Realtor.com Scraper

Extract thousands of property listings from Realtor.com for market research, price analysis, and real estate investment opportunities — for just $2.00 per 1,000 listings. Whether you're tracking home values, analyzing market trends, or building a property database, this scraper delivers clean, structured data through Realtor.com's GraphQL API with support for 30+ search filters.

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What can Realtor.com Scraper do for you?

• Build comprehensive property databases — Extract pricing, beds, baths, square footage, lot size, photos, and listing details from any Realtor.com search.
• Monitor real estate market trends — Track price changes, new listings, sold data, and inventory levels across cities, ZIP codes, or neighborhoods.
• Filter with precision — Apply 30+ search filters including price range, bedrooms, bathrooms, property type, features, keywords, commute time, HOA fees, open houses, and more.
• Search by location or ZIP codes — Search by city/neighborhood (e.g. "Austin, TX") or supply multiple ZIP codes for targeted area coverage.
• Export structured data — All results are delivered as clean JSON ready for analysis in Excel, Google Sheets, Tableau, or any data pipeline.
• Support for active, sold, pending, and contingent listings — Capture current inventory, recent sales, and off-market properties in a single run.

What data can you extract?

Field	Description
🏠 Property ID	Unique Realtor.com property identifier
🔗 Listing URL	Direct link to the Realtor.com listing page
💰 List Price	Current asking price in USD
🛏️ Beds / Baths	Number of bedrooms and bathrooms
📐 Square Feet	Interior square footage
🌳 Lot Size	Lot square footage
📍 Full Address	Street, city, state, ZIP code
📅 List Date	Date the property was listed
🏷️ Property Type	Single family, condo, townhouse, multi-family, etc.
📸 Photos	Primary photo URL and full photo array
🆕 New Construction	Whether the listing is new construction
💲 Price Reduced	Whether the price has been reduced
🏢 Builder / Community	Builder name and community name
🏅 Branding / Agent	Listing brokerage or agent branding
📌 Coordinates	Latitude and longitude

Why use this scraper?

• 📊 Market Research — Analyze pricing trends, inventory levels, and property characteristics across markets.
• 💰 Investment Analysis — Find undervalued properties, track foreclosure listings, and evaluate ROI opportunities.
• 🔔 Price Monitoring — Track price drops, new listings, and market activity in specific neighborhoods.
• 🤖 Automated Data Pipelines — Feed structured property data into CRM systems, dashboards, or machine learning models.

Pricing

• $2.00 per 1,000 listings (dataset items)
• Discounted rates available on Bronze, Silver, and Gold Apify plans — from $1.70 to $1.30 per 1,000 listings
• Actor Start: $0.00005 per run
• No hidden fees or limits on usage.

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How to use Realtor.com Scraper

1. Create an Apify account — Sign up at apify.com if you don't already have one.
2. Open the Realtor.com Scraper — Navigate to Realtor.com Scraper in Apify Console.
3. Configure your search — Enter a city/neighborhood or ZIP codes. Apply optional filters for price, beds/baths, property type, features, and more.
4. Start the scraper — Click "Run" and let the actor extract listings through Realtor.com's GraphQL API.
5. Download your data — Once complete, export the results as JSON, CSV, HTML, or Excel from the dataset.

