Funda Scraper
by bpg
Extract property listings, prices, and details from Funda automatically. Get clean, structured real estate data delivered to your spreadsheet or app.
Opens on Apify.com
About Funda Scraper
Need to pull real estate data from Funda for your project? This actor is your go-to. I've used it to gather property listings, prices, and key details without getting blocked. It navigates the site just like a person, handling search results and pagination automatically. You can configure it to target specific locations, property types, and price ranges. It extracts everything from the address and asking price to the number of rooms, square footage, and property description. The data comes out clean and structured in JSON, CSV, or Excel, ready to drop into your analysis or application. It's perfect for building market analysis reports, tracking price trends, or aggregating listings for a portfolio site. Since it runs on Apify, you can schedule it to run daily and store the results directly in the cloud. It saves you the headache of writing and maintaining your own scraper, letting you focus on actually using the data.
What does this actor do?
Funda Scraper is a web scraping and automation tool available on the Apify platform. It's designed to help you extract data and automate tasks efficiently in the cloud.
Key Features
- Cloud-based execution - no local setup required
- Scalable infrastructure for large-scale operations
- API access for integration with your applications
- Built-in proxy rotation and anti-blocking measures
- Scheduled runs and webhooks for automation
How to Use
- Click "Try This Actor" to open it on Apify
- Create a free Apify account if you don't have one
- Configure the input parameters as needed
- Run the actor and download your results
Documentation
Funda Scraper
An Apify Actor that extracts detailed property listing data from Funda.nl. It's designed to scrape comprehensive information from Dutch real estate advertisements.
Overview
This actor takes a single Funda.nl property URL as input and returns a structured JSON object containing all available listing details. It uses Puppeteer to handle the dynamic content on the site.
Key Features
The scraper extracts the following data groups:
- Property Information: Title, full address, price (asking price, buyer's costs), specifications (living area, plot size, volume, room/bedroom count), year of construction, energy label, property type, and status.
- Detailed Characteristics: Complete features table, garden details, parking facilities, insulation, heating information, and construction type.
- Description & Media: Full property description, high-resolution photo URLs, and counts of photos, floor plans, 360° images, and videos.
- Market Data: View count, save/favorite count, listing date, and neighborhood statistics (inhabitants, average price per m²).
- Broker: Real estate agency name and phone number.
How to Use
Input Configuration
Provide a JSON object with the target Funda.nl listing URL.
{
"url": "https://www.funda.nl/detail/koop/amsterdam/huis-voorbeeld-12345678/"
}
| Field | Type | Required | Description |
|---|---|---|---|
url |
String | Yes | The full URL of the Funda.nl property listing to scrape. |
Running the Actor
- In the Apify Console, create a new Actor.
- Copy the code from
src/main.jsinto the source code editor. - Update the
package.jsonwith the required dependencies (see below). - Ensure the Dockerfile is correctly configured.
- Build and run the Actor.
Package.json Dependencies:
{
"dependencies": {
"apify": "^3.4.2",
"crawlee": "^3.5.0",
"puppeteer": "*"
}
}
Recommended Actor Settings:
* Memory: Minimum 512 MB (1GB recommended).
* Timeout: Minimum 300 seconds.
* Build: Use the apify/actor-node-puppeteer-chrome Docker image.
Input/Output
Output Example
The actor returns a detailed JSON object. Here's a condensed example showing the structure:
{
"url": "https://www.funda.nl/detail/koop/soest/huis-julianalaan-33/43006481/",
"titel": "Julianalaan 33",
"adres": "Julianalaan 33",
"postcode": "3761 DB",
"plaats": "Soest",
"vraagprijs": "€ 795.000 k.k.",
"woonoppervlakte": "140 m²",
"perceeloppervlakte": "290 m²",
"aantal_kamers": "6 kamers (4 slaapkamers)",
"bouwjaar": "1937",
"energielabel": "E",
"kenmerken": {
"Vraagprijs per m²": "€ 5.679",
"Aangeboden sinds": "2 weken"
},
"media": {
"fotos": 30,
"plattegronden": 6
},
"foto_urls": ["https://cloud.funda.nl/valentina_media/185/901/234_1440x960.jpg"],
"populariteit": {
"aantal_keer_bekeken": "11.546"
},
"makelaar_naam": "Deelen Makelaars SOEST",
"gescraped_op": "2025-08-03T20:45:32.123Z"
}
Categories
Common Use Cases
Market Research
Gather competitive intelligence and market data
Lead Generation
Extract contact information for sales outreach
Price Monitoring
Track competitor pricing and product changes
Content Aggregation
Collect and organize content from multiple sources
Ready to Get Started?
Try Funda Scraper now on Apify. Free tier available with no credit card required.
Start Free TrialActor Information
- Developer
- bpg
- Pricing
- Paid
- Total Runs
- 178
- Active Users
- 15
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