Boligsiden.dk Scraper

Extract thousands of Danish real estate listings from Boligsiden.dk — for sale, sold, and rental properties with pricing, property details, location data, and price history — for just $1 per 1,000 listings.

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What can Boligsiden.dk Scraper do for you?

• Scrape properties for sale, sold, and rentals — Search all three sections of Boligsiden.dk (tilsalg, solgte, leje) with full filtering by property type, price, size, rooms, year built, energy label, and more.
• Enrich listings with stats and price history — Optionally fetch detailed listing descriptions, images, municipality demographics, realtor ratings, page views, favourites, and the full price timeline for each property.
• Export structured data in any format — Get clean JSON output that you can download as JSON, CSV, Excel, or HTML for analysis, reporting, or integration.
• Filter by 12 property types — From villas and condos to holiday houses, farms, houseboats, and cooperative housing.
• Target by location, price, and features — Filter by municipality, province, zip code, price range, living area, lot area, rooms, year built, days on market, open house, balcony, terrace, and elevator.
• Run at scale with residential proxies — Supports Apify residential proxies for reliable, uninterrupted scraping.

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What data can you extract?

Field	Description
🏠 Property Info	Type, price, monthly expense, living area, lot area, rooms, per-area price, energy label, year built
📍 Location	Street address, zip code, city, municipality, province, coordinates
🏢 Realtor	Agency name, branch, logo, ratings, sales percentages
🖼️ Media	Property images, floor plans
📈 Enriched Data	Full description, buildings, amenities (balcony, terrace, elevator), bathrooms, toilets, floors
📊 Stats	Page views, clicks, favourites
💰 Price Timeline	Full price history with dates and event types
🏛️ Municipality	Population, schools, council tax, church tax, land value tax

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Why use this scraper?

• 📊 Danish property market research — Analyze pricing trends, time on market, and price reductions across municipalities and property types for market intelligence.
• 🏘️ Find investment opportunities — Identify undervalued properties, track price drops, and monitor days on market to spot motivated sellers.
• 📈 Competitive analysis for realtors — Monitor competitor listings, pricing strategies, and sales success rates across regions.
• 🤖 Automate property lead generation — Build custom property alerts, notify clients of new listings matching their criteria, and power automated outreach.
• 📋 Create custom property databases — Build your own portal or analysis tool with structured Boligsiden.dk data, including full price history and valuation data.

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Pricing

• $1/1,000 listings
• No hidden fees or limits on usage.
• Optional enrichment data included when enabled — pay only for what you scrape.

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How to use Boligsiden.dk Scraper

1. Create a free Apify account at apify.com if you don't have one.
2. Open the Boligsiden.dk Scraper in Apify Console.
3. Configure your search — choose search type (for sale, sold, or rentals), select property types, and apply filters like price range, area, rooms, or location.
4. Enable enrichment (optional) — toggle enrichDetails on to get full descriptions, images, stats, and price timeline.
5. Start the scraper — click "Run" and wait for your data.
6. Download your dataset — export results as JSON, CSV, Excel, or HTML.

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Input

Search Scope

• searchType (string, optional, default: "tilsalg") — Section to scrape: "tilsalg" (For Sale), "solgte" (Sold), or "leje" (Rentals)
• searchQuery (string, optional) — Location search text — city, municipality (e.g. København, Aarhus), neighborhood (e.g. Nørrebro), zip code (e.g. 2100), or street name (e.g. Strandvejen). Leave empty to search all of Denmark.
• addressTypes (array, optional) — Property types to include (leave empty for all). Options: villa, condo, terraced_house, holiday_house, cooperative, farm, hobby_farm, full_year_plot, villa_apartment, holiday_plot, houseboat, room
• sortBy (string, optional) — Sort field: timeOnMarket, price, createdAt, soldDate, area, distance, random
• sortAscending (boolean, optional, default: false) — Sort ascending (low to high)

Price & Size

• minPrice / maxPrice (integer, optional) — Price range in DKK
• minArea / maxArea (integer, optional) — Living area range in m²
• minLotArea / maxLotArea (integer, optional) — Lot area range in m²