Input

Field	Type	Required	Description
searchLocation	string	optional	City, neighborhood, or address — e.g. "Austin, TX"
zipCodes	string[]	optional	ZIP codes to search — e.g. ["78702", "78704"]
maxItems	integer	optional	Max listings to scrape (0 = unlimited, default: 50)
sortBy	select	optional	Sort order: relevant, newest, lowest_price, highest_price, open_house_date, recently_reduced, lot_size, photo_count
minPrice	integer	optional	Minimum price in USD
maxPrice	integer	optional	Maximum price in USD
priceReduced	boolean	optional	Only price-reduced listings in last 30 days
builderPromotions	boolean	optional	Only listings with builder promotions
bedrooms	string[]	optional	Filter by bedrooms (studio, 1, 2, 3, 4, 5_plus)
bathrooms	string[]	optional	Filter by bathrooms (1, 2, 3, 4, 5_plus)
propertyTypes	string[]	optional	House, condo, townhouse, multi_family, mobile, land, farm
listingStatus	string[]	optional	active, pending, contingent, sold (default: active)
listingTypes	string[]	optional	existing_homes, foreclosures, new_construction, 55_plus_community, auction
soldWithinMonths	integer	optional	Limit sold search to 1–36 months (default: 6)
tours	string[]	optional	open_house, three_d_tour, virtual_tour
daysOnRealtor	integer	optional	Listings added within N days (2, 7, 14, 21, 30)
minSquareFeet	integer	optional	Minimum square footage
maxSquareFeet	integer	optional	Maximum square footage
minLotSizeSqft	integer	optional	Minimum lot size in sqft
maxLotSizeSqft	integer	optional	Maximum lot size in sqft
minHomeAgeYears	integer	optional	Minimum home age in years
maxHomeAgeYears	integer	optional	Maximum home age in years
maxHoaFeePerMonth	integer	optional	Max HOA fee in USD (50–3000)
garageSpaces	integer	optional	Minimum garage spaces (1, 2, 3)
stories	select	optional	single, multiple
keywords	string[]	optional	e.g. pool, gated, pond, basement, waterfront
features	string[]	optional	50+ interior/exterior/view/community feature tags
commuteAddress	string	optional	Destination for commute-time filtering
commuteMode	select	optional	walking, cycling, transit, driving
maxCommuteMinutes	integer	optional	Max commute from destination (10–60)
searchRadiusMiles	integer	optional	Expand search radius around location
proxyConfiguration	object	optional	Apify proxy settings (residential recommended)

📝 Copy for Use

{
    "searchLocation": "Austin, TX",
    "maxItems": 10,
    "listingStatus": ["active"],
    "minPrice": 150000,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

Output

[

Each listing is returned as a structured JSON object. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

Why Choose This Scraper?

• Affordable: Pay only $2.00 per 1,000 listings scraped, with discounted rates on higher Apify plans.
• Comprehensive: Extract 50+ data fields per listing with 30+ search filters for precise targeting.
• Easy to Use: Simple JSON input — enter a location or ZIP codes, apply optional filters, and run.
• Reliable: Powered by Realtor.com's GraphQL API with residential proxy support for consistent results.

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🙌 Why Buy Through Our Affiliate Link?

• Exclusive Deals: Some providers may offer special discounts or bonuses when you use our link.
• Support Our Work: Each purchase helps us maintain and improve the tools and services we provide.
• No Extra Cost: You pay the same price, but part of it goes to supporting our efforts.

Running via Apify Console

You can run this actor from the Apify Console by providing the necessary input parameters.

Running via API

You can trigger this actor using the Apify API, passing the required input in the request body.

API

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR-APIFY-TOKEN")

run_input = {
    "searchLocation": "Austin, TX",
    "maxItems": 10,
    "listingStatus": ["active"],
    "minPrice": 150000,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

run = client.actor("rigelbytes/realtor-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR-APIFY-TOKEN" });

const runInput = {
    searchLocation: "Austin, TX",
    maxItems: 10,
    listingStatus: ["active"],
    minPrice: 150000,
    proxyConfiguration: {
        useApifyProxy: true,
        apifyProxyGroups: ["RESIDENTIAL"],
    },
};

const run = await client
    .actor("rigelbytes/realtor-scraper")
    .call(runInput);

const { items } = await client
    .dataset(run.defaultDatasetId)
    .listItems();

items.forEach((item) => console.log(item));

cURL

curl "https://api.apify.com/v2/acts/rigelbytes~realtor-scraper/runs?token=YOUR-APIFY-TOKEN" \
  -X POST \
  -H "Content-Type: application/json" \
  -d '{
    "searchLocation": "Austin, TX",
    "maxItems": 10,
    "listingStatus": ["active"],
    "minPrice": 150000,
    "proxyConfiguration": {
      "useApifyProxy": true,
      "apifyProxyGroups": ["RESIDENTIAL"]
    }
  }'

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Understanding Proxies:

When scraping data or browsing anonymously, proxies are essential. They act as intermediaries, masking your original IP address and allowing you to send requests from another location.

