We extract residential and commercial listings, price drops, energy ratings, and agency portfolios from Habitaclia. 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 habitaclia.com. All fields typed and schema-versioned.
"listing_id": "9382-104928", "title": "Piso en Eixample, Barcelona", "property_type": "flat", "transaction_type": "sale", "price": 450000.0, "area_sqm": 85, "rooms": 3, "bathrooms": 2
| # | listing_id | title | property_type | transaction_type | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & History objects from habitaclia.com. All fields typed and schema-versioned.
"listing_id": "9382-104928", "current_price": 450000.0, "original_price": 475000.0, "price_drop_pct": 5.2, "price_per_sqm": 5294.11, "community_fees": 120.0, "last_updated": "2026-03-14", "price_timestamp": "2026-05-12T09:14:00Z"
| # | listing_id | current_price | original_price | price_drop_pct | price_per_sqm | community_fees |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Features & Amenities objects from habitaclia.com. All fields typed and schema-versioned.
"listing_id": "9382-104928", "has_elevator": true, "has_pool": false, "has_terrace": true, "has_parking": false, "heating_type": "gas", "air_conditioning": true, "condition": "good"
| # | listing_id | has_elevator | has_pool | has_terrace | has_parking | heating_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Agency Data objects from habitaclia.com. All fields typed and schema-versioned.
"agency_id": "ag-1029", "agency_name": "Finques Barcelona", "contact_phone": "+34 931 234 567", "total_listings": 142, "city": "Barcelona", "province": "Barcelona", "logo_url": "https://habitaclia.com/logos/ag-1029.jpg"
| # | agency_id | agency_name | agency_url | contact_phone | total_listings | address |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location Data objects from habitaclia.com. All fields typed and schema-versioned.
"listing_id": "9382-104928", "province": "Barcelona", "municipality": "Barcelona", "district": "Eixample", "neighborhood": "La Dreta de l'Eixample", "latitude": 41.3934, "longitude": 2.1648, "zip_code": "08009"
| # | listing_id | province | municipality | district | neighborhood | latitude |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Habitaclia scraper handles every layer of the portal: residential listings, commercial spaces, agency details, and historical price drops — with JavaScript rendering and pagination bypass built in.
Title, price, description, sqm, rooms, bathrooms, and high-resolution image URLs captured for every property.
Monitor listing price changes over time to identify motivated sellers and regional market trends.
Extract broker details, contact numbers, and total portfolio sizes across all provinces.
Capture 'obra nueva' project details, delivery dates, and available unit breakdowns.
Extract EPC ratings (A-G) for consumption and emissions to feed ESG compliance models.
Capture province, municipality, district, and exact latitude/longitude where available.
Structured booleans for elevator, pool, terrace, parking, heating, and air conditioning.
Extract data across residential, office, industrial, and land asset classes with specific schemas.
Run continuous pipelines at daily or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide target provinces, municipalities, or property types. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and anti-bot circumvention for habitaclia.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 portals protect their inventory. Here's how we stay resilient — and why teams choose managed infrastructure over DIY.
Habitaclia uses standard web application firewalls. Our crawlers use residential ISP proxies with realistic browser fingerprints and request pacing to avoid geographic blocking.
Search results cap at a certain page depth. We bypass this by bisecting searches using granular price brackets and micro-geographies to ensure total extraction without hitting the limit.
Phone numbers often require interaction or JavaScript execution to reveal. We use Playwright to trigger these elements reliably and capture the unmasked contact details.
Real estate DOM structures vary between standard listings, luxury properties, and new developments. We use resilient fallback chains to ensure consistent schema extraction.
We maintain a hash index of last-seen values per listing. Subsequent runs only push diffs, reducing downstream processing load and storage bloat.
Proptech platforms feed historical pricing and feature data into ML models to predict property values.
Real estate funds correlate asking prices with rental rates to identify high-yield postcodes.
B2B service providers extract agency contact details and portfolio sizes to target high-volume brokers.
Analysts monitor time-on-market and price-drop frequencies to gauge regional demand.
Extract energy performance certificates to audit regional housing stock efficiency.
Real estate portals monitor Habitaclia inventory to identify coverage gaps in their own catalogues.
"Habitaclia holds the definitive record of the Mediterranean real estate market, but extracting structured historical data requires navigating strict pagination limits and dynamic DOM structures."
Most teams underestimate the investment required: reliable real estate scraping requires handling complex search bisections to bypass 50-page limits, executing JavaScript for contact reveals, and maintaining daily selector health. DataFlirt absorbs that complexity so your engineers can focus on the analysis — not the infrastructure.
Everything supported by our habitaclia.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 and interaction flows.
We maintain pools of residential ISP proxies across Spain. Rotation happens per-request to avoid geographic blocking.
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 habitaclia.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible. We target only public listing data and do not extract personal user data or bypass authentication.
We recursively divide searches by geographic polygons and tight price brackets to ensure every property is captured before hitting the page limit.
Yes. We use headless browser sessions to simulate user interaction and reveal masked agency phone numbers.
Full regional refreshes typically run daily or weekly depending on client requirements, completing within a few hours.
Yes. Every pipeline run produces timestamped snapshots. We calculate price deltas between runs to flag motivated sellers.
Our smallest packages start at a defined province or property type with weekly delivery. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off regional dump or a continuous price-monitoring feed — we scope, build, and operate the pipeline. Tell us what you need.
