# Tabelog Scraper (`huggable_quote/tabelog-scraper`) Actor Extract restaurant details and reviews from Tabelog (食べログ), Japan's #1 restaurant review platform. Search by keyword/area or provide URLs directly. - **URL**: https://apify.com/huggable_quote/tabelog-scraper.md - **Developed by:** [OrbitData Labs](https://apify.com/huggable_quote) (community) - **Categories:** Travel - **Features:** Limited permissions - **Stats:** 68 total users, 17 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. 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. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## 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. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Tabelog Scraper — Extract restaurant data and reviews from Tabelog ### What does Tabelog Scraper do? **Tabelog Scraper** extracts restaurant details and reviews from [Tabelog (食べログ)](https://tabelog.com), Japan's largest restaurant review platform with **890,000+ restaurants** and **85 million+ reviews**. Simply enter a keyword like "ラーメン" or paste restaurant URLs, and the scraper collects structured data you can download as **JSON, CSV, Excel**, or connect to your apps via the **Apify API**. You can use it in two ways: - 🔍 **Search mode** — Find restaurants by keyword and area (e.g., "寿司" in Tokyo) - 🔗 **Direct URL mode** — Provide specific Tabelog restaurant URLs ### Why scrape Tabelog restaurant data? Tabelog is Japan's #1 restaurant review site, trusted by millions of diners. Extracting its data opens doors to powerful use cases: - 📊 **Market research** — Study dining trends, pricing, and customer satisfaction across Japan - 🤖 **NLP & sentiment analysis** — Build Japanese language models with authentic restaurant review corpora - 🗺️ **Travel & food apps** — Power recommendation engines with real restaurant data - 📈 **Competitive intelligence** — Monitor competitor restaurants, pricing, and customer feedback - 🗄️ **Restaurant databases** — Build comprehensive directories with address, hours, budget, and ratings Combined with the **Apify platform**, you get automatic retries, proxy rotation, scheduled runs, API access, and seamless integrations with tools like Google Sheets, Slack, Zapier, and more. ### What data can you extract from Tabelog? #### Restaurant information
FieldExample
restaurantNameグルガオン
restaurantId13002457
restaurantRating3.72
restaurantGenreインド料理、インドカレー
address東京都中央区銀座1-6-13 銀座106ビル B1F
postalCode1040061
latitude / longitude35.6747 / 139.7671
nearestStation銀座一丁目駅から35m
businessHours月・火・水・木・金
budgetDinner￥2,000～￥2,999
budgetLunch￥1,000～￥1,999
paymentMethodsカード可（VISA、Master、JCB、AMEX、Diners）
seats38席（テーブル席のみ）
privateRoom無
smokingPolicy全席禁煙
parking無
awardsアジア・エスニック 百名店 2024 選出店
reservation予約可
homepagehttp://gurgaontokyo.com/
officialAccountsInstagram, Twitter URLs
childPolicy子供可
servicesテイクアウト、複数言語メニューあり
phoneNumber03-3563-0623
photoUrlMain restaurant photo URL
budgetFromReviews￥3,000～￥3,999 (aggregated from reviewer spend)
serviceChargeランチは現金払いのみ
charterReservation不可
spaceFacilitiesおしゃれな空間、落ち着いた空間
drinksワインあり、カクテルあり
cuisineNotesベジタリアンメニューあり
occasions家族・子供と ｜ 知人・友人と
remarks瓶コーク提供店
#### Review data (when `includeReviews` is enabled) Each review row includes all restaurant fields above, plus:
FieldExample
reviewText美味しすぎて感動した銀座にあるインドカレー屋さん…
rating4.5
scoreFood, scoreService, scoreAtmosphere, scoreCostPerformance, scoreDrinks4.5, 4.0, 4.0, 4.5, null (sub-scores; null when the reviewer left one blank)
visitDate2026/04
visitCount3 (the reviewer's 3rd visit)
reviewerNameわらびもちーず
reviewerReviewCount / reviewerFollowerCount604 / 257
reviewTitle銀座の名店カレー
mealTypeディナー
priceRange￥2,000～￥2,999
reviewIdB470973875
photosPhoto URLs (when enabled)
### How to scrape Tabelog restaurant data 1. Go to [Tabelog Scraper](https://apify.com/huggable_quote/tabelog-scraper) on Apify Store 2. Click **Try for free** to open the Actor in Apify Console 3. Choose your input method: - **Search mode**: Enter a keyword (e.g., `カレー`) and select an area (e.g., `tokyo`) - **Direct URLs**: Paste one or more Tabelog restaurant URLs 4. Set **Include reviews** to `true` for full review text, or `false` for restaurant info only 5. Click **Start** and wait for the run to finish 6. Download your data as JSON, CSV, Excel, or connect via API #### Input example — Search mode ```json { "searchKeyword": "ラーメン", "searchArea": "tokyo", "maxRestaurants": 10, "includeReviews": true, "maxReviewsPerRestaurant": 50, "sortBy": "newest" } ``` #### Input example — Direct URL mode ```json { "startUrls": [ { "url": "https://tabelog.com/tokyo/A1304/A130401/13002457/" } ], "includeReviews": true, "maxReviewsPerRestaurant": 100 } ``` > 💡 **Tip**: Set `includeReviews` to `false` if you only need restaurant details — it's much faster and cheaper. ### Input options Tabelog Scraper has the following input options. Click on the [Input tab](https://apify.com/huggable_quote/tabelog-scraper/input-schema) for more information. | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `startUrls` | Array | — | Tabelog restaurant page URLs | | `searchKeyword` | String | — | Search keyword (e.g., `寿司`, `カレー`) | | `searchArea` | String | `all` | Prefecture filter — 47 prefectures supported | | `maxRestaurants` | Integer | `5` | Max restaurants from search results | | `includeReviews` | Boolean | `true` | Extract reviews or restaurant info only | | `maxReviewsPerRestaurant` | Integer | `100` | Max reviews per restaurant (`0` = all). Tabelog only serves ~60 review pages, so **~1,100 reviews per restaurant is the hard ceiling** — higher values are capped by the site, not by this Actor. | | `reviewLanguage` | String | `all` | Filter reviews by language | | `includePhotos` | Boolean | `false` | Include review photo URLs | | `sortBy` | String | `newest` | Sort order: `newest`, `rating_high`, `rating_low`, `default` | | `minRating` | Number | — | Only reviews rated at least this (e.g. `4.0`). With `sortBy: rating_high` the crawl stops as soon as ratings drop below it. | | `visitedAfter` | String | — | Only reviews for visits in this month or later, as `YYYY-MM` (e.g. `2026-01`). | | `mealType` | String | `all` | `all`, `lunch` or `dinner` | | `withPhotosOnly` | Boolean | `false` | Only reviews that include photos | | `onlyNewReviews` | Boolean | `false` | Skip reviews an earlier run already delivered — for scheduled monitoring. State is kept in the `tabelog-scraper-seen-reviews` key-value store in your account (delete it to start over). | | `proxyConfiguration` | Object | — | Apify Proxy settings | You must provide either `startUrls` or `searchKeyword` (or both). **Review filters are free:** reviews that don't match `minRating` / `visitedAfter` / `mealType` / `withPhotosOnly` are dropped on the review list page — they are never fetched in full and never charged. `maxReviewsPerRestaurant` counts matching reviews only. ### Output example You can download the dataset extracted by Tabelog Scraper in various formats such as **JSON, HTML, CSV, or Excel**. #### Restaurant info only (`includeReviews: false`) ```json { "restaurantName": "グルガオン", "restaurantUrl": "https://tabelog.com/tokyo/A1301/A130101/13002457/", "restaurantId": "13002457", "restaurantRating": 3.72, "restaurantGenre": "インド料理、インドカレー", "restaurantArea": "東京", "totalReviewCount": 3177, "address": "東京都中央区銀座1-6-13 銀座106ビル B1F", "postalCode": "1040061", "latitude": 35.6747, "longitude": 139.7671, "nearestStation": "銀座一丁目駅から35m", "businessHours": "月・火・水・木・金", "budgetDinner": "￥2,000～￥2,999", "budgetLunch": "￥1,000～￥1,999", "paymentMethods": "カード可（VISA、Master、JCB、AMEX、Diners）", "seats": "38席（テーブル席のみ）", "smokingPolicy": "全席禁煙", "awards": ["アジア・エスニック 百名店 2024 選出店"], "homepage": "http://gurgaontokyo.com/", "scrapedAt": "2026-05-02T12:00:00.000Z" } ``` #### With reviews (`includeReviews: true`) ```json { "restaurantName": "グルガオン", "restaurantRating": 3.72, "address": "東京都中央区銀座1-6-13 銀座106ビル B1F", "reviewText": "美味しすぎて感動した銀座にあるインドカレー屋さん\n\n大人気と聞いていたので...", "rating": 4.5, "scoreFood": 4.5, "scoreService": 4.0, "scoreAtmosphere": 4.0, "scoreCostPerformance": 4.5, "scoreDrinks": null, "visitDate": "2025/10", "visitCount": 1, "reviewerName": "わらびもちーず", "reviewerReviewCount": 604, "reviewerFollowerCount": 257, "mealType": "ディナー", "priceRange": "￥2,000～￥2,999", "reviewUrl": "https://tabelog.com/tokyo/A1301/A130101/13002457/dtlrvwlst/B...", "scrapedAt": "2026-05-02T12:00:00.000Z" } ``` ### How much does it cost to scrape Tabelog? Tabelog Scraper uses a **pay-per-result** pricing model on top of Apify platform usage costs. | Mode | Estimated cost | |------|---------------| | 🏪 Restaurant info only | ~**$0.50** per 100 restaurants | | 📝 With reviews | ~**$3.00** per 1,000 reviews | You can try the Actor **for free** on Apify's free plan. The free tier includes enough compute units to scrape several restaurants with reviews and explore the output format. > 💡 **Cost-saving tip**: Use `includeReviews: false` when you only need restaurant metadata — it skips individual review page visits and runs significantly faster. ### Tips for best results - 🇯🇵 **Use a Japan proxy** — Tabelog may geo-restrict access. On Apify, the