We extract event schedules, venue coordinates, restaurant directories, and hotel listings from Visit Seattle. 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 Events objects from visitseattle.org. All fields typed and schema-versioned.
"event_id": "EVT-84920", "title": "Seattle International Film Festival", "start_date": "2026-05-14", "venue_name": "SIFF Cinema Uptown", "category": "Arts & Culture", "price_range": "$15 - $250"
| # | event_id | title | start_date | end_date | venue_name | category |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Restaurants objects from visitseattle.org. All fields typed and schema-versioned.
"restaurant_id": "RST-1029", "name": "The Pink Door", "cuisine_type": "Italian", "neighbourhood": "Pike Place Market", "price_tier": "$$$", "phone": "+1 206-443-3241"
| # | restaurant_id | name | cuisine_type | neighbourhood | address | phone |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Hotels objects from visitseattle.org. All fields typed and schema-versioned.
"hotel_id": "HTL-442", "name": "Fairmont Olympic Hotel", "star_rating": 5, "neighbourhood": "Downtown", "total_rooms": 450, "amenities": "['Pool', 'Spa', 'Fitness Centre', 'Pet Friendly']"
| # | hotel_id | name | star_rating | neighbourhood | address | amenities |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Attractions objects from visitseattle.org. All fields typed and schema-versioned.
"attraction_id": "ATT-992", "name": "Space Needle", "category": "Landmarks", "admission_fee": "$35.00 - $39.00", "latitude": 47.6205, "longitude": -122.3493
| # | attraction_id | name | category | description | address | admission_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Neighbourhoods objects from visitseattle.org. All fields typed and schema-versioned.
"neighbourhood_id": "NH-12", "name": "Capitol Hill", "known_for": "['Nightlife', 'Coffee Shops', 'LGBTQ+ Culture']", "transit_options": "['Link Light Rail', 'Bus']", "top_attractions": "['Volunteer Park', 'Starbucks Reserve Roastery']", "page_url": "https://visitseattle.org/neighborhoods/capitol-hill/"
| # | neighbourhood_id | name | description | known_for | transit_options | image_url |
|---|---|---|---|---|---|---|
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Our visitseattle.org scraper extracts structured data across every category: dynamic event calendars, deep venue directories, and curated neighbourhood guides, handling all map layers and pagination.
Parse dynamic event dates, times, venues, and ticketing links. Handles recurring events and multi-day festival schedules.
Extract capacity, contact details, and accessibility information for convention centres, theatres, and stadiums.
Capture restaurant names, cuisines, price tiers, and reservation links across thousands of local listings.
Extract star ratings, amenity lists, room counts, and direct booking URLs for Seattle accommodation.
Compile descriptive text, top attractions, and transit options for all 40+ Seattle neighbourhoods.
Extract specific accessibility features, wheelchair access notes, and sensory guides where published.
Extract latitude and longitude points from embedded map widgets for spatial analysis.
Run daily or weekly pipelines to capture newly announced events and seasonal menu changes.
Extract admission fees, resident discounts, and external ticketing provider URLs.
Brief in. Clean data out.
Provide target categories, date ranges, or specific directory URLs. We design the extraction schema together.
We configure Scrapy crawlers, handle map widget hydration, and manage pagination logic for visitseattle.org.
Schema validation, null-rate checks, coordinate verification, and sample outputs before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Modern destination sites rely on dynamic map layers and JavaScript-heavy calendars. We manage the extraction complexity.
Venue and attraction pages often embed location data within JavaScript map objects rather than raw HTML. We execute Playwright sessions to intercept map API responses and extract clean latitude and longitude pairs.
The event calendar uses AJAX-based infinite scroll and dynamic date filtering. Our crawlers programmatically iterate through date parameters to ensure 100% coverage of future events without missing records.
Tourism sites frequently update layouts for seasonal campaigns. We use multiple fallback chains per field, relying on structured data (JSON-LD) where available, to prevent pipeline breakage during site updates.
For event monitoring, we maintain a hash index of last-seen values. Subsequent runs only push diffs, allowing you to track postponed dates or cancelled performances efficiently.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing coordinates, and schema drift, ensuring your travel applications always have reliable data.
OTA platforms and travel apps ingest local event and venue data to enrich their Seattle destination guides.
Marketing agencies monitor business listings to ensure client NAP (Name, Address, Phone) consistency across local directories.
Ticketing platforms and hospitality providers track major conventions and festivals to forecast local demand spikes.
Real estate and hospitality investors analyse neighbourhood attraction density and hotel room supply metrics.
Civic organisations map accessibility features and transit proximity across major cultural venues.
AI travel assistants use structured restaurant and itinerary data to generate personalised recommendations for visitors.
"Visit Seattle maintains the definitive catalogue of the city's hospitality, events, and cultural infrastructure, critical data for travel aggregators."
Extracting venue details, seasonal event schedules, and local business directories requires navigating complex calendar widgets, dynamic map layers, and paginated lists. DataFlirt manages the extraction infrastructure so you can focus on building travel products.
Everything supported by our visitseattle.org 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 deduplication. Playwright handles JavaScript rendering for dynamic event calendars and map widgets.
We maintain pools of residential US proxies to ensure uninterrupted access during high-volume directory extraction runs.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling for daily event updates. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About visitseattle.org scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public, non-authenticated directory and event data. We do not extract personal data or circumvent authentication walls. Clients should review the target site's Terms of Service.
We use Playwright to execute JavaScript and intercept AJAX requests, allowing us to programmatically iterate through date filters and infinite scroll pagination to capture all future events.
Pipelines can be configured for daily or weekly runs depending on your requirements. Event calendars are typically refreshed daily to capture new announcements and cancellations.
We can extract past events if they remain accessible via the site's archive or URL structure. Otherwise, we build a historical dataset moving forward from the date your pipeline is commissioned.
Our packages start at defined directory scopes with weekly delivery. For comprehensive site extraction or real-time event monitoring, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 500 records as part of the pre-engagement scoping process, allowing you to validate schema fit and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off venue directory export or continuous event calendar monitoring, we scope, build, and operate the pipeline. Tell us what you need.
