We extract coworking venues, meeting room rates, office availability, and amenity lists from LiquidSpace. 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 Venue Data objects from liquidspace.com. All fields typed and schema-versioned.
"venue_id": "v-83921", "name": "WeWork - Salesforce Tower", "city": "San Francisco", "state": "CA", "rating": 4.8, "review_count": 142, "workspace_count": 18, "latitude": 37.7899, "longitude": -122.3969
| # | venue_id | name | address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Workspaces objects from liquidspace.com. All fields typed and schema-versioned.
"workspace_id": "ws-49210", "type": "Meeting Room", "capacity": 12, "price_hourly": 75.0, "price_daily": 450.0, "currency": "USD", "sqft": 250, "description": "Boardroom with video conferencing"
| # | workspace_id | venue_id | name | type | capacity | price_hourly |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Complete list of extractable fields for Pricing & Availability objects from liquidspace.com. All fields typed and schema-versioned.
"workspace_id": "ws-49210", "date": "2026-06-15", "is_available": true, "dynamic_price": 85.0, "minimum_term": "1 hour", "cancellation_policy": "24 hours", "scraped_at": "2026-05-12T10:15:00Z"
| # | workspace_id | date | available_slots | is_available | dynamic_price | minimum_term |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Amenities objects from liquidspace.com. All fields typed and schema-versioned.
"venue_id": "v-83921", "has_wifi": true, "has_whiteboard": true, "has_coffee": true, "has_reception": true, "access_hours": "24/7", "ada_compliant": true
| # | venue_id | has_wifi | has_parking | has_whiteboard | has_coffee | has_printing |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Reviews objects from liquidspace.com. All fields typed and schema-versioned.
"review_id": "r-992103", "venue_id": "v-83921", "rating": 5, "review_text": "Excellent natural light and fast WiFi.", "date_posted": "2026-04-20", "verified_booking": true, "reviewer_name": "Sarah J."
| # | review_id | venue_id | reviewer_name | rating | review_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our LiquidSpace scraper maps the entire flexible workspace ecosystem: venue details, granular workspace pricing, availability calendars, and amenities — fully managed and delivered to your warehouse.
Capture address, host details, aggregate ratings, operating hours, and geo-coordinates for every coworking space and private office.
Extract individual meeting rooms, hot desks, dedicated desks, and private suites nested under each venue.
Capture hourly, daily, and monthly rates alongside minimum term requirements and deposit rules.
Scrape real-time booking slots and date-specific availability to model occupancy rates and demand.
Convert unstructured amenity lists into normalised boolean fields: WiFi, parking, whiteboards, printing, and A/V equipment.
Provide bounding boxes, zip codes, or city names. We execute map-based searches to ensure complete regional coverage.
Extract user reviews, star ratings, and host responses to gauge tenant satisfaction and facility quality.
Track host portfolios, response times, and cancellation policies across multiple managed locations.
Run daily or hourly pipelines that only push price changes and availability updates, reducing warehouse compute costs.
Brief in. Clean data out.
Provide target cities, zip codes, or specific venue URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and map-viewport manipulation for liquidspace.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Real estate platforms use map-based pagination and heavy JavaScript to deter scraping. Here is how we maintain pipeline stability.
LiquidSpace relies on map viewports rather than traditional pagination. We programmatically divide target cities into coordinate grids and manipulate the map bounds via Playwright to ensure 100% coverage without missing clustered venues.
Availability calendars and time-slot pricing are loaded asynchronously via XHR after the page renders. We use Playwright to intercept these API responses and hydrate the DOM, capturing real-time occupancy data.
Frequent searches from data centre IPs trigger rate limits and CAPTCHAs. We route all requests through ISP-grade residential proxies with geographic targeting matching the search radius.
Venue layouts vary depending on the host and workspace type. We use multi-layer XPath and CSS fallback chains to ensure pricing and amenity fields are extracted consistently regardless of template variations.
For daily availability tracking, we maintain a hash index of last-seen values per workspace. Subsequent runs only push diffs — giving you a clean changelog of bookings and price adjustments.
Flexible workspace operators monitor competitor pricing, amenity offerings, and regional expansion to optimise their own portfolios.
Enterprise teams track daily and monthly rates across cities to budget for hybrid work models and distributed teams.
Revenue managers ingest hourly and daily rate fluctuations to train algorithmic pricing models for their own venues.
Operators track availability calendars across the platform to estimate market-wide occupancy rates and adjust supply.
Consultancies map the density of flexible workspaces against transit hubs to analyse commercial real estate trends.
Private equity firms track venue growth, review sentiment, and pricing power to evaluate investments in the coworking sector.
"Flexible workspace pricing changes daily based on occupancy. You cannot model commercial real estate trends without querying the actual booking calendars."
Extracting data from LiquidSpace requires navigating map-based search, asynchronous calendar loading, and strict rate limits. DataFlirt manages the proxy rotation, JavaScript rendering, and geo-spatial pagination so your team receives clean, structured pricing data directly in your warehouse.
Everything supported by our liquidspace.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 geo-grid generation. Playwright handles JavaScript rendering, map interactions, and calendar API interception.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required to prevent rate limiting during map searches.
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 liquidspace.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from LiquidSpace is generally permissible under applicable law. DataFlirt targets only public, non-authenticated venue, pricing, and availability data. We do not extract personal data, circumvent authentication walls, or violate GDPR. Clients should review LiquidSpace's ToS and consult legal counsel for specific use cases.
We programmatically divide target regions into geographic bounding boxes. Our Playwright instances manipulate the map viewport to load all venues within each grid, ensuring no locations are missed due to clustering limits.
Yes. We intercept the XHR requests that populate the booking calendars to extract available time slots, minimum term requirements, and dynamic pricing for specific dates.
Yes. We can extract venue data across any city or country supported by LiquidSpace, using localised proxies to ensure accurate currency and regional pricing.
Our smallest packages start at a defined city list (e.g., top 50 US metros) with weekly delivery. For continuous daily availability tracking, we price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 50 venues or 3 cities as part of the pre-engagement scoping process — so you can validate schema fit, field completeness, and data quality before signing any contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off venue catalogue dump or continuous availability tracking across major metros — we scope, build, and operate the pipeline. Tell us what you need.
