# Funda Propertylist Spider (`getdataforme/funda-propertylist-spider`) Actor
The Funda Propertylist Spider efficiently scrapes detailed property data from Funda.nl for real estate analysis. It offers customizable inputs, high performance, and scalable data extraction....
- **URL**: https://apify.com/getdataforme/funda-propertylist-spider.md
- **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community)
- **Categories:** AI, E-commerce, Other
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN 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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## Funda Propertylist Spider
### Introduction
The Funda Propertylist Spider is designed to efficiently scrape property listings from Funda.nl, providing comprehensive data for real estate analysis and decision-making. This actor is perfect for users looking to gather detailed property information for market research, competitive intelligence, or business automation.
### Features
- **Comprehensive Data Extraction**: Captures detailed property information including price, bedrooms, energy label, and more.
- **High Performance**: Efficiently processes multiple URLs to deliver fast and reliable results.
- **Customizable Inputs**: Easily configure start URLs to target specific areas or property types.
- **Data Quality**: Ensures accurate and up-to-date information directly from Funda.nl.
- **Scalable**: Handles large volumes of data with ease, making it suitable for both small and large-scale projects.
- **User-Friendly Interface**: Simple setup and execution through the Apify platform.
- **Versatile Output Formats**: Export results in JSON, CSV, or Excel for easy integration into your workflow.
### Input Parameters
| Parameter | Type | Required | Description | Example |
|-------------|--------|----------|---------------------------------------------------|-------------------------------------------------------------------------|
| StartUrls | Array | No | The start URLs for the spider. | `["https://www.funda.nl/en/zoeken/koop?selected_area=[%22bergen-li%22]"]` |
### Example Usage
#### Example Input JSON
```json
{
"StartUrls": [
"https://www.funda.nl/en/zoeken/koop?selected_area=[%22bergen-li%22]"
]
}
````
#### Example Output JSON
```json
[
{
"id": 7966834,
"price": 685000,
"price_condition": "kosten_koper",
"bedrooms": 4,
"rooms": 8,
"floor_area": 237,
"plot_area": 1660,
"energy_label": "B",
"object_type": "house",
"construction_type": "resale",
"street": "Oude Kerkstraat",
"house_number": "24",
"postal_code": "5854AC",
"city": "Bergen (LI)",
"province": "Limburg",
"agent_name": "Kolmeijer makelaars Malden",
"agent_id": 13045,
"agent_url": "https://www.funda.nl/makelaar/13045-kolmeijer-makelaars-malden/",
"detail_url": "https://www.funda.nl/detail/koop/bergen-li/huis-oude-kerkstraat-24/43311297/",
"thumbnail_ids": [227423877, 227423878, 227423884, ...],
"actor_id": "va275Uj9AJtJA5CxI",
"run_id": "C8hXloSyex81gkdjL"
}
]
```
### Use Cases
- **Market Research and Analysis**: Gather data for understanding real estate trends.
- **Competitive Intelligence**: Monitor competitor listings and pricing strategies.
- **Price Monitoring**: Track property prices over time for investment decisions.
- **Content Aggregation**: Compile property data for websites or applications.
- **Academic Research**: Analyze housing data for studies and reports.
- **Business Automation**: Automate data collection for real estate businesses.
### Installation and Usage
1. Search for "Funda Propertylist 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. Key fields include `price`, `bedrooms`, `energy_label`, `object_type`, `agent_name`, and `detail_url`. This structured data allows for easy analysis and integration into various applications.
### Support
For custom/simplified outputs or bug reports, please contact:
- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form:
We're here to help you get the most out of this Actor!
# Actor input Schema
## `StartUrls` (type: `array`):
The start urls for the spider.
## Actor input object example
```json
{
"StartUrls": [
"https://www.funda.nl/en/zoeken/koop?selected_area=[%22bergen-li%22]"
]
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {};
// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/funda-propertylist-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {}
# Run the Actor and wait for it to finish
run = client.actor("getdataforme/funda-propertylist-spider").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).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/funda-propertylist-spider --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=getdataforme/funda-propertylist-spider",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Funda Propertylist Spider",
"description": "The Funda Propertylist Spider efficiently scrapes detailed property data from Funda.nl for real estate analysis. It offers customizable inputs, high performance, and scalable data extraction....",
"version": "0.0",
"x-build-id": "sfsvNMbajVVT8FeLc"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/getdataforme~funda-propertylist-spider/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-getdataforme-funda-propertylist-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/getdataforme~funda-propertylist-spider/runs": {
"post": {
"operationId": "runs-sync-getdataforme-funda-propertylist-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/getdataforme~funda-propertylist-spider/run-sync": {
"post": {
"operationId": "run-sync-getdataforme-funda-propertylist-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"StartUrls": {
"title": "Start Urls",
"minItems": 1,
"type": "array",
"description": "The start urls for the spider.",
"default": [
"https://www.funda.nl/en/zoeken/koop?selected_area=[%22bergen-li%22]"
],
"items": {
"type": "string"
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```