# Realtyrac Parser Spider (`getdataforme/realtyrac-parser-spider`) Actor

The Realtyrac Parser Spider efficiently extracts detailed property data from RealtyTrac listings, ideal for market analysis and business automation....

- **URL**: https://apify.com/getdataforme/realtyrac-parser-spider.md
- **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community)
- **Categories:** Agents, E-commerce, Other
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $9.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## Realtyrac Parser Spider

### Introduction

The Realtyrac Parser Spider is designed to efficiently extract detailed property information from RealtyTrac listings. This actor is ideal for users seeking comprehensive real estate data for market analysis, competitive intelligence, and business automation.

### Features

- **Comprehensive Data Extraction**: Retrieves detailed property information including price, type, size, and historical data.
- **High Data Quality**: Ensures accurate and up-to-date information from RealtyTrac.
- **Performance Efficiency**: Optimized for fast and reliable data scraping.
- **Customizable Inputs**: Easily configure URLs for targeted data extraction.
- **Versatile Output Formats**: Export data in JSON, CSV, or Excel formats.
- **User-Friendly Interface**: Simple setup and monitoring via the Apify platform.
- **Scalable Solution**: Suitable for both small-scale and large-scale data needs.

### Input Parameters

| Parameter | Type   | Required | Description                                      | Example                                                                 |
|-----------|--------|----------|--------------------------------------------------|-------------------------------------------------------------------------|
| Urls      | Array  | Yes      | List of URLs to scrape from RealtyTrac.          | `["https://www.realtytrac.com/p/aspen-ave-california-city-ca-93505-25287085/"]` |

### Example Usage

#### Example Input JSON

```json
{
  "Urls": [
    "https://www.realtytrac.com/p/aspen-ave-california-city-ca-93505-25287085/"
  ]
}
```