Property Details

• minRooms / maxRooms (integer, optional) — Room count range
• minYearBuilt / maxYearBuilt (integer, optional) — Construction year range
• maxDaysOnMarket (integer, optional) — Maximum days on market
• maxDaysSincePriceDrop (integer, optional) — Maximum days since last price reduction
• hasOpenHouse (boolean, optional, default: false) — Only properties with open house
• hasBalcony (boolean, optional, default: false) — Only with balcony
• hasTerrace (boolean, optional, default: false) — Only with terrace
• hasElevator (boolean, optional, default: false) — Only with elevator
• registrationTypes (array, optional) — Sold property registration type filters: normal, family, auction, sole_owner, company, sold, new_construction

Advanced Settings

• maxItems (integer, optional, default: 0) — Maximum listings to scrape (0 = unlimited)
• maxPages (integer, optional, default: 0) — Maximum search result pages to scrape (0 = unlimited)
• enrichDetails (boolean, optional, default: false) — Fetch full details, images, stats, and price timeline
• proxyConfiguration (proxy object, optional, default: Apify RESIDENTIAL) — Proxy settings

📝 Copy for Use:

{
    "searchType": "tilsalg",
    "searchQuery": "København",
    "addressTypes": ["villa", "condo", "terraced_house"],
    "sortBy": "timeOnMarket",
    "sortAscending": false,
    "minPrice": 500000,
    "maxPrice": 10000000,
    "minArea": 50,
    "maxArea": 300,
    "minRooms": 2,
    "maxRooms": 6,
    "minYearBuilt": 1960,
    "maxYearBuilt": 2025,
    "maxDaysOnMarket": 365,
    "maxItems": 100,
    "maxPages": 0,
    "enrichDetails": true,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

---

Why Choose This Scraper?

• Affordable: Pay only $1 per 1,000 listings scraped.
• Comprehensive: Full coverage of for-sale, sold, and rental listings with 20+ filter parameters and optional enrichment with images, stats, and price history.
• Easy to Use: Simple input configuration with clear defaults — run in minutes with no coding required.
• Reliable: API-based architecture with Chrome TLS impersonation and built-in retries ensures stable data extraction at scale.

---

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🙌 Why Buy Through Our Affiliate Link?

• Exclusive Deals: Some providers may offer special discounts or bonuses when you use our link.
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• No Extra Cost: You pay the same price, but part of it goes to supporting our efforts.

Running via Apify Console

You can run this actor from the Apify Console by providing the necessary input parameters.

Running via API

You can trigger this actor using the Apify API, passing the required input in the request body.

---

API

Python

from apify_client import ApifyClient

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

run_input = {
    "searchType": "tilsalg",
    "searchQuery": "København",
    "addressTypes": ["villa", "condo", "terraced_house"],
    "sortBy": "timeOnMarket",
    "sortAscending": False,
    "minPrice": 500000,
    "maxPrice": 10000000,
    "minArea": 50,
    "maxArea": 300,
    "minRooms": 2,
    "maxRooms": 6,
    "maxItems": 100,
    "maxPages": 0,
    "enrichDetails": True,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

run = client.actor("rigelbytes/boligsiden-dk-scraper").call(run_input=run_input)
dataset = client.dataset(run["defaultDatasetId"]).list_items().items

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR-APIFY-TOKEN' });

const runInput = {
    searchType: "tilsalg",
    searchQuery: "København",
    addressTypes: ["villa", "condo", "terraced_house"],
    sortBy: "timeOnMarket",
    sortAscending: false,
    minPrice: 500000,
    maxPrice: 10000000,
    minArea: 50,
    maxArea: 300,
    minRooms: 2,
    maxRooms: 6,
    maxItems: 100,
    maxPages: 0,
    enrichDetails: true,
    proxyConfiguration: {
        useApifyProxy: true,
        apifyProxyGroups: ["RESIDENTIAL"]
    }
};

const run = await client.actor("rigelbytes/boligsiden-dk-scraper").call(runInput);
const { items } = await client.dataset(run.defaultDatasetId).listItems();

cURL

curl -X POST "https://api.apify.com/v2/acts/rigelbytes/boligsiden-dk-scraper/runs?token=YOUR-APIFY-TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "searchType": "tilsalg",
    "searchQuery": "København",
    "addressTypes": ["villa", "condo", "terraced_house"],
    "sortBy": "timeOnMarket",
    "sortAscending": false,
    "minPrice": 500000,
    "maxPrice": 10000000,
    "minArea": 50,
    "maxArea": 300,
    "minRooms": 2,
    "maxRooms": 6,
    "maxItems": 100,
    "maxPages": 0,
    "enrichDetails": true,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
  }'

---

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Understanding Proxies:

When scraping data or browsing anonymously, proxies are essential. They act as intermediaries, masking your original IP address and allowing you to send requests from another location.

