DAHLER Real Estate Scraper

DAHLER Real Estate Scraper creates a structured dataset of buy and rent listings collected from DAHLER (dahler.com) in Germany, Austria, and Spain. Each dataset item is one property and can include property_id, title, URL, purchase type, price or base rent, living area, room count, property type, city, country, coordinates, and energy class when the detail page provides it. Query the source with region and marketingTypes (buy, rent, or both). Cap the run with maxItems. Turn on fetchDetails for gallery, description, and office fields. Retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or XML.

Dataset at a glance

Property	Value
Source	dahler.com
Record unit	One property listing
Input methods	region, marketingTypes, fetchDetails
Main identifiers	property_id, url
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML
Update model	Fresh records per Actor run
Pricing	$5.00 per 1,000 dataset-item events. Platform usage is billed separately.

Coverage and available records

Regions follow the Actor input, including a German state, Berlin, nationwide Germany, Austria, and Spain. marketingTypes selects buy, rent, or both. Overview rows come from the public search index. fetchDetails opens the listing page for description, images, energy data, and office contact. A detail failure keeps the overview row.

price is the asking purchase price for buy listings. base_rent is the rent figure for rent listings. price_on_request is true when the index marks the price as on request, and the numeric price is then empty.

Data dictionary

Field	Type	Nullable	Description	Example
property_id	string	no	DAHLER property id. Deduplication key.	DC-BER32752
url	string	yes	Listing page	https://www.dahler.com/de/immobilie-kaufen/wohnimmobilien/dachgeschoss/berlin/dachgeschoss-highlight-mit-sonnenterrassen-am-rosenthaler-platz/DC-BER32752
title	string	yes	Listing headline. Stored in German.	Dachgeschoss-Highlight mit Sonnenterrassen am Rosenthaler Platz
purchase_type	string	yes	BUY or RENT	BUY
marketing_type	string	yes	buy or rent	buy
price	number	yes	Asking purchase price, EUR	995000
base_rent	number	yes	Rent amount when the listing is a rental
price_on_request	boolean	yes	True when no public price is posted	false
price_per_m2	number	yes	Price per square meter	7571.43
living_area_m2	number	yes	Living area	139.27
nr_rooms	number	yes	Room count	4.0
property_type	string	yes	Normalized type	OTHER
city	string	yes	Locality label	Berlin / Mitte
country	string	yes	Country label	Deutschland
energy_class	string	yes	Energy class when the detail page has one

Example dataset record

Saved buy listing from a Berlin search. The headline on the site is German. Office contact names are omitted.

{
  "property_id": "DC-BER32752",
  "url": "https://www.dahler.com/de/immobilie-kaufen/wohnimmobilien/dachgeschoss/berlin/dachgeschoss-highlight-mit-sonnenterrassen-am-rosenthaler-platz/DC-BER32752",
  "title": "Dachgeschoss-Highlight mit Sonnenterrassen am Rosenthaler Platz",
  "purchase_type": "BUY",
  "price": 995000,
  "living_area_m2": 139.27,
  "property_type": "OTHER",
  "city": "Berlin / Mitte",
  "base_rent": null,
  "energy_class": null
}

Query and input reference

Field	Type	Description
region	string	Search region, such as Berlin, Deutschland, or Austria.
marketingTypes	array	buy, rent, or both.
fetchDetails	boolean	Open listing pages for description, images, and office fields.
maxDetailConcurrency	integer	Parallel detail requests.
maxItems	integer	Maximum listings.
proxyConfiguration	object	Apify proxy settings. Residential is the intended default.

Retrieve the data through the API

from apify_client import ApifyClient

client = ApifyClient("YOUR-APIFY-TOKEN")
run = client.actor("datascrapers/dahler-scraper").call(run_input={
    "region": "Berlin",
    "marketingTypes": ["buy", "rent"],
    "fetchDetails": True,
    "maxItems": 5,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["property_id"], item["city"], item.get("price"))

Data quality and record handling

Deduplicate on property_id. Prices are asking figures from DAHLER, in EUR unless the record says otherwise. price and base_rent are separate: a buy row leaves base_rent empty, and a rent row leaves price empty when the index only has rent. Coordinates come from the search index. Energy class is present only after a successful detail fetch.

Pricing and cost examples

Event	When it fires	Free	Bronze	Silver	Gold
dataset-item	Every listing saved	$5.00 / 1,000	$4.90 / 1,000	$4.80 / 1,000	$4.70 / 1,000

Platinum and Diamond use the Gold rate. Platform usage, including residential proxy traffic, is billed separately.

1,000 saved listings cost $5.00 in event charges on Free and $4.70 on Gold, plus platform usage.

Limitations and responsible data use

DAHLER can change region coverage and listing ids. Asking prices are not transaction prices. Office emails on a detail page belong to the agency. Use the dataset for market research. Do not treat a missing price as zero. price_on_request means the figure was withheld.

Dataset questions

What is one record?

One DAHLER listing, buy or rent.

Which field is the key?

property_id.

Does fetchDetails change the charge?

No. The saved listing is one dataset-item whether or not the detail page was opened.

Related datasets from Data Scrapers

• CBRE Scraper
• Funda Scraper
• Boliga Scraper
• Crexi Scraper
• Apartments Scraper

Data Scrapers support

Questions about this dataset: stardustspotlight@gmail.com.