# Tabelog Japan Restaurant Scraper (`parseforge/tabelog-scraper`) Actor Scrape Japan's largest restaurant directory. Returns name, cuisine, price range, address, geo coordinates, phone, rating, review count, image, and JSON-LD structured data per restaurant. Filter by city, area, or cuisine. - **URL**: https://apify.com/parseforge/tabelog-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Travel, Lead generation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 restaurant records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## ๐Ÿฃ Tabelog Japan Restaurant Scraper > ๐Ÿš€ ๐Ÿฃ **Scrape Japan's largest restaurant directory.** Pull **800,000+ Japanese restaurants** worth of data with **14 fields per record**. No API key, no manual data entry. > ๐Ÿ•’ **Last updated:** 2026-05-05 ยท **๐Ÿ“Š 14 fields per record** ยท **๐ŸŒ Japan** ยท **๐Ÿ’ต from $0.008 per item (FREE tier)** The **Tabelog Japan Restaurant Scraper** Scrape restaurant records from Tabelog, Japan's largest restaurant directory. Returns name, cuisine, price range, geo coordinates, address, phone, rating, review count, and a representative image per restaurant. Filter by city and area code to scope your run. | ๐ŸŽฏ Target Audience | ๐Ÿ’ก Primary Use Cases | |---|---| | Sales teams, compliance officers, researchers, journalists, real-estate analysts, healthcare ops | Restaurant tech & POS, Travel-tech curation, F&B market intelligence, Localization & directory enrichment | --- ### ๐Ÿ“‹ What the Tabelog Japan Restaurant Scraper does Highlights of every record returned: - ๐Ÿฎ **Restaurant identity.** name, cuisine, image, official Tabelog URL. - ๐Ÿ’ด **Pricing & rating.** price range, average rating, review count. - ๐Ÿ“ **Location.** full address, city, region, postal code, lat/lng. - ๐Ÿ“ž **Contact.** telephone. - ๐ŸŒ **City + area scoping.** 12 supported cities + optional area-code filter (e.g., A1311 for Ueno in Tokyo). > ๐Ÿ’ก **Why it matters:** verified, structured data delivered in seconds beats hand-curated spreadsheets that go stale within days. Run this Actor on a schedule and your downstream pipeline always has fresh records. --- ### ๐ŸŽฌ Full Demo _๐Ÿšง Coming soon: a 3-minute walkthrough showing how to go from sign-up to a downloaded Tabelog Japan Restaurant Scraper dataset._ --- ### โš™๏ธ Input
InputTypeDefaultBehavior
citystring"tokyo"Tabelog city slug. 12 supported.
areaCodestring""Optional area filter (e.g., `A1311`). Empty = entire city.
maxItemsinteger10Records to return. Free: max 10. Paid: up to 1,000,000.
**Example input:** ```json { "city": "tokyo", "areaCode": "A1311", "maxItems": 100 } ```` *** ### ๐Ÿ“Š Output Each record contains **14 fields**. Download the dataset as CSV, Excel, JSON, or XML. #### ๐Ÿงพ Top fields - `name` - `url` - `imageUrl` - `cuisine` - `priceRange` - `rating` - `reviewCount` - `phone` - `addressFull` - `city` - `lat` - `lng` *** ### โœจ Why choose this Actor - ๐Ÿ› ๏ธ **No infrastructure** to maintain. The Apify cloud handles scheduling, retries, proxies, and storage. - ๐ŸŒ **Verified source data.** Records come from authoritative public sources, not third-party aggregators. - ๐Ÿ” **Repeatable runs.** Schedule monthly, weekly, or hourly to keep your pipeline always fresh. - ๐Ÿ“Š **Multiple export formats.** CSV, Excel, JSON, XML out of the box. - ๐Ÿ’ต **Pay only for what you use.** Pay-per-result-item pricing, free preview included. *** ### ๐Ÿ’ผ Business use cases #### ๐Ÿง‘โ€๐Ÿณ Restaurant tech & POS Build a target list of Japanese restaurants by city for POS, reservation, or delivery-platform sales. #### ๐Ÿ“Š Travel-tech curation Power restaurant recommendations in travel apps, hotel concierge tools, and destination guides. #### ๐Ÿ“ˆ F\&B market intelligence Track price-range distribution and cuisine density across Tokyo wards or other Japanese cities. #### ๐ŸŒ Localization & directory enrichment Add verified Japanese restaurant data to multilingual review sites or food-discovery platforms. *** ### ๐Ÿ“ˆ How it compares to alternatives | Approach | Cost | Coverage | Refresh | Filters | Setup | |---|---|---|---|---|---| | **โญ Tabelog Japan Restaurant Scraper** *(this Actor)* | $5 free credit, then pay-per-use | Full source coverage | **Live per run** | Source-native filters supported | โšก 2 min | | Build your own scraper | Engineering hours | Full once built | Whenever you maintain it | Custom code | ๐Ÿข Days to weeks | | Paid managed APIs | $$$ monthly | Vendor-defined | Live | Vendor-defined | โณ Hours | | Third-party data dumps | Varies | Subset, often stale | Periodic | None | ๐Ÿ•’ Variable | Pick this Actor when you want broad coverage, server-side filtering, and no pipeline maintenance. *** ### ๐Ÿš€ How to use 1. [Create a free account](https://console.apify.com/sign-up?fpr=vmoqkp) on Apify (includes $5 in free credit). 2. Open the **Tabelog Japan Restaurant Scraper** Actor page. 3. Fill out the input form and click **Start**. 