# Fang Properties and Details Scraper (`realestateapi/fang-properties-and-details-scraper`) Actor

Fang access-status Actor. No applicable written permission is recorded; runtime writes AUTHORIZATION_REQUIRED to RUN_METADATA, emits no dataset rows, and makes zero Fang requests. The retained parser is offline only.

- **URL**: https://apify.com/realestateapi/fang-properties-and-details-scraper.md
- **Developed by:** [Real Estate API](https://apify.com/realestateapi) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.99 / 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.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Fang Properties and Details Scraper

### Current behavior

This Actor is in access-status mode. Fang's public service agreement and copyright declaration were reviewed in Chrome on 2026-09-25. They restrict unauthorized copying, commercial use, and derivative works; no applicable written permission is recorded. The Actor therefore emits one AUTHORIZATION_REQUIRED diagnostic and a SKIPPED_POLICY run summary with zero source requests. Its input schema exposes no way to self-attest or enable scraping.

The community parser remains available for offline regression tests only. The Actor runtime does not call it and does not contact Fang. Policy diagnostics and failures are stored in `RUN_METADATA`, never in the dataset. The only saved local artifact is historical RUN_METADATA from a 2026-09-23 failed fetch; no community dataset is present. The old summary is preserved and is not current extraction evidence.

New runs use `SUCCEEDED` / `SKIPPED_POLICY` with exit code 0 for the no-request policy gate. A completed empty run is `SUCCEEDED` / `COMPLETED`; a later failure after saved community rows is `SUCCEEDED` / `PARTIAL`; a failure with zero saved rows is `FAILED` / `FAILED` with exit code 1.

### Offline verification

Run npm test, npm run lint, and apify validate-schema. Synthetic parser tests do not prove current source coverage. Do not use --purge or run a live source request without applicable written permission.

### Runtime dependency remediation — 2026-10-03

The full Actor SDK and its unused crawler, HTTP cache, FTP and proxy dependency chains were removed. The batch entrypoint now uses native fetch for the documented Apify dataset and key-value-store APIs, awaits storage acknowledgements, confines the platform credential to api.apify.com, refuses redirects, and uses the official standalone @apify/log logger. The build performs a production dependency audit and stores its exact locked application graph as RUNTIME_DEPENDENCIES. This evidence concerns the application graph, not operating-system packages. Node.js 22 or later is required.

Source permission gates, allowed hosts, advertised extraction scope, and historical storage remain unchanged. A clean dependency audit or a successful closed-gate run does not qualify source extraction. The existing written-authorization and no-retry instructions still apply.

Storage API documentation: https://docs.apify.com/api/v2/dataset-items-post and https://docs.apify.com/api/v2/key-value-store-record-put.

# Actor input Schema

## Actor input object example

```json
{}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `runMetadata` (type: `string`):

No description

## `dependencies` (type: `string`):

No description

# 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("realestateapi/fang-properties-and-details-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 = {}

# Run the Actor and wait for it to finish
run = client.actor("realestateapi/fang-properties-and-details-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 '{}' |
apify call realestateapi/fang-properties-and-details-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,realestateapi/fang-properties-and-details-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/78sfD5b8KLNoqZH62/builds/7Hv0QGFNh8qrPLD0F/openapi.json