We extract office spaces, retail listings, industrial properties, lease rates, and broker intelligence from 42Floors. 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 Property Listings objects from 42floors.com. All fields typed and schema-versioned.
"property_id": "42F-9821A", "address": "100 Montgomery St", "city": "San Francisco", "state": "CA", "zip_code": "94104", "property_type": "Office", "building_class": "A", "total_sqft": 420000
| # | property_id | address | city | state | zip_code | property_type |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Available Spaces objects from 42floors.com. All fields typed and schema-versioned.
"space_id": "SP-449102", "property_id": "42F-9821A", "floor_number": "12", "suite_number": "1200", "available_sqft": 5400, "lease_rate": 65.0, "lease_type": "Full Service Gross", "space_condition": "Built Out"
| # | space_id | property_id | floor_number | suite_number | available_sqft | lease_rate |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Broker Info objects from 42floors.com. All fields typed and schema-versioned.
"broker_id": "BRK-7732", "first_name": "Jane", "last_name": "Doe", "agency_name": "CBRE", "phone_number": "+1-415-555-0198", "license_number": "DRE-01928374", "profile_url": "https://42floors.com/brokers/jane-doe"
| # | broker_id | first_name | last_name | agency_name | phone_number | email_address |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Building Amenities objects from 42floors.com. All fields typed and schema-versioned.
"property_id": "42F-9821A", "hvac_hours": "Mon-Fri 8AM-6PM", "security_type": "24/7 Manned", "onsite_management": true, "fitness_center": true, "bike_storage": true, "transit_score": 100
| # | property_id | internet_providers | hvac_hours | security_type | onsite_management | fitness_center |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Market Analytics objects from 42floors.com. All fields typed and schema-versioned.
"market_name": "San Francisco", "submarket_name": "Financial District", "total_active_listings": 342, "avg_lease_rate": 62.5, "median_sqft": 4200, "currency": "USD", "scraped_at": "2026-05-12T09:14:00Z"
| # | market_name | submarket_name | total_active_listings | avg_lease_rate | median_sqft | inventory_growth_pct |
|---|---|---|---|---|---|---|
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Our 42Floors pipeline navigates map based searches, intercepts undocumented XHR endpoints, and extracts deep property metadata with full session management and proxy rotation.
Capture address, building class, year built, total square footage, and parking ratios for every office, retail, and industrial property.
Extract asking rates, lease types (NNN, FSG, Modified Gross), and minimum term lengths across all available spaces.
Collect listing agent names, agency affiliations, phone numbers, and profile links to build comprehensive broker directories.
We intercept backend XHR requests powering the map interface to ensure 100% coverage of listings within any geographic bounding box.
Identify sublease opportunities versus direct-to-landlord leases, including sublease expiration dates when available.
Extract high resolution image URLs, floor plan PDFs, and virtual tour links associated with individual spaces or entire buildings.
Capture transit scores, security details, HVAC hours, and onsite facilities like gyms and cafes.
Monitor markets continuously. Our pipeline hashes fields and only emits records when lease rates change or spaces go off market.
Run bulk market exports monthly or configure daily pipelines to catch new listings the moment they are published.
Brief in. Clean data out.
Provide target cities, zip codes, or geographic bounding boxes. We design the extraction schema together.
We configure Scrapy crawlers, map XHR interception, proxy rotation, and session management for 42floors.com.
Schema validation, null-rate checks, lease rate outlier detection, and geographic coverage tests before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting map based real estate data requires precise request engineering. Here is how we build resilient pipelines.
Map based search interfaces limit the number of visible pins. We intercept the underlying XHR requests and programmatically tile geographic bounding boxes to extract every listing without relying on brittle UI automation.
Real estate platforms monitor request velocity and IP reputation. Our crawlers route traffic through US based residential ISP proxies, ensuring uninterrupted access to market data.
Commercial real estate data is notoriously inconsistent. We implement strict normalization rules to handle missing lease rates, variable square footage formats, and unstructured amenity descriptions.
We maintain a hash index of last seen values per space. Subsequent runs only push diffs, reducing storage bloat and downstream processing load when tracking daily market movements.
Every run emits structured logs. We alert on null-rate spikes, missing geographic regions, and schema drift, responding before you notice any data degradation.
Real estate technology platforms aggregate listings to build market intelligence dashboards and predictive pricing models.
Commercial brokerages monitor competing agencies, track active listing volumes, and identify off market trends.
Private equity and REITs analyze lease rate trends and inventory growth across target submarkets to inform acquisition strategies.
Advisors aggregate space availability and historical pricing to negotiate better lease terms for corporate clients.
Economic development teams track commercial vacancy rates and space utilization to inform zoning and infrastructure decisions.
Appraisers feed structured lease comparables and building class data into automated valuation models (AVMs).
"42Floors holds critical supply and pricing signals for commercial real estate, but extracting map based listings at scale requires precision infrastructure."
Most teams underestimate the investment required: reliable 42Floors scraping requires intercepting undocumented XHR endpoints, managing session state across geographic boundaries, and handling strict rate limits. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our 42floors.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 map interactions. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. 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 42floors.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available real estate listings is generally permissible under applicable law. DataFlirt targets only public, non-authenticated property and broker data. We do not extract personal user data or circumvent authentication walls. Clients should review terms of service and consult legal counsel.
We intercept the XHR requests that populate the frontend map interface. By programmatically tiling geographic bounding boxes, we capture all listings in a market without relying on brittle browser automation.
Yes. Every pipeline run produces timestamped snapshots. We maintain a hash index to identify when a lease rate changes, allowing you to track pricing trends over time.
Depending on your requirements, we can configure daily sweeps of target markets or run continuous pipelines to identify new listings within hours of publication.
Yes, we extract publicly listed broker names, agency affiliations, phone numbers, and profile URLs associated with each property or space.
Our smallest packages start at defined geographic markets (e.g., top 10 US metros) with weekly delivery. For national coverage or custom schema requirements, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off market export or a continuous lease rate feed across the US, we scope, build, and operate the pipeline. Tell us what you need.
