We extract property listings, pricing histories, agent portfolios, and regional trends from pisos.com. 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 pisos.com. All fields typed and schema-versioned.
"property_id": "pisos-3829104", "transaction_type": "sale", "price": 345000, "province": "Madrid", "rooms": 3, "surface_sqm": 110, "has_elevator": true
| # | property_id | transaction_type | property_type | price | currency | province |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Valuation objects from pisos.com. All fields typed and schema-versioned.
"property_id": "pisos-3829104", "current_price": 345000, "original_price": 360000, "price_drop_pct": 4.1, "price_per_sqm": 3136, "community_fees": 120, "listed_date": "2023-09-14"
| # | property_id | current_price | original_price | price_drop_pct | price_per_sqm | community_fees |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Agent Data objects from pisos.com. All fields typed and schema-versioned.
"agent_id": "ag-9921", "agency_name": "Inmobiliaria Madrid Centro", "total_listings": 142, "active_sales": 98, "active_rentals": 44, "contact_phone": "+34 91 123 45 67", "rating": 4.6
| # | agent_id | agency_name | agency_url | contact_phone | contact_name | total_listings |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for New Developments objects from pisos.com. All fields typed and schema-versioned.
"development_id": "dev-441", "name": "Residencial Las Rozas", "developer_name": "Metrovacesa", "status": "under_construction", "min_price": 420000, "total_units": 45, "delivery_date": "Q4 2025"
| # | development_id | name | developer_name | status | delivery_date | min_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Amenities objects from pisos.com. All fields typed and schema-versioned.
"property_id": "pisos-3829104", "heating_type": "natural gas", "air_conditioning": true, "parking_included": true, "terrace_sqm": 12, "pool": false, "condition": "good"
| # | property_id | heating_type | air_conditioning | parking_included | parking_price | terrace_sqm |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our pisos.com scraper handles every layer of the platform: property listings, dynamic pricing, agent portfolios, and new developments, with JavaScript rendering and anti-bot circumvention built in.
Price, surface area, rooms, bathrooms, floor level, and elevator status across all Spanish provinces.
Track original listing prices against current prices to calculate discount percentages and market cooling signals.
Extract complete new development projects, including developer details, unit availability, and expected delivery dates.
Map total listing volume, sales vs rentals ratios, and contact details for every real estate agency on the platform.
Capture province, municipality, district, neighborhood, and exact coordinates where published by the agent.
Extract mandatory Spanish energy performance ratings (A-G) for emissions and consumption.
Monitor organic ranking positions for specific neighborhoods or property types across paginated SERPs.
Hash-based diffing ensures you only receive updates when a property price changes or a listing goes offline.
Track fast-moving rental markets in Madrid and Barcelona with hourly pipeline executions.
Brief in. Clean data out.
Provide target provinces, property types (venta/alquiler), or specific agency URLs. We design the extraction schema together.
We configure Scrapy crawlers, handle IP rotation for Spanish residential proxies, and bypass bot protection.
Schema validation, null-rate checks on critical fields like price and sqm, and sample data review before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Real estate portals actively block automated extraction to protect their inventory. Here is how we maintain pipeline stability.
European real estate portals aggressively block datacenter IPs. We route all requests through Spanish residential ISP proxies to blend with legitimate local traffic.
Many search interfaces on pisos.com rely on dynamic AJAX loading. We execute full Playwright sessions to trigger lazy-loaded properties and map pins.
Surface area (metros construidos vs útiles), floor levels (bajo, entresuelo, ático), and energy ratings are normalised into consistent data types.
Real estate inventory turns over rapidly. We maintain state across runs to flag properties that have been delisted, sold, or rented.
To avoid triggering volumetric blocks, we distribute extraction tasks across thousands of IPs, strictly adhering to realistic request delays.
Feed current listing prices, price per sqm, and property features into algorithmic valuation models for the Spanish market.
Track supply volume and average asking prices across different provinces and municipalities to identify macro trends.
Monitor price drops and days-on-market metrics to identify motivated sellers and high-yield rental investment opportunities.
Real estate agencies track competitor portfolios, listing volumes, and regional market share.
Aggregate listings for meta-search engines, mortgage calculators, and property management platforms.
Universities and municipal planners analyse housing affordability, rental stock, and energy efficiency trends.
"Pisos.com holds the most accurate pulse on Spanish real estate, but extracting that intelligence requires circumventing aggressive anti-bot layers and dynamic map interfaces."
Most teams waste engineering cycles trying to bypass CAPTCHAs and parse inconsistent Spanish address formats. DataFlirt absorbs that complexity. We handle the residential proxy rotation, JavaScript execution, and schema normalization so your data scientists can focus on building valuation models and market analysis.
Everything supported by our pisos.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 for dynamic map views and lazy-loaded property images.
We maintain pools of residential ISP proxies across Spain and the EU. Rotation happens per-request to bypass aggressive geo-fencing and rate limits.
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 pisos.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available real estate listings is generally permissible under EU law, provided it does not extract personal data (GDPR) or breach copyright. DataFlirt targets only public property facts and agent business details. We do not extract private user data or circumvent authentication walls.
We use Spanish residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. This prevents the IP bans and CAPTCHAs common on European real estate sites.
Pisos.com often hides the exact street number until a buyer contacts the agent. We extract the highest resolution location data publicly available, typically the street name, district, and municipality.
Rental markets move fast. We can configure pipelines to run hourly or daily on specific high-velocity markets like Madrid or Barcelona, ensuring you capture listings before they are rented and delisted.
Yes. When a property price is reduced, pisos.com often displays the original price. We capture both the current and original price to calculate the exact discount percentage.
Our smallest packages start at a defined regional scope with weekly delivery. For national coverage across all of Spain, we price based on volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of Madrid rentals or a full historical snapshot of Spanish new builds, we scope, build, and operate the pipeline. Tell us what you need.
