can scrape thousands of places per city. Google's hard limit is ~120 per single viewport β€” quad-tree subdivision recursively splits saturated areas to break it. **Q: Does this extract reviews?** A: **No.** Google's `/maps/preview/review/listentitiesreviews` endpoint requires browser-bound session tokens that JavaScript constructs from in-memory state β€” impossible to obtain from HTTP-only requests. If you need reviews, use a browser-based scraper (which costs 5–10Γ— more compute). For the same reason, full week opening hours, popular times, and photo lists aren't extractable HTTP-only. Everything else IS. **Q: Which fields are 100% reliable?** A: title, categories, full structured address (street/city/state/postal/country), coordinates, placeId, fid, cid, kgmid, totalScore (rating), URL, timezone, ownerName, imagesCount. Phone & website are present on 84%+ of places (only places without listed contacts are missing them). **Q: Can I resume an interrupted run?** A: Yes β€” state is checkpointed every 30 seconds and on Apify's `PERSIST_STATE` event. Migrated runs auto-resume without re-pushing duplicates. **Q: Multi-language passes β€” when should I use them?** A: When scraping non-English areas (e.g. Tokyo, Mexico City, Berlin) β€” Google returns slightly different category names and translations per `hl` setting. Each language costs 1Γ— the search budget but typically catches 5–15% more unique places. *** ### πŸ”§ Honest limitations We believe in being upfront. Here's what this scraper **does not** extract: | Field | Why not | |---|---| | Review text & individual reviews | Endpoint requires browser-bound session tokens | | 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 it from the search XHR for restaurants/retail/etc. | If any of the above are critical for your use case, you'll need a browser-based scraper (which will be **5–10Γ— slower and more expensive**). For the 95% of users who just need leads, addresses, contacts, ratings, and place identifiers β€” **this scraper is the optimal choice**. *** ### πŸ›  Tech stack - **`curl_cffi`** β€” TLS-impersonation HTTP client (Chrome fingerprint rotation) - **`apify` SDK** β‰₯ 3.3.0 β€” Actor runtime, dataset, KV store, proxy - **`crawlee`** β‰₯ 1.5.0 β€” Used as a browserforge bug workaround dependency - **Python 3.12** β€” Slim Apify base image, no system Chromium installed No Node.js. No browser. No headless detection risk. Just Python + curl. *** ### πŸ“œ License & feedback Built by independent developers. Open to feature requests on the actor's **Issues** tab. If this scraper saves you compute units, leave a ⭐️ review on the Apify Store! # Actor input Schema ## `searchStringsArray` (type: `array`): Search queries to scrape, e.g. \['restaurant', 'cafe', 'pub']. Each term searches independently across all seed viewports and languages. ## `locationQuery` (type: `string`): Free-text location, e.g. 'New York, USA' or 'Manhattan'. Resolved via OpenStreetMap Nominatim. Ignored if customGeolocation is set. ## `customGeolocation` (type: `object`): GeoJSON Polygon, MultiPolygon, or Point. Overrides locationQuery. Point requires 'radiusKm'. MultiPolygon yields one seed per polygon. ## `startUrls` (type: `array`): Direct google.com/maps/place/... URLs. Scraped without going through search. ## `maxCrawledPlacesPerSearch` (type: `integer`): Hard cap per term across all viewports & languages. Quad-tree subdivision stops when this is hit. Default 500 β€” increase for dense city-scale scraping. ## `maxPlacesPerViewport` (type: `integer`): Per-viewport cap. Google itself returns ≀120 per viewport scroll; values above 120 have no effect for one viewport. ## `enableSubdivision` (type: `boolean`): When a viewport saturates (β‰₯18 new of 20 first-page results), split into 4 quadrants and recurse. This is what unlocks scraping >120 results per area. Leave on. ## `maxSubdivisionDepth` (type: `integer`): Max recursive splits. Each level multiplies viewports by 4 (depth=4 β†’ up to 256 viewports per seed). ## `language` (type: `string`): Google UI language (hl=). Affects place names, opening-hours strings, tag labels, etc. ## `additionalLanguages` (type: `array`): Extra language codes to re-search the same areas. Useful for non-English regions where Google returns different translations & categories per language. Each language adds ~Nx searches. ## `zoom` (type: `integer`): Override auto-derived zoom of the seed viewport. Higher zoom = denser results before subdivision. ## `multiZoomDelta` (type: `integer`): Search each seed at zoom-N..zoom+N to maximize coverage. delta=1 β†’ 3 zoom levels per seed (3x cost, +30-70% unique places). delta=0 disables. ## `concurrency` (type: `integer`): How many viewports run in parallel. Each on its own sticky proxy session. Tune up for speed, down if rate-limited. ## `requestTimeoutSecs` (type: `integer`): Per-HTTP-request timeout in seconds. Increase if your residential proxies are slow. ## `minRequestIntervalMs` (type: `integer`): Global throttle: minimum gap between any two outbound requests. 0 = disabled. ## `proxyConfiguration` (type: `object`): Apify proxy settings. Residential proxies are strongly recommended. ## Actor input object example ```json { "searchStringsArray": [ "restaurant" ], "locationQuery": "Times Square, Manhattan, New York", "maxCrawledPlacesPerSearch": 500, "maxPlacesPerViewport": 80, "enableSubdivision": true, "maxSubdivisionDepth": 4, "language": "en", "additionalLanguages": [], "multiZoomDelta": 0, "concurrency": 8, "requestTimeoutSecs": 15, "minRequestIntervalMs": 0, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchStringsArray": [ "restaurant" ], "locationQuery": "Times Square, Manhattan, New York", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("kitcunemia/google-maps-scraper-http").