Boligsiden.dk Scraper

Boligsiden Scraper creates a structured dataset of property rows collected from Boligsiden in Denmark. Each dataset item is one case and can include the case id, road, zip code, cash price, housing area, room count, energy label, and year built. Query the source with a search type, a location string, and property types, limit the run with maxItems, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, XML, or another supported format.

Dataset at a glance

Property	Value
Source	boligsiden.dk
Record unit	One property case
Input methods	searchType, searchQuery, addressTypes
Main identifiers	caseID
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML, and other Apify dataset exports
Update model	Fresh records per Actor run
Pricing	$1.00 per 1,000 dataset-item events

Coverage and available records

The Actor searches for-sale, sold, and rental sections. An empty searchQuery searches Denmark. The saved sample is a for-sale house in zip 7790.

Supported:

• tilsalg, solgte, and leje
• City, municipality, neighborhood, zip, or street text
• Price, area, rooms, year built, and days-on-market filters
• Feature flags such as balcony, terrace, elevator, and open house
• A result cap through maxItems and a page cap through maxPages. 0 means no cap

Not currently collected unless enrichDetails is true:

• Extra images, building notes, description, and the price timeline
• The saved search row already includes the cash price, area, and energy label

Data dictionary

Fields match a saved for-sale row. Prices are Danish kroner.

Field	Type	Nullable	Description	Example
caseID	string	No	Case UUID. Best field for deduplication.	f8df46de-9098-444b-8a67-4e8f49f1b9c6
roadName	string	Yes	Street name.	Søndervænget
zipCode	number	Yes	Postal code.	7790
priceCash	number	Yes	Cash price in DKK.	595000
housingArea	number	Yes	Living area in square meters.	179
numberOfRooms	number	Yes	Room count.	6
energyLabel	string	Yes	Energy label.	e
yearBuilt	number	Yes	Construction year.	1972
slug	string	Yes	Address slug.	soendervaenget-46-7790-thyholm-06710287__46_______
lat	number	Yes	Latitude.	Present on the saved row
lon	number	Yes	Longitude.	Present on the saved row
imageUrl	string	Yes	Photo URL.	Present on the saved row

Example dataset record

{
  "caseID": "f8df46de-9098-444b-8a67-4e8f49f1b9c6",
  "roadName": "Søndervænget",
  "zipCode": 7790,
  "priceCash": 595000,
  "housingArea": 179,
  "numberOfRooms": 6,
  "energyLabel": "e",
  "yearBuilt": 1972
}

The saved row came from a for-sale search. enrichDetails was not required for these fields.

Query and input reference

Input	Type	Required	Default	Accepted values	Description
searchType	string	No	tilsalg	tilsalg, solgte, leje	Which section of Boligsiden.dk to scrape
searchQuery	string	No	``		Location search text — city, municipality (e.g.
addressTypes	array	No	["villa", "condo", "terraced_house"]	villa, condo, terraced_house, holiday_house, cooperative, farm, hobby_farm, full_year_plot, villa_apartment, holiday_plot, houseboat, room	Filter by property types (leave empty for all)
sortBy	string	No	``	timeOnMarket, price, createdAt, soldDate, area, distance, random	How to sort the results (note: only timeOnMarket, price, and random work for tilsalg; price, timeOnMarket, and soldDate for solgte; createdAt for leje)
sortAscending	boolean	No	False		Sort from lowest to highest (false = highest to lowest)
minPrice	integer	No	``		Minimum price in Danish Kroner
maxPrice	integer	No	``		Maximum price in Danish Kroner
minArea	integer	No	``		Minimum living area in square meters
maxArea	integer	No	``		Maximum living area in square meters
minLotArea	integer	No	``		Minimum lot/plot area in square meters
maxLotArea	integer	No	``		Maximum lot/plot area in square meters
minRooms	integer	No	``		Minimum number of rooms
maxRooms	integer	No	``		Maximum number of rooms
minYearBuilt	integer	No	``		Earliest construction year
maxYearBuilt	integer	No	``		Latest construction year
maxDaysOnMarket	integer	No	``		Only properties listed for at most this many days
maxDaysSincePriceDrop	integer	No	``		Only properties with a price reduction within this many days
hasOpenHouse	boolean	No	False		Only properties with scheduled open house viewings
hasBalcony	boolean	No	False		Only properties with a balcony
hasTerrace	boolean	No	False		Only properties with a terrace
hasElevator	boolean	No	False		Only properties with an elevator in the building
registrationTypes	array	No	``	normal, family, auction, sole_owner, company, sold, new_construction	Filter sold properties by registration type (normal, auction, family transfer, etc.)
maxItems	integer	No	0		Maximum number of listings to scrape (0 = unlimited)
maxPages	integer	No	0		Maximum number of search result pages to scrape (0 = unlimited)
enrichDetails	boolean	No	False		Fetch listing details (images, buildings, description, realtor ratings), stats (page views, favourites, clicks), and price timeline for each listing
maxConcurrency	integer	No	10		How many listings to enrich in parallel when enrichDetails is enabled (1–50).
proxyConfiguration	object	No	{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}		Proxy settings for anti-bot protection