4. Download your dataset in CSV, Excel, JSON, or XML. *** ### ๐ŸŒŸ Beyond business use cases #### ๐ŸŽ“ Research and academia Hospitality researchers can study cuisine clustering, price stratification, and rating distributions across Japanese cities. #### ๐ŸŽจ Personal and creative Food bloggers and travel writers can build curated lists of top-rated restaurants in any Tokyo neighborhood. #### ๐Ÿค Non-profit and civic Tourism boards can publish open datasets of recommended local cuisine. #### ๐Ÿงช Experimentation Data scientists can use cuisine + price-range + rating as a multi-label classification benchmark for Japanese NLP. *** ### ๐Ÿค– Ask an AI assistant about this scraper Open a ready-to-send prompt about this ParseForge actor in the AI of your choice: - ๐Ÿ’ฌ [**ChatGPT**](https://chat.openai.com/?q=How%20do%20I%20use%20the%20%F0%9F%8D%A3%20Tabelog%20Japan%20Restaurant%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - ๐Ÿง  [**Claude**](https://claude.ai/new?q=How%20do%20I%20use%20the%20%F0%9F%8D%A3%20Tabelog%20Japan%20Restaurant%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - ๐Ÿ” [**Perplexity**](https://perplexity.ai/search?q=How%20do%20I%20use%20the%20%F0%9F%8D%A3%20Tabelog%20Japan%20Restaurant%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - ๐Ÿ…’ [**Copilot**](https://copilot.microsoft.com/?q=How%20do%20I%20use%20the%20%F0%9F%8D%A3%20Tabelog%20Japan%20Restaurant%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) *** ### โ“ Frequently Asked Questions #### What cities are supported? Tokyo, Osaka, Kyoto, Fukuoka, Sapporo, Hokkaido, Yokohama, Nagoya, Kobe, Sendai, Hiroshima, Okinawa. #### How do I find an area code? Browse Tabelog and the area code (e.g., `A1311` for Ueno) appears in the URL. Leave empty to scrape the entire city. #### Are reviews returned? No. The actor returns aggregate rating and review count. Individual review text would require a separate, slower scraper. #### Are menus included? No, only the restaurant directory entry. Tabelog does not expose full menus on the listing page. #### How fresh is the data? Records are scraped in real time. Tabelog updates daily as restaurants open, close, and submit new ratings. *** ### ๐Ÿ”Œ Integrate with any app Connect this Actor to your stack via the [Apify integrations](https://docs.apify.com/platform/integrations) catalog: - ๐Ÿ“Š **Make / Zapier / n8n** - trigger scrapes from any business workflow. - ๐Ÿ’ฌ **Slack / Discord** - get a notification when a run finishes. - ๐Ÿ“ **Google Drive / Google Sheets** - push the dataset directly into a spreadsheet. - ๐Ÿ“จ **Gmail / Mailchimp / HubSpot** - automate outreach with the scraped leads. - ๐Ÿ”Œ **Apify CLI / SDK** - programmatic control from Python, Node.js, or any HTTP client. - โšก **Webhooks** - POST run results to any endpoint when complete. *** ### ๐Ÿ”— Recommended Actors - ๐Ÿ”ง [**Booking.com Hotels**](https://apify.com/parseforge/booking-com-hotels-scraper) - ๐Ÿ”ง [**TripAdvisor Scraper**](https://apify.com/parseforge/tripadvisor-scraper) - ๐Ÿ”ง [**Expedia Scraper**](https://apify.com/parseforge/expedia-scraper) - ๐Ÿ”ง [**Agoda Scraper**](https://apify.com/parseforge/agoda-scraper) - ๐Ÿ”ง [**OpenSky Flights**](https://apify.com/parseforge/opensky-flights-scraper) *** > **Disclaimer:** This Actor scrapes only publicly accessible data. We do not collect personal information beyond what is voluntarily published by the source. Do not use the data for unauthorized contact, spam, or any purpose violating applicable laws or the source site's Terms of Service. Respect [GDPR](https://gdpr.eu/), [CCPA](https://oag.ca.gov/privacy/ccpa), and applicable consumer-protection laws. ParseForge is not affiliated with any source site. *** **๐Ÿ†˜ Need Help?** [**Open our contact form**](https://tally.so/r/BzdKgA) to request a new scraper, propose a custom data project, or report an issue. # Actor input Schema ## `city` (type: `string`): Tabelog city slug (English). ## `areaCode` (type: `string`): Optional area filter (e.g., 'A1311' for Ueno area in Tokyo). Leave empty to scrape entire city. ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## Actor input object example ```json { "city": "tokyo", "maxItems": 10 } ``` # Actor output Schema ## `overview` (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 = { "areaCode": "", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/tabelog-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "areaCode": "", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("parseforge/tabelog-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "areaCode": "", "maxItems": 10 }' | apify call parseforge/tabelog-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/tabelog-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tabelog Japan Restaurant Scraper", "description": "Scrape Japan's largest restaurant directory. Returns name, cuisine, price range, address, geo coordinates, phone, rating, review count, image, and JSON-LD structured data per restaurant. Filter by city, area, or cuisine.", "version": "1.0", "x-build-id": "v5Eh3fs8brMZebE4z" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~tabelog-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-tabelog-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~tabelog-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-tabelog-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~tabelog-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-tabelog-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "city": { "title": "City", "enum": [ "tokyo", "osaka", "kyoto", "fukuoka", "sapporo", "hokkaido", "yokohama", "nagoya", "kobe", "sendai", "hiroshima", "okinawa" ], "type": "string", "description": "Tabelog city slug (English).", "default": "tokyo" }, "areaCode": { "title": "Area Code (optional)", "type": "string", "description": "Optional area filter (e.g., 'A1311' for Ueno area in Tokyo). Leave empty to scrape entire city." }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" } } }, "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 } } } } } } } } } } ```