Tabelog Scraper

Extract restaurant details and reviews from Tabelog (食べログ) — Japan's largest restaurant review platform with 890,000+ restaurants and 85 million+ reviews.

Why this scraper?

• All-in-one — restaurant info (address, hours, budget, seats) AND full review text in a single run
• Search mode — find restaurants by keyword and area, no need to know URLs in advance
• Full review text — visits each review page for complete untruncated content
• Flexible — scrape restaurant info only (fast & cheap) or include reviews
• Cost-effective — ~$3.00 per 1,000 reviews

Two modes of operation

1. Restaurant info only (includeReviews: false)

Collects detailed restaurant metadata without reviews. Fast and low-cost.

2. Restaurant info + reviews (includeReviews: true)

Collects everything: restaurant details plus full review text from individual review pages.

What data can you extract?

Restaurant fields

Field	Type	Description
restaurantName	String	Restaurant name
restaurantUrl	String	Tabelog page URL
restaurantRating	Number	Overall rating (0.0–5.0)
restaurantGenre	String	Cuisine type (e.g., "インド料理、インドカレー")
restaurantArea	String	Prefecture/area
totalReviewCount	Number	Total number of reviews
address	String	Full address
nearestStation	String	Nearest station and distance
businessHours	String	Operating days/hours
budgetDinner	String	Dinner price range
budgetLunch	String	Lunch price range
paymentMethods	String	Accepted payment methods
seats	String	Number and type of seats
privateRoom	String	Private room availability
smokingPolicy	String	Smoking policy
parking	String	Parking availability
awards	Array	Tabelog awards (百名店 etc.)
reservation	String	Reservation availability
homepage	String	Restaurant homepage URL
officialAccounts	Array	Social media URLs
childPolicy	String	Policy for children
services	String	Available services

Review fields (when includeReviews: true)

Each row includes all restaurant fields above, plus:

Field	Type	Description
reviewText	String	Full review text
rating	Number	Individual review rating (0.0–5.0)
visitDate	String	Visit date (e.g., "2026/04")
reviewerName	String	Reviewer's display name
reviewerUrl	String	Reviewer's profile URL
reviewTitle	String/null	Review title
mealType	String/null	"ランチ" (lunch) or "ディナー" (dinner)
priceRange	String/null	Price range spent
reviewUrl	String	Direct URL to the review
photos	Array	Review photo URLs (when enabled)

How to use

Option A: Search by keyword

1. Set searchKeyword (e.g., ラーメン, 寿司, カレー)
2. Set searchArea (e.g., tokyo, osaka, or all)
3. Set maxRestaurants (how many restaurants to scrape)

Option B: Direct URLs

1. Add Tabelog restaurant URLs to startUrls
   • Example: https://tabelog.com/tokyo/A1304/A130401/13002457/

Then configure:

• includeReviews: true for reviews, false for restaurant info only
• maxReviewsPerRestaurant: limit reviews per restaurant (default: 100)
• sortBy: sort reviews by newest, highest/lowest rating

Input options

Parameter	Type	Default	Description
startUrls	Array	—	Tabelog restaurant URLs (optional if using search)
searchKeyword	String	—	Search keyword (optional if using URLs)
searchArea	String	"all"	Prefecture filter for search
maxRestaurants	Integer	5	Max restaurants from search results
includeReviews	Boolean	true	Whether to scrape reviews
maxReviewsPerRestaurant	Integer	100	Max reviews per restaurant (0 = all)
reviewLanguage	String	"all"	Language filter
includePhotos	Boolean	false	Include review photo URLs
sortBy	String	"newest"	Review sort order
proxyConfiguration	Object	—	Apify Proxy settings

Output examples

Restaurant info only

{
    "restaurantName": "グルガオン",
    "restaurantUrl": "https://tabelog.com/tokyo/A1301/A130101/13002457/",
    "restaurantRating": 3.72,
    "restaurantGenre": "インド料理、インドカレー",
    "restaurantArea": "東京",
    "totalReviewCount": 3173,
    "address": "東京都中央区銀座1-6-13 銀座106ビル B1F",
    "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

Each row includes all restaurant fields above, plus review data:

{
    "restaurantName": "グルガオン",
    "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,
    "visitDate": "2025/10",
    "reviewerName": "わらびもちーず",
    "mealType": "ディナー",
    "priceRange": "￥2,000～￥2,999",
    "scrapedAt": "2026-05-02T12:00:00.000Z"
}

Use cases

• Restaurant database — Build a comprehensive database of Japanese restaurants with full details
• NLP sentiment analysis — Analyze Japanese restaurant review corpora
• Market research — Study dining trends, pricing, and customer satisfaction across Japan
• Travel apps — Power recommendation engines with real data
• Competitive intelligence — Monitor restaurant details and reviews

Pricing

• Restaurant info only: ~$0.50 per 100 restaurants
• With reviews: ~$3.00 per 1,000 reviews

Limitations

• Japanese text — Data is extracted in Japanese. English version (/en/) has limited coverage.
• Rate-limited — 2-4 second delays between requests for polite crawling.
• No search URL input — Provide restaurant URLs or use keyword search. Area-level browsing URLs are not supported.
• Pagination limit — Tabelog limits review pages to ~180, so restaurants with 3,600+ reviews may not have all reviews accessible.

Technical details

• Built with Crawlee and Apify SDK
• CheerioCrawler for fast HTML parsing (no browser needed)
• 4-stage pipeline: Search → Restaurant → Review List → Review Detail
• Automatic retry (up to 3), deduplication by review URL
• Auto-proxy on Apify cloud for reliability