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchStringsArray": ["restaurant"], "locationQuery": "Times Square, Manhattan, New York", "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("kitcunemia/google-maps-scraper-http").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchStringsArray": [ "restaurant" ], "locationQuery": "Times Square, Manhattan, New York", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call kitcunemia/google-maps-scraper-http --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kitcunemia/google-maps-scraper-http", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Maps Scraper (HTTP / curl_cffi)", "description": "Lightning-fast HTTP Google Maps scraper for lead generation. No browser = 5–10Γ— cheaper. Returns 30+ fields per place: phone, website, address, owner, ratings, amenities. Quad-tree subdivision unlocks unlimited results per area. Chrome TLS impersonation bypasses Google anti-bot.", "version": "0.5", "x-build-id": "voAxb6nXiahe1pffy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kitcunemia~google-maps-scraper-http/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kitcunemia-google-maps-scraper-http", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kitcunemia~google-maps-scraper-http/runs": { "post": { "operationId": "runs-sync-kitcunemia-google-maps-scraper-http", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kitcunemia~google-maps-scraper-http/run-sync": { "post": { "operationId": "run-sync-kitcunemia-google-maps-scraper-http", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "searchStringsArray": { "title": "Search terms", "uniqueItems": true, "type": "array", "description": "Search queries to scrape, e.g. ['restaurant', 'cafe', 'pub']. Each term searches independently across all seed viewports and languages.", "items": { "type": "string" } }, "locationQuery": { "title": "Location", "type": "string", "description": "Free-text location, e.g. 'New York, USA' or 'Manhattan'. Resolved via OpenStreetMap Nominatim. Ignored if customGeolocation is set." }, "customGeolocation": { "title": "Custom geolocation (GeoJSON)", "type": "object", "description": "GeoJSON Polygon, MultiPolygon, or Point. Overrides locationQuery. Point requires 'radiusKm'. MultiPolygon yields one seed per polygon." }, "startUrls": { "title": "Direct Google Maps URLs", "type": "array", "description": "Direct google.com/maps/place/... URLs. Scraped without going through search.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxCrawledPlacesPerSearch": { "title": "Max places per search term", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Hard cap per term across all viewports & languages. Quad-tree subdivision stops when this is hit. Default 500 β€” increase for dense city-scale scraping.", "default": 500 }, "maxPlacesPerViewport": { "title": "Max places per viewport", "minimum": 1, "maximum": 120, "type": "integer", "description": "Per-viewport cap. Google itself returns ≀120 per viewport scroll; values above 120 have no effect for one viewport.", "default": 80 }, "enableSubdivision": { "title": "Quad-tree subdivision", "type": "boolean", "description": "When a viewport saturates (β‰₯18 new of 20 first-page results), split into 4 quadrants and recurse. This is what unlocks scraping >120 results per area. Leave on.", "default": true }, "maxSubdivisionDepth": { "title": "Max subdivision depth", "minimum": 0, "maximum": 7, "type": "integer", "description": "Max recursive splits. Each level multiplies viewports by 4 (depth=4 β†’ up to 256 viewports per seed).", "default": 4 }, "language": { "title": "Primary language", "type": "string", "description": "Google UI language (hl=). Affects place names, opening-hours strings, tag labels, etc.", "default": "en" }, "additionalLanguages": { "title": "Additional languages", "uniqueItems": true, "type": "array", "description": "Extra language codes to re-search the same areas. Useful for non-English regions where Google returns different translations & categories per language. Each language adds ~Nx searches.", "default": [], "items": { "type": "string" } }, "zoom": { "title": "Initial zoom", "minimum": 1, "maximum": 21, "type": "integer", "description": "Override auto-derived zoom of the seed viewport. Higher zoom = denser results before subdivision." }, "multiZoomDelta": { "title": "Multi-zoom expansion (Β±N)", "minimum": 0, "maximum": 3, "type": "integer", "description": "Search each seed at zoom-N..zoom+N to maximize coverage. delta=1 β†’ 3 zoom levels per seed (3x cost, +30-70% unique places). delta=0 disables.", "default": 0 }, "concurrency": { "title": "Concurrent tasks", "minimum": 1, "maximum": 30, "type": "integer", "description": "How many viewports run in parallel. Each on its own sticky proxy session. Tune up for speed, down if rate-limited.", "default": 8 }, "requestTimeoutSecs": { "title": "Per-request HTTP timeout (s)", "minimum": 5, "maximum": 60, "type": "integer", "description": "Per-HTTP-request timeout in seconds. Increase if your residential proxies are slow.", "default": 15 }, "minRequestIntervalMs": { "title": "Min interval between requests (ms)", "minimum": 0, "maximum": 5000, "type": "integer", "description": "Global throttle: minimum gap between any two outbound requests. 0 = disabled.", "default": 0 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Apify proxy settings. Residential proxies are strongly recommended.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```