# HappyCow Vegan Restaurant Scraper (`lulzasaur/happycow-scraper`) Actor Scrape vegan and vegetarian restaurants from HappyCow. Get ratings, reviews, addresses, cuisine types, price ranges, and location data. Search by city or location worldwide. - **URL**: https://apify.com/lulzasaur/happycow-scraper.md - **Developed by:** [lulz bot](https://apify.com/lulzasaur) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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 ## HappyCow Vegan Restaurant Scraper Scrape vegan and vegetarian restaurants from [HappyCow](https://www.happycow.net), the world's largest vegan/vegetarian restaurant finder. Get ratings, reviews, addresses, cuisine types, price ranges, and location data for restaurants worldwide. ### Features - **Search by location** — Enter any city name or location (e.g., "New York", "London", "Tokyo") - **Restaurant types** — Identifies vegan, vegetarian, and veg-friendly restaurants - **Ratings and reviews** — Star ratings, review counts, and full review text (with detail scraping) - **Location data** — Addresses, cities, countries, postal codes, and precise lat/lng coordinates - **Contact info** — Phone numbers and website URLs (with detail scraping) - **Price ranges** — Budget indicators from $ to $$$$ - **Pagination** — Automatically pages through all results up to your limit ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | `searchQueries` | string[] | City names or locations to search | `["San Francisco"]` | | `maxListings` | integer | Max restaurants per search location | `100` | | `scrapeDetails` | boolean | Visit individual pages for full reviews, phone, website, coordinates | `false` | | `proxyConfiguration` | object | Proxy settings | Apify Residential | #### Example Input ```json { "searchQueries": ["New York", "Los Angeles", "London"], "maxListings": 50, "scrapeDetails": true } ```` ### Output Each result contains: | Field | Description | |-------|-------------| | `name` | Restaurant name | | `type` | `vegan`, `vegetarian`, or `veg-friendly` | | `venueCategory` | Restaurant, Food Truck, Bakery, Juice Bar, etc. | | `address` | Street address | | `city` | City name | | `country` | Country name | | `postalCode` | Postal/ZIP code | | `latitude` | GPS latitude (detail mode only) | | `longitude` | GPS longitude (detail mode only) | | `rating` | Star rating (0-5) | | `ratingCount` | Number of reviews | | `reviews` | Array of review objects with author, rating, text (detail mode only) | | `description` | Restaurant description (detail mode only) | | `website` | Restaurant website URL (detail mode only) | | `phone` | Phone number (detail mode only) | | `priceRange` | Price indicator ($, $$, $$$, or descriptive like "Moderate") | | `imageUrl` | Restaurant photo URL | | `url` | HappyCow listing URL | | `searchQuery` | The search query that found this result | | `scrapedAt` | ISO timestamp | #### Example Output ```json { "venueId": "133328", "name": "Next Level Burger - Potrero Hill", "type": "vegan", "venueCategory": "Restaurant", "address": "450 Rhode Island St", "city": "San Francisco", "country": "USA", "postalCode": "94107", "latitude": 37.7642, "longitude": -122.4028, "rating": 4.5, "ratingCount": 106, "priceRange": "$$", "imageUrl": "https://images.happycow.net/venues/500/13/33/hcmp133328_2231265.jpeg", "url": "https://www.happycow.net/reviews/next-level-burger-san-francisco-133328", "searchQuery": "San Francisco", "scrapedAt": "2026-04-26T07:00:00.000Z" } ``` ### Modes #### Quick mode (default) Set `scrapeDetails: false` for fast scraping. Gets name, type, rating, review count, address, price range, and image from search results. Does not include phone, website, coordinates, description, or individual reviews. #### Detail mode Set `scrapeDetails: true` to visit each restaurant's individual page. This adds phone numbers, website URLs, precise GPS coordinates, full descriptions, price range text, and individual review text with author names and ratings. Slower but provides complete data. ### Cost - **Quick mode**: ~$0.25 per 1,000 restaurants (very fast, minimal requests) - **Detail mode**: ~$2.50 per 1,000 restaurants (one additional request per restaurant) ### Tips - Start with a small `maxListings` (10-20) to test your query - Use detail mode only when you need phone/website/coordinates/reviews - Each location searches a 15-mile radius by default - The scraper automatically handles pagination across multiple result pages # Actor input Schema ## `searchQueries` (type: `array`): City names or locations to search (e.g. 'New York', 'London', 'Tokyo'). Each query searches a 15-mile radius. ## `maxListings` (type: `integer`): Maximum number of restaurants to scrape per search location. ## `scrapeDetails` (type: `boolean`): Visit individual restaurant pages for full reviews, phone numbers, website URLs, and precise coordinates. Slower but more data. ## `proxyConfiguration` (type: `object`): Select proxies to be used by your scraper. ## Actor input object example ```json { "searchQueries": [ "San Francisco" ], "maxListings": 100, "scrapeDetails": false, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQueries": [ "San Francisco" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("lulzasaur/happycow-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → 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 = { "searchQueries": ["San Francisco"], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("lulzasaur/happycow-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchQueries": [ "San Francisco" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call lulzasaur/happycow-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lulzasaur/happycow-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "HappyCow Vegan Restaurant Scraper", "description": "Scrape vegan and vegetarian restaurants from HappyCow. Get ratings, reviews, addresses, cuisine types, price ranges, and location data. Search by city or location worldwide.", "version": "1.0", "x-build-id": "mdBbMizfqXBsSPzPA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lulzasaur~happycow-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lulzasaur-happycow-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lulzasaur~happycow-scraper/runs": { "post": { "operationId": "runs-sync-lulzasaur-happycow-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lulzasaur~happycow-scraper/run-sync": { "post": { "operationId": "run-sync-lulzasaur-happycow-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "searchQueries" ], "properties": { "searchQueries": { "title": "Search locations", "type": "array", "description": "City names or locations to search (e.g. 'New York', 'London', 'Tokyo'). Each query searches a 15-mile radius.", "default": [ "San Francisco" ], "items": { "type": "string" } }, "maxListings": { "title": "Max listings per query", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of restaurants to scrape per search location.", "default": 100 }, "scrapeDetails": { "title": "Scrape full details", "type": "boolean", "description": "Visit individual restaurant pages for full reviews, phone numbers, website URLs, and precise coordinates. Slower but more data.", "default": false }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Select proxies to be used by your scraper." } } }, "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 } } } } } } } } } } ```