Why Use Proxies?

• Avoid IP Blocks: By routing requests through proxies, you prevent the target website from recognizing your IP as a scraper or spammer.
• Access Geo-restricted Content: Proxies let you access content or websites restricted by location.
• Enhance Anonymity: Hide your actual IP, ensuring privacy while scraping or browsing.

Types of Proxies

1. Residential Proxies
   • Real IP addresses provided by ISPs to home users.
   • They mimic regular users, making them harder to detect.
   • Best for: Long-term, undetectable scraping, and avoiding blocks.
2. Data Center Proxies
   • IP addresses from servers in data centers.
   • Faster and cheaper than residential proxies but easier to detect and block.
   • Best for: High-speed scraping, but with a higher risk of detection.
3. Mobile Proxies
   • IPs provided by mobile carriers (3G/4G/5G networks).
   • Very difficult to detect, as they appear as regular mobile users.
   • Best for: Mobile-related scraping or avoiding sophisticated blocks.

Rotating Proxies vs. Straight Proxies

• Rotating Proxies: Every request you send goes through a different proxy, making it harder for websites to detect patterns.
• Straight Proxies: All requests are sent through the same proxy, making it easier to track your IP.

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About Rigel Bytes

Rigel Bytes specializes in web scraping, automation, and data analytics. We help businesses extract and leverage valuable data for informed decision-making.

Contact Us

Ready to unlock the power of data? Reach out to us at (contact@rigelbytes.com) or book an appointment with us to learn more about how we can help you achieve your data goals.

---

Detailed Data

[
  {
    "caseID": "f8df46de-9098-444b-8a67-4e8f49f1b9c6",
    "addressType": "villa",
    "priceCash": 595000,
    "monthlyExpense": 1028,
    "housingArea": 179,
    "lotArea": 843,
    "numberOfRooms": 6,
    "perAreaPrice": 3115,
    "energyLabel": "e",
    "yearBuilt": 1972,
    "roadName": "Søndervænget",
    "houseNumber": "46",
    "zipCode": 7790,
    "cityName": "Thyholm",
    "municipality": "Struer",
    "province": "Vestjylland",
    "realtorName": "Nybolig",
    "daysListed": 4719,
    "descriptionTitle": "Her er den rummelige villa til børnefamilien!",
    "status": "open",
    "hasBalcony": false,
    "hasTerrace": false,
    "hasElevator": false,
    "stats": {
      "pageViews": 5290,
      "totalClickCount": 2877,
      "totalFavourites": 68
    },
    "priceTimeline": [
      { "date": "2013-07-19T00:00:00Z", "price": 595000, "eventType": "open" }
    ]
  },
  {
    "caseID": "add1986b-329f-488b-9e81-89ed36f14cd5",
    "addressType": "villa",
    "priceCash": 1295000,
    "priceChangePercentage": -23.6,
    "monthlyExpense": 2665,
    "housingArea": 228,
    "lotArea": 1554,
    "numberOfRooms": 5,
    "perAreaPrice": 5307,
    "energyLabel": "f",
    "yearBuilt": 1955,
    "roadName": "Johs Buchholtz Vej",
    "houseNumber": "2",
    "zipCode": 7600,
    "cityName": "Struer",
    "municipality": "Struer",
    "province": "Vestjylland",
    "realtorName": "EDC",
    "daysListed": 4701,
    "status": "open",
    "stats": {
      "pageViews": 4602,
      "totalClickCount": 3281,
      "totalFavourites": 96
    },
    "priceTimeline": [
      { "date": "2013-08-06T16:24:00Z", "price": 1695000, "eventType": "open" },
      { "date": "2025-09-10T14:10:12Z", "price": 1295000, "eventType": "price_change" }
    ]
  }
]