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.

178 runs
15 users
Try This Actor

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

  1. Click "Try This Actor" to open it on Apify
  2. Create a free Apify account if you don't have one
  3. Configure the input parameters as needed
  4. 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

  1. In the Apify Console, create a new Actor.
  2. Copy the code from src/main.js into the source code editor.
  3. Update the package.json with the required dependencies (see below).
  4. Ensure the Dockerfile is correctly configured.
  5. 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 Trial

Actor Information

Developer
bpg
Pricing
Paid
Total Runs
178
Active Users
15
Apify Platform

Apify provides a cloud platform for web scraping, data extraction, and automation. Build and run web scrapers in the cloud.

Learn more about Apify

Need Professional Help?

Couldn't solve your problem? Hire a verified specialist on Fiverr to get it done quickly and professionally.

Find a Specialist

Trusted by millions | Money-back guarantee | 24/7 Support