We extract event calendars, hospitality listings, dining directories, and attraction metadata from sftravel.com. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Hotels & Lodging objects from sftravel.com. All fields typed and schema-versioned.
"name": "Fairmont San Francisco", "neighborhood": "Nob Hill", "star_rating": 5, "amenities": "['WiFi', 'Gym', 'Spa']", "latitude": 37.7925, "longitude": -122.41
| # | hotel_id | name | neighborhood | address | phone | website_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Dining & Restaurants objects from sftravel.com. All fields typed and schema-versioned.
"name": "Gary Danko", "cuisine_type": "French", "price_tier": "$$$$", "neighborhood": "Fisherman's Wharf", "michelin_status": "1 Star", "reservation_link": "https://example.com/reserve"
| # | restaurant_id | name | cuisine_type | price_tier | neighborhood | address |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Local Events objects from sftravel.com. All fields typed and schema-versioned.
"title": "Outside Lands Music Festival", "start_date": "2026-08-07", "venue_name": "Golden Gate Park", "event_type": "Festival", "ticket_price_min": 199.0, "organizer": "Another Planet Entertainment"
| # | event_id | title | start_date | end_date | venue_name | neighborhood |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Attractions & Tours objects from sftravel.com. All fields typed and schema-versioned.
"name": "Alcatraz Island Tour", "category": "Landmark", "neighborhood": "Embarcadero", "admission_fee": 45.25, "family_friendly": true, "accessibility_options": "['Wheelchair Accessible']"
| # | attraction_id | name | category | neighborhood | address | duration |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Venues & Meetings objects from sftravel.com. All fields typed and schema-versioned.
"name": "Moscone Center", "max_capacity": 50000, "total_sqft": 700000, "meeting_rooms": 106, "neighborhood": "SoMa", "catering_options": "['In-house', 'Approved List']"
| # | venue_id | name | max_capacity | meeting_rooms | total_sqft | neighborhood |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our pipeline handles the complexity of tourism directories: dynamic pagination, nested taxonomy, and inconsistent date formats.
Capture every hotel, restaurant, and attraction listed across sftravel.com with complete metadata and contact details.
Extract rolling event schedules, venue assignments, and ticketing URLs to maintain accurate local event databases.
Extract latitude, longitude, and neighbourhood classifications for precise mapping and proximity analysis.
Scrape B2B meeting planner data including square footage, room counts, and maximum capacities for corporate events.
Preserve sftravel.com's native taxonomy for cuisine types, accommodation styles, and event categories.
Capture high-resolution image URLs, gallery assets, and promotional video links associated with each listing.
Structure unstructured description text to identify WiFi availability, ADA compliance, and pet-friendly policies.
Monitor directories for new business additions, event date changes, or closed venues with automated diffing.
Compile outbound links, phone numbers, and reservation endpoints for lead generation and CRM enrichment.
Brief in. Clean data out.
Select target directories (e.g., dining, events, hotels) and specify extraction frequency.
We configure Scrapy crawlers to navigate sftravel.com's pagination and taxonomy structures.
Schema validation ensures critical fields like addresses and event dates meet formatting standards.
Structured JSON or Parquet pushed to your S3 bucket or Snowflake warehouse on schedule.
Tourism directories present unique pagination and schema drift challenges. We handle the complexity.
sftravel.com uses dynamic loading for large categories like dining and hotels. We intercept XHR requests to extract raw JSON payloads rather than scraping DOM elements, ensuring zero data loss.
A boutique hotel listing differs vastly from a corporate venue. Our pipeline normalises these variations into a unified schema, applying intelligent defaults for missing fields.
Events are listed in varied formats. We use NLP to parse natural language dates into standard ISO-8601 timestamps.
When listings lack explicit coordinates, our pipeline validates and geocodes street addresses to provide accurate latitude and longitude for downstream mapping.
We maintain state across pipeline runs to flag listings that disappear from the directory, indicating closed businesses or cancelled events.
OTAs and travel startups integrate local event and attraction data to enrich their booking platforms.
Digital concierge services use dining and nightlife directories to provide up-to-date recommendations to hotel guests.
Hospitality vendors extract restaurant and hotel contact details to build targeted outbound sales lists.
Platforms aggregate local happenings to help corporate planners avoid scheduling conflicts with major city events.
Analysts study the density of amenities, restaurants, and attractions to evaluate commercial property valuations.
Transit companies overlay event calendars with venue capacities to forecast localized demand spikes.
"Tourism boards hold the most accurate, curated directories of local commerce. Structured extraction turns this public utility into actionable market intelligence."
Scraping sftravel.com requires handling varied page templates, inconsistent date formatting, and AJAX-loaded directories. DataFlirt normalises this unstructured content into clean, relational datasets so your engineering team can focus on product development, not writing custom parsers for event calendars.
Everything supported by our sftravel.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 deduplication. Playwright handles JavaScript rendering and interaction flows for dynamic directories.
Custom parsers clean inconsistent date formats, address strings, and missing schema fields to ensure uniform dataset output.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About sftravel.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available directory and event information is generally permissible under US law. DataFlirt extracts only public data and does not breach authentication walls.
We can run daily or weekly pipelines to capture new event additions and date changes across the platform.
Yes, we extract all publicly listed contact information, including emails, phone numbers, and website URLs.
Yes. Our Playwright integration or XHR interception handles dynamic pagination and infinite scroll to capture every listing.
If sftravel.com does not provide explicit latitude and longitude, we can integrate third-party geocoding APIs during the pipeline run.
We parse all event dates and times into standard ISO-8601 format to ensure compatibility with your database.
20-minute scoping call. Pilot dataset within the week. Production within two. From comprehensive hospitality directories to rolling event calendars, we build and operate the extraction infrastructure. Tell us your requirements.
