Realtor.com Scraper

Realtor.com Scraper creates a structured dataset of property listings collected from Realtor.com, the US real estate portal. Each dataset item represents one property and can include list price, beds and baths, square footage, lot size, photos, property type, coordinates, and listing status. Query the source by location or ZIP code with 30+ search filters, control the result limit with maxItems, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or other supported formats.

Dataset at a glance

Property	Value
Source	realtor.com (United States)
Record unit	One property listing
Input methods	Location (searchLocation) or ZIP codes (zipCodes) with search filters
Main identifiers	propertyId, listingId
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML, HTML (Apify dataset exports)
Update model	Fresh records per Actor run
Pricing	$2 per 1,000 listings

Coverage and available records

The Actor collects properties from public Realtor.com search results using a location or ZIP-code entry point:

• Location-based: Pass a city, neighborhood, or address (for example "Austin, TX") in searchLocation.
• ZIP-code-based: Pass one or more US ZIP codes (for example ["78702", "78704"]) in zipCodes, alone or combined with a location.

Supported record types and limits:

• Listing-level records are always collected: property ID, listing ID, URL, status, list price, list date, property type, beds, baths, square feet, lot size, address, coordinates, primary photo, and photo count.
• Status filters: listingStatus supports active, pending, contingent, and sold listings (default active).
• Result cap: maxItems limits the number of listings collected (0 means unlimited; the default is 50).
• Filters: 30+ filters for price, beds, baths, property type, features, keywords, commute time, HOA fees, open houses, square footage, lot size, home age, and more.

Known exclusions: each run captures page state at run time (no historical snapshots); fields the listing does not expose (for example isNewConstruction) are returned as null.

Data dictionary

Field names below match dataset record JSON properties exactly.

Field	Type	Nullable	Description	Example
propertyId	string	No	Realtor.com property identifier; best stable deduplication key	9607103106
listingId	string	No	Realtor.com listing identifier	2997598864
url	string	No	Listing detail URL	https://www.realtor.com/realestateandhomes-detail/...
status	string	No	Listing status	for_sale
listPrice	number	Yes	Current list price in USD	1100000
listDate	string	Yes	Date listed (ISO 8601)	2026-06-24T04:15:09.000000Z
propertyType	string	Yes	Property type	single_family
beds	number	Yes	Number of bedrooms	4
baths	string	Yes	Number of bathrooms (may include +)	2.5+
squareFeet	number	Yes	Interior square footage	2538
lotSquareFeet	number	Yes	Lot size in square feet	2309
address	string	Yes	Full address	3101.5 Neal St, Austin, TX, 78702
city	string	Yes	City	Austin
state	string	Yes	State	TX
zipCode	string	Yes	ZIP code	78702
latitude	number	Yes	Map latitude	30.265224
longitude	number	Yes	Map longitude	-97.703499
primaryPhotoUrl	string	Yes	Primary photo URL	https://ap.rdcpix.com/...
photoCount	number	Yes	Number of photos	15
isNewListing	boolean	Yes	Whether the listing is new	true
isNewConstruction	boolean	Yes	Whether it is new construction	true

Example dataset record

Real record produced with a location search (searchLocation: "Austin, TX"), active listings, minimum price $150,000.

{
  "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
}

The record above was produced with this input:

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

Query and input reference

Input	Type	Required	Default	Accepted values	Description
searchLocation	string	No*	Austin, TX	City, neighborhood, or address	Location search
zipCodes	array (stringList)	No*	["78702"]	US ZIP codes	ZIP-code search, alone or with location
maxItems	integer	No	50	0 (unlimited) or positive integer	Maximum listings to collect
sortBy	string	No	relevant	relevant, newest, lowest_price, highest_price, open_house_date, recently_reduced, lot_size, photo_count	Sort order
minPrice / maxPrice	integer	No	—	USD	Price range
priceReduced	boolean	No	false	true / false	Price reduced in last 30 days
builderPromotions	boolean	No	false	true / false	Builder promotions only
bedrooms	array	No	—	studio, 1, 2, 3, 4, 5_plus	Bedroom filter
bathrooms	array	No	—	1, 2, 3, 4, 5_plus	Bathroom filter
propertyTypes	array	No	—	house, condo, townhouse, multi_family, mobile, land, farm	Home type
listingStatus	array	No	["active"]	active, pending, contingent, sold	Listing activity status
listingTypes	array	No	—	existing_homes, foreclosures, new_construction, 55_plus_community, auction	Special listing categories
soldWithinMonths	integer	No	6	1, 3, 6, 12, 24, 36	Limit sold search
tours	array	No	—	open_house, three_d_tour, virtual_tour	Open house and tour filters
daysOnRealtor	integer	No	—	2, 7, 14, 21, 30	Listed within N days
minSquareFeet / maxSquareFeet	integer	No	—	sqft	Interior square footage range
minLotSizeSqft / maxLotSizeSqft	integer	No	—	sqft	Lot size range
minHomeAgeYears / maxHomeAgeYears	integer	No	—	years	Home age range
maxHoaFeePerMonth	integer	No	—	USD (50–3000)	Max monthly HOA fee
garageSpaces	integer	No	—	1, 2, 3	Minimum garage spaces
stories	string	No	—	single, multiple	Number of stories
keywords	array	No	—	Free text (e.g. pool, waterfront)	Keyword filters
features	array	No	—	basement, pool, waterfront, and 40+ more	Home feature tags
commuteAddress	string	No	—	Address	Commute destination
commuteMode	string	No	—	walking, cycling, transit, driving	Commute transport mode
maxCommuteMinutes	integer	No	—	10–60	Max commute minutes
searchRadiusMiles	integer	No	—	miles	Expand search radius
proxyConfiguration	object	No	Apify proxy, RESIDENTIAL group	Apify proxy groups or custom proxies	Residential proxies are recommended

* Provide either searchLocation or zipCodes — at least one source is required.

