Realtor.com Property Scraper

Scrape Realtor.com listings, full property details, agent info, mortgage estimates, and search-box autocomplete suggestions — all from one Actor. Backed by realtyapi.io's real-time Realtor API.

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What you can do

Section	What it does	Input format
🏠 Property Details	Full details for a specific listing	property_id digits, Realtor.com listing URL, or full street address — auto-detected per row
🔎 Search Listings	Paginated search with filters	location string, ZIP, lat,lng,radius_mi, polygon (lon lat,lon lat,...), or Realtor.com search URL
🔍 Autocomplete	Search-box suggestions (cities, ZIPs, neighborhoods, schools, addresses)	partial query string
👤 Agent Lookup	Agent name, office, profile URL	fulfillment_id (found in any details/search response under advertisers[].fulfillment_id)
💰 Mortgage Calculator	Monthly payment + breakdown	price or price,downPayment,rate,term

You can fill any combination of sections in a single run — leave the others empty.

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Output

Each listing / property / agent / mortgage / autocomplete suggestion is pushed as one dataset row, flattened to friendly columns plus a Raw column with the original JSON.

Mode	Input Given	Property ID	Status	Price	Beds	Baths	Sqft	Street	City	State	Zip	Agent Name	Listing URL	Raw
search/bylocation	Austin, TX (p1)	8873523070	for_sale	588888	3	2.5+	3066	13902 Panorama Dr	Austin	TX	78732	Elena Licari	https://www.realtor.com/...	{...}
details/byid	8955838462	8955838462	for_sale	240000	3	2.5	1193	9504 Quail Village Ln	Austin	TX	78758	Carolina Aceituno	https://www.realtor.com/...	{...}

Plus: Listing ID, Lot Sqft, Year Built, Property Type, Latitude, Longitude, Days on Market, List Date, Photos (cover URL), Photo Count, Agent Fulfillment ID, Office Name.

For nested/large fields (full photo arrays, schools, tax history, all phones, etc.) the complete upstream JSON is in the Raw column.

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Sample input

{
    "property_inputs": [
        "8955838462",
        "https://www.realtor.com/realestateandhomes-detail/9504-Quail-Village-Ln_Austin_TX_78758_M89558-38462",
        "166 W 22nd St Unit 1D, New York, NY 10011"
    ],
    "search_inputs": ["Austin, TX", "78758", "30.4108,-97.7177,2"],
    "searchType": "For_Sale",
    "propertyType": "House,Condo",
    "priceRange": "min:300000,max:900000",
    "bedsRange": "min:2",
    "sortOrder": "Newest",
    "pages": 2,
    "resultCount": 50,

    "autocomplete_inputs": ["Brooklyn"],
    "agent_inputs": ["472555"],
    "mortgage_inputs": ["525000", "525000,105000,0.065,30"]
}

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Search filters (apply to all search_inputs)

• searchType — For_Sale | For_Rent | Sold (or comma-combined like For_Sale,Sold)
• propertyType — comma list of House, Condo, Townhome, Multi_Family, Mobile, Farm, Land, Co-op
• priceRange / bedsRange / bathsRange / sqftRange — min:X | max:Y | min:X,max:Y (baths support 2.5)
• sortOrder — Recommended, Newest, Oldest, Price_High_to_Low, Price_Low_to_High, Square_Feet, Lot_Size, Beds, Baths, Most_Recently_Sold, Open_House_Date
• pages — how many pages to fetch (1–50). Each page = resultCount listings.
• resultCount — 1–200 per page, default 50
• newConstruction / foreclosure — any | true (only) | false (exclude)
• openHouse — true to keep only listings with an upcoming open house
• keywords — free-text, comma-separated (e.g. pool,fireplace,granite countertops)
• daysOnMarketMax — only listings within last N days

Filters apply to every search_inputs row in the run.

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Pricing

Pay per result — you only pay for dataset items the Actor pushes. Failed inputs return a row with Status: ERROR: ... and are billed the same as a successful row.

To cap spend, set Max paid dataset items on the run page.

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Tips

• Need just one property? Use the property_inputs section — auto-detects property_id, URL, or address.
• Pull all listings in a city? Use search_inputs: ["City, ST"] and crank pages (each page is up to 200 results).
• Use a lat/lng circle? Format: 30.4108,-97.7177,2 (last value is radius in miles).
• Polygon? lon lat,lon lat,lon lat,... — note longitude first (GeoJSON convention).
• Resolve a Realtor.com URL? Drop a search or detail URL straight into the matching section — both byurl modes parse the URL into the right call internally.