Funda Netherlands Real Estate Scraper

Funda Netherlands Real Estate Scraper creates a structured dataset of property listings collected from Funda.nl, the largest real estate platform in the Netherlands. Each dataset item represents one property and can include address, price, size, energy label, rooms, and agent details, with optional full descriptions, coordinates, photo galleries, and agent contact information. Query the source by Funda search URL or by location with detailed filters, control the result limit with maxItems, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or other supported formats.

Dataset at a glance

Property	Value
Source	funda.nl (Netherlands)
Record unit	One property listing, with optional nested detail and agent-contact fields
Input methods	Funda search URL (startUrls) or location search (searchQueries) with filters
Main identifiers	listingId, listing url
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML, HTML (Apify dataset exports)
Update model	Fresh records per Actor run
Pricing	$1 per 1,000 listings; +$1 per 1,000 for details; +$1 per 1,000 for agent contact

Coverage and available records

The Actor collects properties from public Funda pages using one of two entry points:

• URL-based: Pass full Funda search result URLs in startUrls. Parameters are read from the URL; any filter missing from the URL is taken from the input fields below it.
• Location-based: Pass city names, neighborhoods, or postal codes (for example Amsterdam or 1012AB) in searchQueries, combined with offeringType and filters. URLs without a location search nationwide.

Supported property types: apartment, house, parking, berth, pitch, land, storage, storage_space, and substructure.

Record types and limits:

• Listing-level records are always collected: address, price, price value, price condition, offering type, property type, construction type, floor area, rooms, bedrooms, energy label, description, coordinates, and agent name.
• Detail fields are conditional: the full listing description, property features, coordinates, and complete photo gallery are returned when extractDetails is enabled.
• Agent contact fields are conditional: phone number, contact person name, and office details are returned when extractAgentContact is enabled.
• Result cap: maxItems limits the number of listings collected (0 means no limit; the default is 100).

Known exclusions: each run captures page state at run time (no historical snapshots); detail and agent-contact fields are not collected unless their toggles are enabled.

Data dictionary

Field names below match dataset record JSON properties exactly. Fields marked conditional appear only when the corresponding input toggle is enabled.

Field	Type	Nullable	Description	Example
address	string	No	Full address string	Wilhelminastraat 117 3, 1054WB Amsterdam
streetName	string	Yes	Street name	Wilhelminastraat
houseNumber	string	Yes	House number	117
postalCode	string	Yes	Dutch postal code	1054WB
city	string	Yes	City	Amsterdam
neighbourhood	string	Yes	Neighborhood	Cremerbuurt-West
municipality	string	Yes	Municipality	Amsterdam
province	string	Yes	Province	Noord-Holland
price	string	Yes	Price as rendered (with condition)	€975.000 k.k.
priceValue	number	Yes	Numeric price in EUR	975000
priceCondition	string	Yes	Price condition	kosten_koper
offeringType	string	Yes	Buy or rent	buy
propertyType	string	Yes	Property type	apartment
constructionType	string	Yes	Construction type	resale
floorArea	number	Yes	Floor area in m²	110
rooms	number	Yes	Number of rooms	4
bedrooms	number	Yes	Number of bedrooms	3
energyLabel	string	Yes	Energy label (A++++ to G)	B
description	string	Yes	Short promo description	Dubbel bovenhuis met dakterras...
agentName	string	Yes	Listing agent name	Living Real Estate
agentPhone	string	Yes	Agent phone (conditional — extractAgentContact)	0205287862
agentContactName	string	Yes	Contact person (conditional — extractAgentContact)	Angelique Bijleveld
latitude	number	Yes	Map latitude (conditional — extractDetails)	52.36126
longitude	number	Yes	Map longitude (conditional — extractDetails)	4.862332
url	string	Yes	Listing detail URL	https://www.funda.nl/detail/koop/amsterdam/...
listingId	number	No	Funda listing identifier; best stable deduplication key	8054903
publicationDate	string	Yes	Publication timestamp (ISO 8601)	2026-06-21T09:00:02.7905094+02:00
status	string	Yes	Listing status	none
images	string[]	Yes	Photo gallery URLs (conditional — extractDetails)	["https://cloud.funda.nl/...", ...]

Example dataset record

Real record produced with a location search (searchQueries: ["Amsterdam"]), buy offering, details and agent contact enabled. The images array is truncated for readability.