Minimal request:

{ "searchLocation": "Austin, TX" }

Advanced request (location search with filters):

{
  "searchLocation": "Austin, TX",
  "listingStatus": ["active"],
  "minPrice": 250000,
  "maxPrice": 900000,
  "bedrooms": ["3", "4"],
  "bathrooms": ["2"],
  "propertyTypes": ["house"],
  "features": ["pool", "hardwood_floors"],
  "maxItems": 500,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Retrieve the data through the API

The Actor runs on the Apify platform, so there is no server to host and no crawling infrastructure to maintain.

1. Start the Actor with a JSON input (console or API).
2. Wait for the run to finish, or use a synchronous endpoint if you want the response inline.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset.

Python example:

from apify_client import ApifyClient

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

run_input = {
    "searchLocation": "Austin, TX",
    "maxItems": 10,
    "listingStatus": ["active"],
}

run = client.actor("datascrapers/realtor-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["propertyId"], item["listPrice"], item["address"])

Apify generates ready-to-run Python, JavaScript, and cURL examples on the Actor's API tab. Do not put a real API token in shared code or URLs.

Data quality and record handling

• Nullability: fields the listing does not expose (for example isNewConstruction or listPrice) are returned as null rather than fabricated.
• Source changes: Realtor.com page structure and values can change; unreadable fields are returned as null.
• Deduplication: each run appends fresh records; the Actor does not deduplicate listings across runs. Use propertyId as the stable key and filter repeated runs against previously stored IDs.
• Rate limits: Realtor.com can rate-limit automated traffic; residential proxies are recommended for consistent coverage.
• Normalization: listPrice is a numeric USD value; baths may include a + suffix (for example 2.5+); listDate is an ISO 8601 timestamp.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL / Supabase	Dataset API poll or webhook consumer	Store US property inventory with price history
Google Sheets	Apify Google Sheets integration	Share market shortlists with agents
BI tools (Looker, Tableau)	Scheduled export via Apify scheduler	Price-per-square-foot benchmarking
S3 / cloud storage	Scheduled export + integration	Archival of market snapshots

Pricing and cost examples

The Actor uses pay-per-event pricing with a single chargeable result event:

Event	Trigger	Rate
Result	Every listing record pushed to the dataset	$2 per 1,000 listings

Example costs:

Records	Configuration	Estimated base cost
1,000	Active listings	$2.00
10,000	Active listings	$20.00
50,000	Active listings	$100.00

Apify paid plans reduce the per-1,000 rate. Compute units consumed by the run are billed by your Apify plan. Estimates depend on the verified pricing model and the options selected for the run.

Limitations and responsible data use

• The Actor collects publicly accessible data from Realtor.com pages only.
• Field availability depends on what Realtor.com renders at run time; some values can be null or missing, and site changes can alter fields.
• The Actor does not provide historical snapshots unless you store them yourself.
• Large runs require residential proxies; without them, coverage may degrade due to rate limiting.
• You are responsible for compliance with Realtor.com's terms of service, applicable privacy law, and any contractual obligations before using the data.

Dataset questions

What does one dataset item represent?

One property listing from Realtor.com, with its price, size, location, photos, and listing status in a single record.

Which field should I use as a unique identifier?

propertyId is the stable Realtor.com property identifier and is the recommended deduplication key. listingId is a reasonable secondary key tied to a specific listing.

Are fields nullable or conditional?

Yes. Fields the listing does not expose are returned as null (for example isNewConstruction). baths is a string and may include a + suffix, so treat it as text rather than a number.

Can I retrieve the records as CSV or JSON?

Yes. The dataset can be exported as JSON, CSV, Excel, XML, or HTML from the Apify Console, and queried through the Dataset API.

Does the Actor return historical data?

No. Each run captures the state of the pages at run time. To track price changes over time, schedule repeated runs and store the outputs yourself.

What counts as a billable result?

A single pay-per-event charge applies: $2 per 1,000 listing records pushed to the dataset. There are no separate detail or contact charges for this Actor.

Which listing statuses can I filter?

listingStatus supports active, pending, contingent, and sold. Use soldWithinMonths to limit sold listings to recent sales, and listingTypes for foreclosures, new construction, and other categories.

Related datasets from Data Scrapers

• Zoopla Scraper — UK property listings for cross-market real estate research.
• Redfin Scraper — US property listings and market signals that can be joined by address or ZIP code.
• Apartments Scraper — US rental listings for comparative housing market analysis.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.