We extract venue directories, event calendars, critical reviews, and local guides from Time Out. 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 Venues & Restaurants objects from timeout.com. All fields typed and schema-versioned.
"venue_id": "v-849201", "name": "Dishoom", "category": "Restaurants", "neighborhood": "Covent Garden", "city": "London", "critic_rating": 4.0, "price_tier": 2, "latitude": 51.5126
| # | venue_id | name | category | subcategory | city | neighborhood |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Events & Things to Do objects from timeout.com. All fields typed and schema-versioned.
"event_id": "e-99214", "title": "Yayoi Kusama: Infinity Mirror Rooms", "event_type": "Art", "venue_name": "Tate Modern", "start_date": "2026-05-18", "price_string": "From 10 GBP", "is_editors_pick": true, "critic_rating": 5.0
| # | event_id | title | event_type | venue_name | venue_id | start_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews & Ratings objects from timeout.com. All fields typed and schema-versioned.
"review_id": "r-55123", "target_id": "v-849201", "target_type": "venue", "author_type": "critic", "rating": 4.0, "publish_date": "2025-11-12", "body_text": "A masterclass in Bombay comfort food.", "verdict": "Highly recommended for group dining."
| # | review_id | target_id | target_type | author_name | author_type | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for City Guides objects from timeout.com. All fields typed and schema-versioned.
"guide_id": "g-1029", "title": "The 50 best restaurants in London", "city": "London", "category": "Food & Drink", "publish_date": "2026-01-10", "featured_venues": "['v-849201', 'v-11234']", "url": "https://www.timeout.com/london/restaurants/best-restaurants-in-london"
| # | guide_id | title | city | author | publish_date | last_updated |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ticket Offers objects from timeout.com. All fields typed and schema-versioned.
"offer_id": "o-4821", "event_id": "e-99214", "provider": "Time Out Offers", "discounted_price": 15.0, "original_price": 25.0, "currency": "GBP", "discount_percentage": 40, "availability_status": "Available"
| # | offer_id | event_id | title | provider | original_price | discounted_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Time Out scraper normalises complex location data, nested event schedules, and critical reviews across all regional subdomains into a single predictable schema.
Capture restaurant, bar, club, and attraction listings with precise geolocation, opening hours, and contact metadata.
Extract start dates, end dates, recurring schedules, and venue associations for art exhibitions, gigs, and theatre shows.
Separate Time Out editorial reviews from user-generated ratings, capturing full text, star ratings, and publication dates.
Map venues and events to specific city zones and neighborhoods using Time Out's internal taxonomy.
Monitor ticket prices, discount offers, and booking links for featured events and exclusive Time Out offers.
Identify highly curated lists like 'Top 50 Restaurants' or 'Best Things to Do This Weekend' to highlight premium inventory.
Scrape timeout.com/london, timeout.com/newyork, timeout.com/tokyo, and all other regional variants through one pipeline.
Keep event calendars accurate with weekly or daily delta crawls that identify new announcements and cancelled shows.
Standardise inconsistent tags across different cities into a clean, queryable category tree.
Brief in. Clean data out.
Provide target cities, categories, or specific guide URLs. We design the extraction schema together.
We configure Scrapy crawlers, regional proxies, and pagination handling for timeout.com.
Schema validation, null-rate checks, and location accuracy verification before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Time Out uses heavy frontend caching, dynamic location routing, and varied page structures across cities. Here is how we extract clean data.
Time Out aggressively redirects users based on IP geolocation. We utilise region-specific proxy pools and strict cookie management to scrape New York data from London servers without triggering redirect loops.
Event dates and ticket availabilities are often loaded via client-side JavaScript. We execute full Playwright sessions to render these dynamic components before extracting the schedule data.
Older city guides on Time Out often use legacy DOM structures compared to flagship cities. Our selector chains handle multiple layout variations, ensuring a consistent output schema regardless of the city.
Time Out limits standard pagination on large categories. We map category sitemaps and utilise targeted search queries to extract the full venue directory, bypassing frontend display limits.
Events expire rapidly. We maintain a hash index of active events and run high-frequency delta crawls to update statuses, add new announcements, and flag past events without re-scraping the entire city.
Incorporate expert venue reviews and event schedules into travel booking platforms to enrich the user experience.
Agencies monitor Time Out critic reviews and rankings to track client visibility in competitive urban markets.
Ticketing platforms track Time Out exclusive offers and featured events to analyse market pricing and demand.
Machine learning teams use curated venue lists and editorial text to train hyper-local recommendation models.
Restaurant groups analyse neighborhood density, price tiers, and critic ratings to identify expansion opportunities.
Firms correlate cultural density and event frequency with property values to assess neighborhood gentrification trends.
"Time Out maps the cultural heartbeat of 333 cities globally, providing the most curated dataset of urban experiences and venues available."
Extracting this requires navigating complex geo-fenced routing, heavily nested event calendars, and inconsistent venue schemas across different regional subdomains. DataFlirt normalises these variations into a predictable, queryable schema so your team can focus on building products rather than fixing broken parsers.
Everything supported by our timeout.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About timeout.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available venue information, event schedules, and reviews from Time Out is generally permissible under applicable laws. DataFlirt targets only public, non-authenticated data. We do not extract personal user data or circumvent authentication walls. Clients should review Time Out ToS and consult legal counsel for specific use cases.
Time Out redirects users based on IP geolocation. We use region-specific proxy pools and strict cookie management to ensure our crawlers access the exact city subdomain required, preventing redirect loops and inaccurate data.
Yes. Our pipeline supports all global subdomains. We normalise the data into a single schema, accounting for regional layout variations and language differences where necessary.
For active event calendars, we configure delta crawls that run daily or weekly to capture new announcements, update availability, and flag expired events. Full venue directory refreshes typically run monthly.
Yes. We separate Time Out editorial reviews (including star ratings and full text) from aggregated user ratings, ensuring you can distinguish expert opinions from general public sentiment.
Our extraction pipeline includes custom parsing logic to normalise recurring text strings into structured date formats and boolean flags, making the data immediately queryable in your warehouse.
Absolutely. We provide a sample run of up to 500 venues or events for a specific city as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off venue directory extract or a continuous event-monitoring feed across 50 cities, we scope, build, and operate the pipeline. Tell us what you need.