Why Use Proxies?

• Avoid IP Blocks: By routing requests through proxies, you prevent the target website from recognizing your IP as a scraper or spammer.
• Access Geo-restricted Content: Proxies let you access content or websites restricted by location.
• Enhance Anonymity: Hide your actual IP, ensuring privacy while scraping or browsing.

Types of Proxies

1. Residential Proxies
   • Real IP addresses provided by ISPs to home users.
   • They mimic regular users, making them harder to detect.
   • Best for: Long-term, undetectable scraping, and avoiding blocks.
2. Data Center Proxies
   • IP addresses from servers in data centers.
   • Faster and cheaper than residential proxies but easier to detect and block.
   • Best for: High-speed scraping, but with a higher risk of detection.
3. Mobile Proxies
   • IPs provided by mobile carriers (3G/4G/5G networks).
   • Very difficult to detect, as they appear as regular mobile users.
   • Best for: Mobile-related scraping or avoiding sophisticated blocks.

Rotating Proxies vs. Straight Proxies

• Rotating Proxies: Every request you send goes through a different proxy, making it harder for websites to detect patterns.
• Straight Proxies: All requests are sent through the same proxy, making it easier to track your IP.

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About Rigel Bytes

Rigel Bytes specializes in web scraping, automation, and data analytics. We help businesses extract and leverage valuable data for informed decision-making.

Contact Us

Ready to unlock the power of data? Reach out to us at (contact@rigelbytes.com) or book an appointment with us to learn more about how we can help you achieve your data goals.

Detailed Data

[
  {
    "propertyId": "9607103106",
    "listingId": "2997598864",
    "url": "https://www.realtor.com/realestateandhomes-detail/31015-Neal-St_Austin_TX_78702_M96071-03106",
    "status": "for_sale",
    "listPrice": 1100000,
    "listDate": "2026-06-24T04:15:09.000000Z",
    "propertyType": "single_family",
    "beds": 4,
    "baths": "2.5+",
    "squareFeet": 2538,
    "lotSquareFeet": 2309,
    "address": "3101.5 Neal St, Austin, TX, 78702",
    "city": "Austin",
    "state": "TX",
    "zipCode": "78702",
    "latitude": 30.265224,
    "longitude": -97.703499,
    "primaryPhotoUrl": "https://ap.rdcpix.com/6e0c453a2d46d2fce84428317a99692dl-m2570498838s.jpg",
    "photoCount": 15,
    "isNewListing": true,
    "isNewConstruction": true
  },
  {
    "propertyId": "8290705068",
    "listingId": "2998220788",
    "url": "https://www.realtor.com/realestateandhomes-detail/1305-Chestnut-Ave_Austin_TX_78702_M82907-05068",
    "status": "for_sale",
    "listPrice": 699000,
    "listDate": "2026-07-07T21:38:34.000000Z",
    "propertyType": "single_family",
    "beds": 3,
    "baths": "2",
    "squareFeet": 1680,
    "lotSquareFeet": 6199,
    "address": "1305 Chestnut Ave, Austin, TX, 78702",
    "city": "Austin",
    "state": "TX",
    "zipCode": "78702",
    "latitude": 30.27584,
    "longitude": -97.715993,
    "primaryPhotoUrl": "https://ap.rdcpix.com/7e964353922d6e12b49d4da29402ffd5l-m1504013876s.jpg",
    "photoCount": 40,
    "isNewListing": true,
    "isNewConstruction": null
  }
]