# Tabelog Japan Restaurant Scraper (`piquno/tabelog-japan-restaurant-scraper`) Actor Scrape restaurant data from Tabelog (食べログ), Japan's #1 restaurant review site. Extract ratings, reviews, genres, budgets, locations, hours, and photos from 800K+ restaurants across all 47 prefectures. - **URL**: https://apify.com/piquno/tabelog-japan-restaurant-scraper.md - **Developed by:** [Piquno](https://apify.com/piquno) (community) - **Categories:** Travel, E-commerce, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $80.00 / 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 ## Tabelog Japan Restaurant Scraper Scrape restaurant data from [Tabelog](https://tabelog.com/en/) (食べログ), Japan's largest restaurant review site with **800,000+ listings** across all 47 prefectures. ### What data can you extract? | Field | Source | Description | |-------|--------|-------------| | name | Listing | Restaurant name | | url | Listing | Tabelog URL | | rating | Listing | Rating score (0-5 scale) | | reviewCount | Listing | Number of reviews | | nearestStation | Listing | Closest train station | | genre | Listing | Cuisine type (Sushi, Ramen, Yakiniku, etc.) | | dinnerBudget | Listing | Average dinner price range | | lunchBudget | Listing | Average lunch price range | | closedDays | Listing | Regular holidays | | features | Listing | Tags (credit card, non-smoking, children welcome, etc.) | | awards | Listing | Tabelog Awards & Hyakumeiten (Top 100) badges | | images | Listing | Up to 5 restaurant photos | | address | Detail | Full address (Japanese) | | phone | Detail | Phone number | | businessHours | Detail | Opening hours | | transportation | Detail | Directions from nearest station | | paymentMethods | Detail | Accepted payment methods | | seats | Detail | Seating capacity | **Listing fields** are always included. **Detail fields** require enabling "Include Detail Pages" (slower, makes one extra request per restaurant). ### Input parameters - **Area**: Any of Japan's 47 prefectures (Tokyo, Osaka, Kyoto, Hokkaido, etc.) - **Keyword**: Search by cuisine or name — supports Japanese (ラーメン, 寿司, カレー) and English - **Sort By**: Highest Rated, Most Reviews, Most Reserved (Travelers/Locals), Most Viewed - **Max Results**: 1-500 restaurants per run - **Include Details**: Toggle extra detail page scraping ### Example output ```json { "name": "Yoroniku", "url": "https://tabelog.com/en/tokyo/A1306/A130602/13042979/", "restaurantId": "13042979", "rating": 4.18, "reviewCount": 2923, "nearestStation": "Omote Sando Sta.", "genre": "Yakiniku (Japanese BBQ), Tripe", "dinnerBudget": "JPY 10,000 - JPY 14,999", "lunchBudget": null, "closedDays": null, "features": ["Multilingual menu", "Credit card accepted", "Non smoking"], "awards": ["The Tabelog Award 2026 Bronze winner"], "images": ["https://tblg.k-img.com/restaurant/images/..."], "searchArea": "tokyo", "searchKeyword": null, "scrapedAt": "2026-04-10T12:00:00+00:00" } ```` ### Use cases - **Market research**: Analyze restaurant density, ratings, and pricing by area and cuisine - **Travel apps**: Build restaurant databases for Japan trip planning tools - **Food analytics**: Track trends in Japanese dining — top-rated cuisines, pricing patterns, regional specialties - **Competitive analysis**: Compare restaurants by rating, review volume, and budget range - **Location intelligence**: Map restaurant data by station and prefecture ### Compliance This actor respects Tabelog's `robots.txt` guidelines with **2.5-second delays** between requests. Restaurant listing pages and detail pages are permitted for crawling. ### Cost estimate - **Listing only**: ~$0.50 per 100 restaurants - **With details**: ~$1.50 per 100 restaurants (additional detail page requests) # Actor input Schema ## `area` (type: `string`): Japanese prefecture to search. Examples: tokyo, osaka, kyoto, hokkaido, fukuoka, okinawa ## `keyword` (type: `string`): Search keyword (cuisine type, restaurant name, etc.). Supports Japanese: e.g. ラーメン, 寿司, yakitori ## `sort` (type: `string`): How to sort results ## `maxResults` (type: `integer`): Maximum number of restaurants to scrape (max 500 per search due to Tabelog pagination limits) ## `includeDetails` (type: `boolean`): Scrape each restaurant's detail page for extra data (address, phone, hours, seats, payment methods). Slower but more comprehensive. ## Actor input object example ```json { "area": "tokyo", "keyword": "", "sort": "highest_rated", "maxResults": 100, "includeDetails": false } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("piquno/tabelog-japan-restaurant-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = {} # Run the Actor and wait for it to finish run = client.actor("piquno/tabelog-japan-restaurant-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 '{}' | apify call piquno/tabelog-japan-restaurant-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=piquno/tabelog-japan-restaurant-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tabelog Japan Restaurant Scraper", "description": "Scrape restaurant data from Tabelog (食べログ), Japan's #1 restaurant review site. Extract ratings, reviews, genres, budgets, locations, hours, and photos from 800K+ restaurants across all 47 prefectures.", "version": "1.0", "x-build-id": "TZFhS56nErwD43sUR" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/piquno~tabelog-japan-restaurant-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-piquno-tabelog-japan-restaurant-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/piquno~tabelog-japan-restaurant-scraper/runs": { "post": { "operationId": "runs-sync-piquno-tabelog-japan-restaurant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/piquno~tabelog-japan-restaurant-scraper/run-sync": { "post": { "operationId": "run-sync-piquno-tabelog-japan-restaurant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "area" ], "properties": { "area": { "title": "Area (Prefecture)", "enum": [ "tokyo", "osaka", "kyoto", "hokkaido", "fukuoka", "aichi", "kanagawa", "chiba", "saitama", "hyogo", "hiroshima", "miyagi", "niigata", "nagano", "shizuoka", "okinawa", "nara", "ishikawa", "kumamoto", "kagoshima", "nagasaki", "oita", "ehime", "okayama", "fukui", "tottori", "shimane", "saga", "kochi", "tokushima", "kagawa", "wakayama", "mie", "gifu", "toyama", "fukushima", "yamagata", "akita", "iwate", "aomori", "tochigi", "gunma", "ibaraki", "yamanashi", "shiga", "yamaguchi", "miyazaki" ], "type": "string", "description": "Japanese prefecture to search. Examples: tokyo, osaka, kyoto, hokkaido, fukuoka, okinawa", "default": "tokyo" }, "keyword": { "title": "Keyword", "type": "string", "description": "Search keyword (cuisine type, restaurant name, etc.). Supports Japanese: e.g. ラーメン, 寿司, yakitori", "default": "" }, "sort": { "title": "Sort By", "enum": [ "highest_rated", "most_reviews", "most_reserved_travelers", "most_reserved_locals", "most_viewed" ], "type": "string", "description": "How to sort results", "default": "highest_rated" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of restaurants to scrape (max 500 per search due to Tabelog pagination limits)", "default": 100 }, "includeDetails": { "title": "Include Detail Pages", "type": "boolean", "description": "Scrape each restaurant's detail page for extra data (address, phone, hours, seats, payment methods). Slower but more comprehensive.", "default": false } } }, "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 } } } } } } } } } } ```