We extract restaurant profiles, tasting menu pricing, dynamic availability, and winery experiences from Tock. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Restaurant Profiles objects from tock.com. All fields typed and schema-versioned.
"restaurant_id": "r-84921", "name": "Alinea", "city": "Chicago", "cuisine_type": "Contemporary", "price_tier": 4, "michelin_status": "3 Stars", "operating_hours": "Wed-Sun 17:00-22:00"
| # | restaurant_id | name | url | city | neighbourhood | cuisine_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Experiences objects from tock.com. All fields typed and schema-versioned.
"experience_id": "exp-3921", "restaurant_id": "r-84921", "title": "The Gallery Menu", "price": 485.0, "currency": "USD", "prepaid_required": true, "duration_minutes": 150
| # | experience_id | restaurant_id | title | description | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Availability objects from tock.com. All fields typed and schema-versioned.
"restaurant_id": "r-84921", "experience_id": "exp-3921", "date": "2026-08-14", "time": "19:30", "party_size": 2, "available": true, "dynamic_price": 495.0
| # | restaurant_id | experience_id | date | time | party_size | available |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Winery Events objects from tock.com. All fields typed and schema-versioned.
"event_id": "evt-9102", "winery_id": "w-1102", "event_name": "Autumn Harvest Tasting", "ticket_price": 120.0, "capacity": 40, "age_restriction": "21+", "start_datetime": "2026-10-12T14:00:00Z"
| # | event_id | winery_id | event_name | location | start_datetime | ticket_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Tags objects from tock.com. All fields typed and schema-versioned.
"restaurant_id": "r-84921", "average_rating": 4.9, "review_count": 3412, "vibe_tags": "['Formal', 'Special Occasion', 'Quiet']", "dietary_options": "['Vegetarian available with notice']", "dress_code": "Business Casual"
| # | restaurant_id | average_rating | review_count | vibe_tags | dietary_options | awards_list |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Tock scraper handles the complex state management required to extract dynamic availability, prepaid experience pricing, and restaurant metadata across the entire platform.
Extract name, location, cuisine type, operating hours, and descriptive metadata for thousands of venues.
Capture open reservation slots mapped to specific dates, times, and party sizes in real time.
Extract prepaid tasting menu costs, deposit requirements, and dynamic pricing variations based on time slots.
Monitor ticket inventory, capacities, and pricing for special events, pop-ups, and winery tours.
Capture refund windows, penalty fees, and transferability rules for high-value prepaid reservations.
Extract Michelin star ratings, James Beard awards, and other accolades listed on the venue profile.
Collect categorical data on atmosphere, dress codes, and dietary accommodations like vegan or gluten-free.
Configure sub-minute polling intervals to capture availability changes for highly sought-after tables.
Run continuous pipelines at hourly, daily, or weekly cadences to feed your internal data models.
Brief in. Clean data out.
Provide city URLs, restaurant IDs, or specific experience links. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and GraphQL interception for tock.com.
Schema validation, null-rate checks, and availability accuracy tests before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Tock uses complex frontend state management and rate limiting to protect inventory. Here is how we maintain stable extraction.
Tock restricts high-frequency requests from data centre IPs. We route traffic through residential ISP proxies with realistic browser fingerprints to maintain access to availability endpoints.
Tock populates calendars via complex GraphQL queries. We intercept these network requests to extract clean JSON responses, bypassing the need to parse volatile DOM elements.
Accessing specific party size availability requires managing session tokens and cookies. Our Playwright integration maintains state perfectly to navigate the booking flow.
Table inventory changes rapidly. We maintain a state index and only emit records when a time slot opens or closes, reducing downstream processing load.
We monitor GraphQL schema changes and null-rate spikes in real time. Our engineers update selectors before your pipeline misses a scheduled delivery.
Hospitality groups monitor tasting menu pricing, deposit requirements, and cancellation policies across competing premium venues.
Analysts track reservation velocity and sold-out rates to measure demand for specific cuisines and dining formats.
Alternative booking platforms and discovery apps synchronise availability data to present unified dining options to users.
Private equity firms measure restaurant group health by analysing booking lead times and average cover prices.
High-end concierge desks automate availability monitoring to secure premium tables the moment cancellations occur.
Industry researchers analyse the shift between prepaid tasting menus and standard reservations across different cities.
"Tock holds the premium inventory of the hospitality world. Tracking availability and pricing across tasting menus requires a pipeline built for high-frequency calendar state changes."
Most teams fail at extracting Tock data because availability is locked behind dynamic GraphQL queries and strict rate limits. DataFlirt manages the residential proxies, query hydration, and session state required to map real-time table inventory. Your engineers get clean relational data, not HTTP 429 errors.
Everything supported by our tock.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright executes JavaScript and manages the complex session state required for reservation flows.
We route requests through residential ISP proxies to avoid rate limits and maintain access to high-frequency availability endpoints.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About tock.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt extracts only public, non-authenticated restaurant profiles, pricing, and availability data. We do not extract personal user data or bypass authentication walls. Clients should review Tock terms of service and consult legal counsel.
We use Playwright to navigate the frontend and intercept the underlying GraphQL queries that populate the calendar. This provides clean, structured JSON data directly from the API rather than parsing HTML.
Yes. We extract all listed experiences per restaurant, including prepaid menu costs, required deposits, and dynamic pricing variations based on selected dates and times.
Pipeline frequency is configurable. For high-demand venues, we can poll availability at sub-minute intervals. Broad catalogue sweeps typically run daily.
Yes. Our schema handles standard restaurant reservations as well as ticketed events, winery tours, and temporary pop-up experiences hosted on the platform.
We typically start with a defined target list of venues or cities. Pricing scales based on the number of targets and the polling frequency required. Contact us for a precise quote.
Yes. We offer sample runs for a subset of venues to validate schema fit and data accuracy before you commit to a production pipeline.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily snapshot of restaurant metadata or real-time availability monitoring for premium venues, we manage the infrastructure. Tell us your requirements.
