🏠 pisos.com Scraper

Want to find properties on pisos.com or analyze the Spanish real estate market? This scraper makes it super easy!

Use structured filters (sale/rent, type, location, price, bedrooms) — structured filters work better for AI agents — or paste an input_url straight from your browser once you've already filtered on pisos.com. When input_url is set it overrides the filters below. Either way, the scraper extracts property listings with prices, specs, photos, and contact phones into a CSV or JSON file.

💡 Perfect for...

• Buyers & Investors: Monitor deals across Spanish cities, price bands, and bedroom counts.
• Estate Agencies: Track competitor listings and build lead lists with revealed contact numbers.
• Market Research: Analyze supply and pricing by province, city, or district.
• Data Analysts: Export clean structured data for dashboards and valuation models.
• 🤖 AI Agents: Power bots and OpenClaw workflows with real-time pisos.com listings.
• 📚 RAG Systems: Feed property specs and prices into retrieval pipelines.
• 🔗 AI Workflows: Plug into LangChain, AutoGPT, CrewAI, and similar stacks.

✨ Why you'll love this scraper

• 🔗 Input URL or Filters: Paste a pisos.com search URL (input_url) if you already filtered in the browser, or use structured filters (better for AI agents). input_url always wins when set — leave it empty when you want location and the other filters to apply.
• 🎯 Website-Matched Filters: Listing type, property type, price, bedrooms, bathrooms, area, and sort use the same path slugs as pisos.com.
• 📍 Location Suggest: Free-text location is resolved through the site’s geo suggest (Madrid, Marbella, Chamberí, …).
• 📞 Phones on Listings: Pulls the call-button number when the grid exposes it.
• 🇪🇸 Built for Spain: Covers venta, alquiler, and obra nueva (promociones).

📦 What's inside the data?

For every property listing, you will get:

• Core Details: id, url, transaction, property_type, title, description
• Pricing: price, price_label, price_currency (EUR)
• Specs: area_m2, bedrooms, bathrooms, floor
• Location: location, city, region, country, latitude, longitude
• Contact / Media: phone, image_url

🛠️ Sort options

Use sort_by with the same slugs as on pisos.com:

• (empty) – Relevance (default)
• fecharecientedesde-desc – Newest
• asc / desc – Price low→high / high→low
• hab-desc / hab-asc – Most / fewest bedrooms
• m2-desc / m2-asc – Largest / smallest

🚀 Quick start

Option A — Input URL

1. Open pisos.com, apply filters in the browser, copy the results URL — e.g. https://www.pisos.com/venta/pisos-madrid/desde-100000/hasta-300000/.
2. Paste it into input_url.
3. Set max_properties and click Start.

Option B — Structured filters (better for AI agents)

1. Leave input_url empty.
2. Set listing type, property type, location, and optional price / bedrooms / area / sort.
3. Set max_properties (up to 1000) and click Start.

Export CSV, Excel, or JSON when done.

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Tech details for developers 🧑‍💻

Input Example (filters):

{
  "listing_type": "venta",
  "property_type": "pisos",
  "location": "madrid",
  "price_min": 100000,
  "price_max": 300000,
  "bedrooms": "2",
  "sort_by": "asc",
  "max_properties": 100
}

Input Example (URL override):

{
  "input_url": "https://www.pisos.com/venta/pisos-marbella/desde-200000/hasta-500000/con-2-habitaciones/",
  "max_properties": 50
}

Output Example:

{
  "id": "65024581430.526710",
  "url": "https://www.pisos.com/comprar/piso-numancia28038-65024581430_526710/",
  "transaction": "venta",
  "property_type": "piso",
  "title": "Piso en calle de Ramón Pérez de Ayala",
  "price": 269000,
  "price_label": "269.000 €",
  "price_currency": "EUR",
  "area_m2": 108,
  "bedrooms": 3,
  "bathrooms": 2,
  "floor": "1ª planta",
  "location": "Numancia (Distrito Puente de Vallecas. Madrid Capital)",
  "city": "Madrid Capital",
  "region": "Madrid",
  "country": "ES",
  "latitude": 40.39,
  "longitude": -3.66,
  "phone": "910000000",
  "image_url": "https://fotos.imghs.net/..."
}