# Realtor.com Scraper (`datascrapers/realtor-scraper`) Actor

Scrape Realtor.com property listings by location or ZIP code with full search filters. Extract list price, beds and baths, square footage, lot size, photos, property type, HOA fees, and listing status, including active, sold, pending, and contingent listings.

- **URL**: https://apify.com/datascrapers/realtor-scraper.md
- **Developed by:** [Farhan Ali](https://apify.com/datascrapers) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.30 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

**Realtor.com Scraper** creates a structured dataset of property listings collected from [Realtor.com](https://www.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.

```json
{
  "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:

```json
{
  "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:

```json
{ "searchLocation": "Austin, TX" }
```

Advanced request (location search with filters):

```json
{
  "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:

```python
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](https://apify.com/datascrapers/zoopla-scraper)** — UK property listings for cross-market real estate research.
- **[Redfin Scraper](https://apify.com/datascrapers/redfin-scraper)** — US property listings and market signals that can be joined by address or ZIP code.
- **[Apartments Scraper](https://apify.com/datascrapers/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.

# Actor input Schema

## `searchLocation` (type: `string`):

City, neighborhood, or address to search — e.g. "Austin, TX". Optional if zipCodes is provided.

## `zipCodes` (type: `array`):

US ZIP codes to search — e.g. \["78702", "78704"]. Can be used alone or together with Search location.

## `maxItems` (type: `integer`):

Maximum number of listings to scrape (0 = unlimited).

## `sortBy` (type: `string`):

How search results are ordered.

## `minPrice` (type: `integer`):

Minimum list price in USD.

## `maxPrice` (type: `integer`):

Maximum list price in USD.

## `priceReduced` (type: `boolean`):

Only show listings with a price reduction in the last 30 days.

## `builderPromotions` (type: `boolean`):

Only show listings with builder promotions.

## `bedrooms` (type: `array`):

Filter by number of bedrooms. Select multiple options.

## `bathrooms` (type: `array`):

Minimum bathroom count — select one or more.

## `propertyTypes` (type: `array`):

Property types to include.

## `listingStatus` (type: `array`):

Listing activity status filters.

## `listingTypes` (type: `array`):

Special listing categories.

## `soldWithinMonths` (type: `integer`):

When searching sold listings, limit to sales within this many months (1, 3, 6, 12, 24, or 36).

## `tours` (type: `array`):

Filter by open houses and virtual/3D tours.

## `daysOnRealtor` (type: `integer`):

Only listings added within this many days (2, 7, 14, 21, or 30).

## `minSquareFeet` (type: `integer`):

Minimum interior square footage.

## `maxSquareFeet` (type: `integer`):

Maximum interior square footage.

## `minLotSizeSqft` (type: `integer`):

Minimum lot size in square feet.

## `maxLotSizeSqft` (type: `integer`):

Maximum lot size in square feet.

## `minHomeAgeYears` (type: `integer`):

Minimum age of the home in years.

## `maxHomeAgeYears` (type: `integer`):

Maximum age of the home in years.

## `maxHoaFeePerMonth` (type: `integer`):

Maximum monthly HOA fee in USD (50–3000).

## `garageSpaces` (type: `integer`):

Minimum number of garage spaces (1, 2, or 3).

## `stories` (type: `string`):

Number of stories.

## `keywords` (type: `array`):

Keyword filters such as pool, gated, pond, basement, waterfront.

## `features` (type: `array`):

Interior, exterior, view, and community feature tags.

## `commuteAddress` (type: `string`):

Destination address for commute-time filtering.

## `commuteMode` (type: `string`):

Transportation mode for commute filter.

## `maxCommuteMinutes` (type: `integer`):

Maximum commute time from the destination address (10–60).

## `searchRadiusMiles` (type: `integer`):

Expand search radius around the location in miles.

## `proxyConfiguration` (type: `object`):

Apify proxy settings — residential proxies recommended.

## Actor input object example

```json
{
  "searchLocation": "Austin, TX",
  "zipCodes": [
    "78702"
  ],
  "maxItems": 50,
  "sortBy": "relevant",
  "priceReduced": false,
  "builderPromotions": false,
  "listingStatus": [
    "active"
  ],
  "soldWithinMonths": 6,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

## `listings` (type: `string`):

Scraped property listings

## `runStats` (type: `string`):

Run metadata including recordsScraped and timestamps

## `input` (type: `string`):

Copy of the input used for this run

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchLocation": "Austin, TX",
    "zipCodes": [
        "78702"
    ],
    "maxItems": 50,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("datascrapers/realtor-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchLocation": "Austin, TX",
    "zipCodes": ["78702"],
    "maxItems": 50,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("datascrapers/realtor-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchLocation": "Austin, TX",
  "zipCodes": [
    "78702"
  ],
  "maxItems": 50,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call datascrapers/realtor-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datascrapers/realtor-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/hVhz4nXHWH9elFwX3/builds/rSghRli4myzC41OBS/openapi.json