# Gurunavi Scraper - Japanese Restaurant Reviews & Listings (`huggable_quote/gurunavi-scraper`) Actor Scrape restaurant data from Rakuten Gurunavi, Japan's top dining guide. Extract menus, prices, reviews, ratings, hours, and location info. Ideal for Japanese F\&B market research and competitor analysis. - **URL**: https://apify.com/huggable\_quote/gurunavi-scraper.md - **Developed by:** [OrbitData Labs](https://apify.com/huggable_quote) (community) - **Categories:** Lead generation, Other - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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 ## Gurunavi Scraper Scrape restaurant data from Rakuten Gurunavi (楽天ぐるなび), Japan's leading dining guide. ### Features - Extract restaurant info: name, address, phone, hours, budget, seats, coordinates - Extract menu items and course menus with prices - Extract customer reviews when available - Search by area + cuisine, search URLs, or direct restaurant URLs - CAPTCHA detection with automatic proxy rotation - Polite crawling with 3-7 second delays # Actor input Schema ## `searchUrls` (type: `array`): Gurunavi search result page URLs. Example: 'https://r.gnavi.co.jp/area/aream2115/izakaya/' (Shibuya izakaya) ## `restaurantUrls` (type: `array`): Direct Gurunavi restaurant page URLs. Example: 'https://r.gnavi.co.jp/pvh7jmg40000/' ## `searchArea` (type: `string`): Area name in Japanese or English. Example: '渋谷' or 'Shibuya' ## `searchCategory` (type: `string`): Cuisine type. Example: '焼肉', '居酒屋', 'イタリアン', 'ramen' ## `maxRestaurants` (type: `integer`): Maximum number of restaurants to extract. 0 = all results. ## `includeMenuDetails` (type: `boolean`): Extract individual menu items and course menu details (increases scraping time) ## `includeReviews` (type: `boolean`): Extract customer reviews if available ## `maxReviewsPerRestaurant` (type: `integer`): Maximum reviews to extract per restaurant. 0 = all. ## `language` (type: `string`): Primary language for data extraction ## `proxyConfiguration` (type: `object`): Proxy settings. Recommended for scraping 50+ restaurants. ## Actor input object example ```json { "searchUrls": [], "restaurantUrls": [ "https://r.gnavi.co.jp/pvh7jmg40000/" ], "searchArea": "", "searchCategory": "", "maxRestaurants": 50, "includeMenuDetails": true, "includeReviews": true, "maxReviewsPerRestaurant": 20, "language": "ja", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ```` # Actor output Schema ## `defaultDataset` (type: `string`): No description # 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 = { "searchUrls": [], "restaurantUrls": [ "https://r.gnavi.co.jp/pvh7jmg40000/" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("huggable_quote/gurunavi-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 = { "searchUrls": [], "restaurantUrls": ["https://r.gnavi.co.jp/pvh7jmg40000/"], "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("huggable_quote/gurunavi-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 '{ "searchUrls": [], "restaurantUrls": [ "https://r.gnavi.co.jp/pvh7jmg40000/" ], "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call huggable_quote/gurunavi-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=huggable_quote/gurunavi-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gurunavi Scraper - Japanese Restaurant Reviews & Listings", "description": "Scrape restaurant data from Rakuten Gurunavi, Japan's top dining guide. Extract menus, prices, reviews, ratings, hours, and location info. Ideal for Japanese F&B market research and competitor analysis.", "version": "1.0", "x-build-id": "vWDsXzEhHwqaMZicq" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/huggable_quote~gurunavi-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-huggable_quote-gurunavi-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/huggable_quote~gurunavi-scraper/runs": { "post": { "operationId": "runs-sync-huggable_quote-gurunavi-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/huggable_quote~gurunavi-scraper/run-sync": { "post": { "operationId": "run-sync-huggable_quote-gurunavi-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchUrls": { "title": "Search URLs", "type": "array", "description": "Gurunavi search result page URLs. Example: 'https://r.gnavi.co.jp/area/aream2115/izakaya/' (Shibuya izakaya)", "items": { "type": "string" } }, "restaurantUrls": { "title": "Restaurant URLs", "type": "array", "description": "Direct Gurunavi restaurant page URLs. Example: 'https://r.gnavi.co.jp/pvh7jmg40000/'", "items": { "type": "string" } }, "searchArea": { "title": "Search area", "type": "string", "description": "Area name in Japanese or English. Example: '渋谷' or 'Shibuya'", "default": "" }, "searchCategory": { "title": "Cuisine category", "type": "string", "description": "Cuisine type. Example: '焼肉', '居酒屋', 'イタリアン', 'ramen'", "default": "" }, "maxRestaurants": { "title": "Max restaurants", "minimum": 0, "maximum": 1000, "type": "integer", "description": "Maximum number of restaurants to extract. 0 = all results.", "default": 50 }, "includeMenuDetails": { "title": "Include menu details", "type": "boolean", "description": "Extract individual menu items and course menu details (increases scraping time)", "default": true }, "includeReviews": { "title": "Include reviews", "type": "boolean", "description": "Extract customer reviews if available", "default": true }, "maxReviewsPerRestaurant": { "title": "Max reviews per restaurant", "minimum": 0, "maximum": 500, "type": "integer", "description": "Maximum reviews to extract per restaurant. 0 = all.", "default": 20 }, "language": { "title": "Output language preference", "enum": [ "ja", "en" ], "type": "string", "description": "Primary language for data extraction", "default": "ja" }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings. Recommended for scraping 50+ restaurants." } } }, "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 } } } } } } } } } } ```