default proxy works well, but Japan-based proxies give the best reliability. - ⏱️ **Start small** — Test with 1-2 restaurants and a few reviews to check output format before scaling up. - 🔢 **Set `maxReviewsPerRestaurant`** — Restaurants can have thousands of reviews. Set a limit to control costs and run time. Note that Tabelog itself caps review pagination at ~60 pages, so you cannot get more than **~1,100 reviews per restaurant** no matter how high you set this. - 📊 **Use Apify integrations** — Connect results directly to Google Sheets, webhooks, or your database via the Apify API. - 📅 **Schedule recurring runs** — Track review trends over time by scheduling the Actor to run daily, weekly, or monthly. ### Is it legal to scrape Tabelog? This scraper only extracts publicly available information from Tabelog. It does not extract private user data such as email addresses or personal contact information. The scraper respects rate limits with built-in delays between requests. You should be aware that extracted results may contain personal data (reviewer names, profile URLs). Personal data is protected by the GDPR in the European Union, APPI in Japan, and other regulations worldwide. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your use case is legitimate, consult your lawyers. ### Limitations and known issues - **Japanese language** — Data is extracted in Japanese. The English version (`/en/`) has limited restaurant coverage. - **Pagination cap** — Tabelog exposes at most ~60 review-list pages per restaurant (the next page returns 404), so roughly **1,100 reviews** are reachable. Restaurants with more reviews than that cannot be fully scraped, and a few reviews are rating-only with no text, so the result count is normally below the restaurant's displayed review total. - **Rate limiting** — The scraper uses 1–2 second delays between requests for polite crawling. Large-scale scraping will take time proportional to the number of reviews. ### FAQ #### Does Tabelog have an API? Tabelog does not provide a free public API for extracting restaurant data. This scraper serves as an alternative by extracting structured data from publicly available Tabelog pages. #### Can I scrape Tabelog in English? Tabelog has a limited English site at `tabelog.com/en/`, but most content is only available in Japanese. This scraper extracts data in Japanese by default. #### How many results can I get for free? On Apify's free plan, you can scrape approximately **5-10 restaurants with reviews** per month, depending on the number of reviews per restaurant. #### Can I extract data from all 47 prefectures? Yes. The `searchArea` input supports all 47 Japanese prefectures (from `hokkaido` to `okinawa`), or you can set it to `all` for a nationwide search. #### How does the 4-stage pipeline work? The scraper operates in four stages: 1. **Search** — Finds restaurant URLs from keyword search results 2. **Restaurant** — Visits each restaurant page and extracts detailed metadata 3. **Review list** — Browses review list pages and collects review metadata 4. **Review detail** — Visits individual review pages for full, untruncated review text #### How do I collect only new reviews on a schedule? Set `onlyNewReviews: true` and `sortBy: newest`, then schedule the run (e.g. daily). The first run collects as usual and remembers every review ID per restaurant; later runs stop at the first review they already delivered, so you only get — and only pay for — reviews posted since the previous run. #### Why did I get fewer reviews than the restaurant shows? This is expected, and there are two separate reasons: 1. **Tabelog's pagination ceiling** — the review list serves at most **~60 pages** per restaurant (requesting page 61 returns a 404), which works out to roughly **1,100 reviews**. Reviews older than that are not reachable through the site's own listing, so no scraper can retrieve them. 2. **Rating-only reviews** — some users post a score with no written review. Those entries have no text to extract, so they are skipped rather than returned as empty rows. So a restaurant displaying 1,491 reviews typically yields around 950–1,100 rows. Setting `maxReviewsPerRestaurant` higher than ~1,100 does not increase the result count. The run log states the exact reason and the number collected when the limit is reached. #### I found a bug or need a custom feature Please report issues or feature requests via the [Issues tab](https://apify.com/huggable_quote/tabelog-scraper/issues) on the Actor page. Feedback is always welcome! # Actor input Schema ## `startUrls` (type: `array`): Tabelog URLs to scrape. Restaurant page URLs are scraped directly; search, area-list, or ranking URLs (containing 'rstLst', '?sk=' or '?sw=') are auto-paginated to collect restaurants. The 'https://' scheme is optional. If calling via API, this field is 'startUrls' (the aliases 'restaurantUrls' and 'urls' are also accepted). Not required if using keyword search. ## `searchKeyword` (type: `string`): Search Tabelog by keyword (e.g. restaurant name, cuisine type). Not required if using direct URLs. ## `searchArea` (type: `string`): Limit search to a specific prefecture. Only used with searchKeyword. ## `maxRestaurants` (type: `integer`): Maximum number of restaurants to scrape from search results. Only used with searchKeyword. ## `includeReviews` (type: `boolean`): Whether to scrape individual reviews. When false, only restaurant info (name, address, hours, rating, etc.) is collected — much faster and cheaper. ## `maxReviewsPerRestaurant` (type: `integer`): Maximum number of reviews to extract per restaurant. Set 0 for all reviews. Only used when includeReviews is true. ## `reviewLanguage` (type: `string`): Filter reviews by language. ## `includePhotos` (type: `boolean`): Whether to include review photo URLs in the output. ## `sortBy` (type: `string`): How to sort reviews. ## `minRating` (type: `number`): Only keep reviews whose overall rating is at least this value (e.g. 4.0). Leave empty for all ratings. With sortBy = rating_high, pagination stops as soon as ratings drop below this value. Only used when includeReviews is true. ## `visitedAfter` (type: `string`): Only keep reviews for visits in this month or later, e.g. 2026-01. Reviews without a visit month are excluded. With sortBy = newest, pagination stops after 2 consecutive pages with no matching visit. Only used when includeReviews is true. ## `mealType` (type: `string`): Only keep lunch or dinner reviews. Only used when includeReviews is true. ## `withPhotosOnly` (type: `boolean`): Only keep reviews that include at least one photo. Only used when includeReviews is true. ## `onlyNewReviews` (type: `boolean`): Skip reviews that an earlier run of this Actor in your account already delivered — ideal for scheduled monitoring. Seen review IDs are kept per restaurant in a key-value store named "tabelog-scraper-seen-reviews" (delete it to start over). With sortBy = newest, the crawl stops at the first already-collected review. Only used when includeReviews is true. ## `proxyConfiguration` (type: `object`): Apify Proxy configuration. If left at the default, the Actor automatically uses a Japan residential proxy (falling back to Japan datacenter), which is strongly recommended to avoid Tabelog's geo-blocking. Pick a specific group/country here only to override that. ## Actor input object example ```json { "startUrls": [ { "url": "https://tabelog.com/tokyo/A1311/A131102/13003699/" } ], "searchKeyword": "", "searchArea": "all", "maxRestaurants": 5, "includeReviews": true, "maxReviewsPerRestaurant": 3, "reviewLanguage": "all", "includePhotos": false, "sortBy": "newest", "mealType": "all", "withPhotosOnly": false, "onlyNewReviews": false } ``` # Actor output Schema ## `results` (type: `string`): Dataset containing restaurant information and/or reviews. # 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 = { "startUrls": [ { "url": "https://tabelog.com/tokyo/A1311/A131102/13003699/" } ], "searchKeyword": "", "searchArea": "all", "maxRestaurants": 5, "includeReviews": true, "maxReviewsPerRestaurant": 3, "reviewLanguage": "all", "sortBy": "newest" }; // Run the Actor and wait for it to finish const run = await client.actor("huggable_quote/tabelog-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 = { "startUrls": [{ "url": "https://tabelog.com/tokyo/A1311/A131102/13003699/" }], "searchKeyword": "", "searchArea": "all", "maxRestaurants": 5, "includeReviews": True, "maxReviewsPerRestaurant": 3, "reviewLanguage": "all", "sortBy": "newest", } # Run the Actor and wait for it to finish run = client.actor("huggable_quote/tabelog-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ { "url": "https://tabelog.com/tokyo/A1311/A131102/13003699/" } ], "searchKeyword": "", "searchArea": "all", "maxRestaurants": 5, "includeReviews": true, "maxReviewsPerRestaurant": 3, "reviewLanguage": "all", "sortBy": "newest" }' | apify call huggable_quote/tabelog-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,huggable_quote/tabelog-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/zRPjPfvs75sVAt6lf/builds/OpdMHZabMmHsuPkJY/openapi.json