{
  "address": "Wilhelminastraat 117 3, 1054WB Amsterdam",
  "streetName": "Wilhelminastraat",
  "houseNumber": "117",
  "postalCode": "1054WB",
  "city": "Amsterdam",
  "neighbourhood": "Cremerbuurt-West",
  "municipality": "Amsterdam",
  "province": "Noord-Holland",
  "price": "€975.000 k.k.",
  "priceValue": 975000,
  "priceCondition": "kosten_koper",
  "offeringType": "buy",
  "propertyType": "apartment",
  "constructionType": "resale",
  "floorArea": 110,
  "rooms": 4,
  "bedrooms": 3,
  "energyLabel": "B",
  "description": "Dubbel bovenhuis met dakterras op toplocatie, eigen grond en 3 slpkmr",
  "agentName": "Living Real Estate",
  "agentPhone": "0205287862",
  "agentContactName": "Angelique Bijleveld",
  "latitude": 52.36126,
  "longitude": 4.862332,
  "url": "https://www.funda.nl/detail/koop/amsterdam/appartement-wilhelminastraat-117-3/44409366/",
  "listingId": 8054903,
  "publicationDate": "2026-06-21T09:00:02.7905094+02:00",
  "status": "none",
  "images": ["https://cloud.funda.nl/valentina_media/b9028258-c909-48d7-b7eb-a77d10135299/14cb40c3-a40f-4e8d-ae1b-e66956f7c18d"]
}

The record above was produced with this input:

{
  "searchQueries": ["Amsterdam"],
  "offeringType": "buy",
  "minPrice": 150000,
  "maxPrice": 750000,
  "propertyTypes": ["apartment", "house"],
  "extractDetails": true,
  "extractAgentContact": true,
  "maxItems": 50,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Query and input reference

Input	Type	Required	Default	Accepted values	Description
startUrls	array (requestListSources)	No*	prefill URL	Funda search result URLs	URL-based entry point; parameters are read from the URL
searchQueries	array (stringList)	No*	["Amsterdam"]	City names, neighborhoods, postal codes	Location search, ignored when URLs are provided
offeringType	string	No	buy	buy, rent	Buy (koop) or rent (huur)
minPrice	integer	No	—	0 or positive integer	Minimum asking price in EUR
maxPrice	integer	No	—	0 or positive integer	Maximum asking price in EUR
propertyTypes	array	No	["apartment", "house"]	apartment, house, parking, berth, pitch, land, storage, storage_space, substructure	Property types; empty means all
constructionType	string	No	""	"", resale, newly_built	Construction type filter
minFloorArea / maxFloorArea	integer	No	—	0 or positive integer	Living area range in m²
minPlotArea / maxPlotArea	integer	No	—	0 or positive integer	Plot area range in m²
minRooms / maxRooms	integer	No	—	0 or positive integer	Room count range
minBedrooms / maxBedrooms	integer	No	—	0 or positive integer	Bedroom count range
publicationDate	string	No	no_preference	no_preference, 1, 3, 7, 10, 14, 30	Listings published within N days
availability	string	No	available	available, negotiations, available_and_negotiations, sold	Availability status
energyLabels	array	No	[]	A++++ … G	Energy label filter; empty means all
exteriorSpaceTypes	array	No	[]	garden, balcony, terrace	Exterior space filter
hasGarden	boolean	No	false	true / false	Shortcut for exterior space garden
constructionPeriods	array	No	[]	before_1906 … after_2020	Construction period filter
surroundingTypes	array	No	[]	rural, in_center, by_water, and more	Surrounding area filter
garage* / parking*	boolean	No	false	true / false	Garage and parking filters
freeTextSearch	string	No	—	Free text	Search within listing descriptions
sortBy	string	No	relevance	relevance, price_asc, price_desc, floor_area_desc, publication_date_desc	Sort order
extractDetails	boolean	No	false	true / false	Collect detail fields and photo gallery (charged as listing details)
extractAgentContact	boolean	No	false	true / false	Collect agent phone and contact (charged as contact info)
detailConcurrency	integer	No	10	1–50	Parallel detail requests
maxItems	integer	No	100	0 (no limit) or positive integer	Maximum listings to collect
proxyConfiguration	object	No	Apify proxy, RESIDENTIAL group	Apify proxy groups or custom proxies	Residential proxies are required for reliable runs

* Provide either startUrls or searchQueries — at least one source is required.

Minimal request:

{ "searchQueries": ["Amsterdam"], "offeringType": "buy" }

Advanced request (location search with filters and enrichment):

{
  "searchQueries": ["Amsterdam"],
  "offeringType": "buy",
  "minPrice": 150000,
  "maxPrice": 750000,
  "propertyTypes": ["apartment", "house"],
  "energyLabels": ["A", "B"],
  "exteriorSpaceTypes": ["garden"],
  "availability": "available_and_negotiations",
  "sortBy": "publication_date_desc",
  "extractDetails": true,
  "extractAgentContact": true,
  "maxItems": 500,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Retrieve the data through the API

The Actor runs on the Apify platform, so there is no server to host and no crawling infrastructure to maintain.