#### Example Output JSON

```json
[
  {
    "URL": "https://www.realtytrac.com/p/aspen-ave-california-city-ca-93505-25287085/",
    "source": "realtytrac",
    "property_id": "25287085",
    "listing_url": "https://www.era.com/property/detail/ca/california-city/10632-aspen-ave/lid-P00800000GzJSb39NzitWZWPkYjKipr7NKrdKAM3",
    "title": "10632 Aspen Ave, California City, CA 93505 | RealtyTrac",
    "property_type": "Single Family Residence",
    "price": 285000,
    "bedrooms": 4,
    "bathrooms": 2,
    "square_footage": 1618,
    "lot_size": 10018,
    "year_built": 1989,
    "street_address": "10632 ASPEN AVE",
    "city": "CALIFORNIA CITY",
    "state": "California",
    "zip_code": "93505",
    "county": "Kern",
    "neighborhood": "2226",
    "parking_spaces": null,
    "parking_type": null,
    "heating": "Yes",
    "cooling": "Package",
    "num_stories": 1,
    "has_fireplace": true,
    "has_pool": false,
    "property_tax": 3206.43,
    "tax_assessed_value": 250000,
    "price_per_sqft": 186.14,
    "image_urls": [
      {
        "desktop": "http://maps.googleapis.com/maps/api/streetview?size=640x480&return_error_code=true&sensor=false&client=gme-nationsinfocorp1&location=10632+ASPEN+AVE%2CCALIFORNIA+CITY%2CCA%2C93505&signature=n1ze4jor-my4YOFT0QGYtTQjR-g"
      }
    ],
    "bing_photo_url": "https://dudtfne5hk5fn.cloudfront.net/null",
    "listing_date": "2025-08-27",
    "last_updated_date": "2026-04-21",
    "property_status": {
      "listedForSale": true,
      "isNew": false,
      "offMarketLast6mo": false
    },
    "occupancy_status": "Owner Occupied",
    "parcel_number": "210-193-05-00-3",
    "latitude": 35.124698,
    "longitude": -117.938467,
    "sale_history": [
      {
        "recordingDate": 1761868800000,
        "status": "Sold",
        "amount": 304000,
        "buildingSquarefeet": 1618,
        "pricePerSqFt": 188
      },
      {
        "recordingDate": 1749427200000,
        "status": "Sold",
        "amount": 182500,
        "buildingSquarefeet": 1618,
        "pricePerSqFt": 113
      }
    ],
    "tax_history": [
      {
        "year": 2020,
        "taxAmount": 1661.47,
        "landAmount": 10075,
        "improvementAmount": 117376,
        "assessment": 127451
      },
      {
        "year": 2019,
        "taxAmount": 1658.42,
        "landAmount": 9878,
        "improvementAmount": 115075,
        "assessment": 124953
      },
      {
        "year": 2018,
        "taxAmount": 1564.96,
        "landAmount": 5000,
        "improvementAmount": 112000,
        "assessment": 117000
      },
      {
        "year": 2017,
        "taxAmount": 1421.88,
        "landAmount": 5000,
        "improvementAmount": 95000,
        "assessment": 100000
      },
      {
        "year": 2016,
        "taxAmount": 1146.24,
        "landAmount": 5000,
        "improvementAmount": 79000,
        "assessment": 84000
      },
      {
        "year": 2015,
        "taxAmount": 1079.51,
        "landAmount": 19000,
        "improvementAmount": 58000,
        "assessment": 77000
      },
      {
        "year": 2014,
        "taxAmount": 863.68,
        "landAmount": 5000,
        "improvementAmount": 55000,
        "assessment": 60000
      },
      {
        "year": 2013,
        "taxAmount": 646.84,
        "landAmount": 3000,
        "improvementAmount": 38300,
        "assessment": 41300
      },
      {
        "year": 2012,
        "taxAmount": 622.05,
        "landAmount": 6000,
        "improvementAmount": 30400,
        "assessment": 36400
      }
    ],
    "estimated_rental": 2174,
    "rental_range_min": 1906,
    "rental_range_max": 2737,
    "owner_name": "VICTOR HUGO CHAVEZ JR",
    "owner_type": "COMPANY",
    "years_owned": 0.47,
    "actor_id": "kZaREmcMgZTOuIyi7",
    "run_id": "w5kQWoxSiUls89hQo"
  }
]
```

### Use Cases

- **Market Research and Analysis**: Gather comprehensive data for real estate market trends.
- **Competitive Intelligence**: Monitor competitor property listings and pricing strategies.
- **Price Monitoring**: Track property price changes over time.
- **Content Aggregation**: Compile real estate data for content creation.
- **Academic Research**: Analyze property data for academic studies.
- **Business Automation**: Automate data collection for real estate businesses.

### Installation and Usage

```
1. Search for "Realtyrac Parser Spider" in the Apify Store
2. Click "Try for free" or "Run"
3. Configure input parameters
4. Click "Start" to begin extraction
5. Monitor progress in the log
6. Export results in your preferred format (JSON, CSV, Excel)
```

### Output Format

The output is a JSON array containing detailed property information such as URL, property type, price, bedrooms, bathrooms, square footage, lot size, and historical data. Key fields include `property_id`, `listing_url`, `price`, `bedrooms`, `bathrooms`, and `sale_history`.

### Support

For custom/simplified outputs or bug reports, please contact:

- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form: https://getdataforme.com/contact/

We're here to help you get the most out of this Actor!

# Actor input Schema

## `Urls` (type: `array`):

The urls for the spider.

## Actor input object example

```json
{
  "Urls": [
    "https://www.realtytrac.com/p/aspen-ave-california-city-ca-93505-25287085/"
  ]
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/realtyrac-parser-spider").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("getdataforme/realtyrac-parser-spider").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 '{}' |
apify call getdataforme/realtyrac-parser-spider --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,getdataforme/realtyrac-parser-spider"
        }
    }
}

```

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/kZaREmcMgZTOuIyi7/builds/AoSVaHYt3VqkDJXXJ/openapi.json