Minimal request:

{
  "searchType": "tilsalg",
  "searchQuery": "7790",
  "maxItems": 10
}

Retrieve the data through the API

1. Start datascrapers/boligsiden-dk-scraper with the JSON input.
2. Wait until the run finishes, or call the synchronous dataset endpoint.
3. Read items from the run's default dataset.
4. Paginate with dataset offset and limit.

from apify_client import ApifyClient

client = ApifyClient("<APIFY_TOKEN>")
run = client.actor("datascrapers/boligsiden-dk-scraper").call(run_input={
    "searchType": "tilsalg",
    "searchQuery": "7790",
    "maxItems": 10,
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["caseID"], item["priceCash"], item["zipCode"])

Other languages are listed on the Actor's API tab. This is the Apify Actor API, not a Boligsiden API.

Data quality and record handling

• One dataset item is one case. Each pushed case charges one dataset-item event.
• Deduplicate on caseID.
• label can be an empty string on a saved row.
• Prices are kroner as returned by Boligsiden.
• maxItems and maxPages of 0 do not cap the result set.

Pricing and cost examples

The price file charges $1.00 per 1,000 listings. That is $0.001 per dataset-item on every Apify plan. Platform usage, including compute and proxy, is billed separately by Apify.

Records	Estimated event cost
1,000	$1.00
10,000	$10.00

Limitations and responsible data use

• Coverage is the search the input requests. An empty query is a Denmark-wide search and can be large.
• Sort options depend on searchType. Some sort values do not apply to every section.
• Prices change. This dataset is not a historical archive unless enrichment returns a price timeline for that run.
• You are responsible for complying with Boligsiden's terms and applicable law.

Dataset questions

What does one dataset item represent?

One Boligsiden property case from for-sale, sold, or rental search.

Which field should I use as a unique identifier?

Use caseID.

Are fields nullable or conditional?

Yes. Description and price timeline fields are conditional on enrichDetails.

Can I retrieve the records as CSV or JSON?

Yes. Export the default dataset as JSON, CSV, Excel, XML, or another Apify format.

How do I paginate large datasets?

Use limit and offset on the dataset items endpoint. maxItems and maxPages limit the run.

Does the Actor return historical data?

Sold searches return sold rows. A for-sale row is the current case.

What counts as a billable result?

One dataset-item event per case saved to the dataset.

Related datasets from Data Scrapers

• Bezrealitky Scraper collects Czech sale and rent offers.
• BNP Paribas Real Estate Scraper collects German commercial property listings.
• Boliga Scraper collects Danish listings with price and energy class.
• Booli Scraper collects Swedish for-sale and sold homes.
• Apartments Scraper collects US rental listings.
• Bayut Scraper collects UAE property listings.

Data Scrapers support

Questions about this dataset: stardustspotlight@gmail.com