1. Start the Actor with a JSON input (console or API).
2. Wait for the run to finish, or use a synchronous endpoint if you want the response inline.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset.

Python example:

from apify_client import ApifyClient

client = ApifyClient("YOUR-APIFY-TOKEN")

run_input = {
    "searchQueries": ["Amsterdam"],
    "offeringType": "buy",
    "maxItems": 50,
}

run = client.actor("datascrapers/funda-nl-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["listingId"], item["priceValue"], item["address"])

Apify generates ready-to-run Python, JavaScript, and cURL examples on the Actor's API tab. Do not put a real API token in shared code or URLs.

Data quality and record handling

• Conditional fields: detail fields (latitude, longitude, images) are present only when extractDetails is enabled; agentPhone and agentContactName are present only when extractAgentContact is enabled.
• Source changes: Funda page structure and values can change; unreadable fields are returned as null rather than fabricated.
• Deduplication: each run appends fresh records; the Actor does not deduplicate listings across runs. Use listingId as the stable key and filter repeated runs against previously stored IDs.
• Rate limits: Funda can rate-limit automated traffic; residential proxies are required for reliable runs.
• Normalization: priceValue is a numeric EUR value while price preserves the rendered string with condition; publicationDate is an ISO 8601 timestamp.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL / Supabase	Dataset API poll or webhook consumer	Store Dutch property inventory with price history
Google Sheets	Apify Google Sheets integration	Share market shortlists with agents
BI tools (Looker, Tableau)	Scheduled export via Apify scheduler	Price-per-m² benchmarking by city
S3 / cloud storage	Scheduled export + integration	Archival of market snapshots

Pricing and cost examples

The Actor uses pay-per-event pricing with three chargeable events, all billed per 1,000 listings:

Event	Trigger	Rate
Result	Every listing record pushed to the dataset	$1 per 1,000
Listing details	extractDetails enabled, detail page fetched	$1 per 1,000
Contact info	extractAgentContact enabled, agent contact retrieved	$1 per 1,000

Example costs:

Records	Configuration	Estimated base cost
1,000	Listing only	$1.00
10,000	Listing only	$10.00
1,000	Listing + details	$2.00
1,000	Listing + details + agent contact	$3.00

Apify paid plans reduce the per-1,000 rate. Compute units consumed by the run are billed by your Apify plan. Estimates depend on the verified pricing model and the options selected for the run.

Limitations and responsible data use

• The Actor collects publicly accessible data from Funda pages only.
• Field availability depends on what Funda renders at run time; some values can be null or missing, and site changes can alter fields.
• Detail and agent-contact fields are only collected when their toggles are enabled.
• The Actor does not provide historical snapshots unless you store them yourself.
• Large runs require residential proxies; without them, coverage may degrade due to rate limiting.
• You are responsible for compliance with Funda's terms of service, applicable privacy law, and any contractual obligations before using the data.

Dataset questions

What does one dataset item represent?

One property listing from Funda. Detail-page fields (images, coordinates) and agent-contact fields are nested inside the same record, so a listing with full details still produces a single dataset item.

Which field should I use as a unique identifier?

listingId is the stable Funda listing identifier and is the recommended deduplication key. The url (listing detail URL) is a reasonable secondary key.

Are fields nullable or conditional?

Yes. Detail fields (latitude, longitude, images) exist only when extractDetails is enabled; agentPhone and agentContactName exist only when extractAgentContact is enabled. Within available records, fields that Funda does not render (for example neighbourhood or energyLabel) are returned as null.

Can I retrieve the records as CSV or JSON?

Yes. The dataset can be exported as JSON, CSV, Excel, XML, or HTML from the Apify Console, and queried through the Dataset API.

Does the Actor return historical data?

No. Each run captures the state of the pages at run time. To track price changes over time, schedule repeated runs and store the outputs yourself.

What counts as a billable result?

Three pay-per-event charges apply: a result charge for every listing record ($1 per 1,000), a listing-details charge for each detail page fetched ($1 per 1,000), and a contact-info charge for each agent contact retrieved ($1 per 1,000). A listing-only run incurs only the result charge.

Which filters can I combine?

The Actor supports price, property type, construction type, floor and plot area, rooms, bedrooms, publication date, availability, energy label, exterior space, construction period, surrounding area, garage, and parking filters. Filters are ignored when startUrls are provided, since parameters are read from the URL.

Related datasets from Data Scrapers

• Zoopla Scraper — UK property listings for cross-market housing research alongside Dutch data.
• Apartments Scraper — US rental listings for comparative market analysis.
• Redfin Scraper — US property listings and market signals for international real estate datasets.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.