# Nybolig Property Search Scraper (`stealth_mode/nybolig-property-search-scraper`) Actor Scrape comprehensive property listings from Nybolig.dk with 48 detailed fields. Perfect for real estate analysts, investors, and researchers gathering Danish housing market data — addresses, prices, property features, and more in structured format. - **URL**: https://apify.com/stealth\_mode/nybolig-property-search-scraper.md - **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community) - **Categories:** Automation, Developer tools, Real estate - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Nybolig Property Search Scraper: Extract Danish Real Estate Data at Scale --- ### What Is Nybolig.dk? Nybolig.dk is Denmark's leading real estate platform, hosting thousands of active property listings across residential, commercial, and agricultural segments. The platform serves as the primary marketplace for property buyers, sellers, and agents throughout Denmark. Manually extracting property data from search results is tedious and error-prone — the **Nybolig Property Search Scraper** automates this workflow, transforming search result pages into clean, structured datasets. --- ### Overview The **Nybolig Property Search Scraper** extracts comprehensive property records from Nybolig.dk search result pages, capturing everything from address coordinates to energy classifications and amenity flags. It is designed for: - **Real estate investors** tracking market trends by location and price range - **Data analysts** building Danish housing market datasets - **Property managers** monitoring competing listings and valuations - **Market researchers** analyzing property types, sizes, and availability - **Developers** integrating Danish property data into platforms or dashboards Key strengths include support for large result sets (up to 200+ items per URL), flexible URL handling via `ignore_url_failures`, and comprehensive field coverage spanning location, pricing, property characteristics, and listing status. --- ### Input Format The scraper accepts a JSON configuration specifying search result URLs and collection parameters: ```json { "urls": [ "https://www.nybolig.dk/soegeresultat-boliger?displayNames=Aalborg&municipalityNames=Aalborg&caseCounts=2166" ], "ignore_url_failures": true, "max_items_per_url": 200 } ```` | Field | Description | |---|---| | `urls` | Array of Nybolig search result page URLs to scrape (e.g., filtered by city, price, or property type) | | `max_items_per_url` | Maximum properties extracted per URL; default `20`, can increase to `200` | | `ignore_url_failures` | If `true`, scraper continues if a URL fails to load; if `false`, the run halts on first failure | **Examples of valid URLs:** - Search by municipality: `https://www.nybolig.dk/soegeresultat-boliger?municipalityNames=Copenhagen` - Search by price range: `https://www.nybolig.dk/soegeresultat-boliger?priceMin=500000&priceMax=2000000` - Search by property type: `https://www.nybolig.dk/soegeresultat-boliger?propertyTypes=Villa` > **Tip:** Copy the full URL from your browser after filtering on Nybolig.dk to ensure all parameters are preserved. *** ### Output Format **Sample output** ```json { "id": "SUNhc2U6NzcyODUx", "site_name": "nybolig", "case_number": "N2402680000791", "address_display_name": "Jagtvej 7, 9000 Aalborg", "address_first_line": "Jagtvej 7", "address_second_line": "9000 Aalborg", "address_longitude": 9.88466543966381, "address_latitude": 57.0415365413044, "address_wkt_point": "", "address_city": "Aalborg", "url": "/villa/9000/jagtvej/n240268/n2402680000791", "image_url": "https://nybolig.mindworking.eu/api/mediaData/mediaDataMediaPurposeId/SU1lZGlhRGF0YTp7Ik1lZGlhRGF0YUlkIjo4NDk4MjYyLCJNZWRpYVB1cnBvc2VJZCI6MjJ9/imageHash/baa51779e90f51404b6f8fa0dc9ae617/imageSize/Assets/inline/True?bgcolor=ffffff&dpi=72&jq=70&tp=rgb&fo=1&w=534", "image_alt": "Villa: Andet på Jagtvej 7, 9000 Aalborg", "primary_images": [ "https://nybolig.mindworking.eu/api/mediaData/mediaDataMediaPurposeId/SU1lZGlhRGF0YTp7Ik1lZGlhRGF0YUlkIjo4NDk4MjYyLCJNZWRpYVB1cnBvc2VJZCI6MjJ9/imageHash/baa51779e90f51404b6f8fa0dc9ae617/imageSize/Assets/inline/True?bgcolor=ffffff&dpi=72&jq=70&tp=rgb&fo=1&w=534", "https://nybolig.mindworking.eu/api/mediaData/mediaDataMediaPurposeId/SU1lZGlhRGF0YTp7Ik1lZGlhRGF0YUlkIjo4NDk4MjM4LCJNZWRpYVB1cnBvc2VJZCI6MjJ9/imageHash/5c57c613c765eda476b34be2b4149ca5/imageSize/Assets/inline/True?bgcolor=ffffff&dpi=72&jq=70&tp=rgb&fo=1&w=534", "https://nybolig.mindworking.eu/api/mediaData/mediaDataMediaPurposeId/SU1lZGlhRGF0YTp7Ik1lZGlhRGF0YUlkIjo4NDk4MjM2LCJNZWRpYVB1cnBvc2VJZCI6MjJ9/imageHash/c61cfb33f4a2570ad46dc1f681661f13/imageSize/Assets/inline/True?bgcolor=ffffff&dpi=72&jq=70&tp=rgb&fo=1&w=534" ], "is_shared_agricultural_case": false, "has_been_sold": false, "is_sale_in_progress": false, "is_rental": false, "is_portfolio_case": false, "street_address": "Jagtvej", "house_number": "7", "floor_side": "", "floor": 0, "rent": 0, "rent_monthly": "0", "cash_price": 7750000, "price": "7.750.000", "project_case_reserved": false, "new_label_event_end": "2026-06-24T11:32:28.427Z", "is_new": true, "new_price_label_event_end": "2026-06-02T00:00:00Z", "has_new_price": false, "show_offers_label": false, "is_active": false, "general_label_text": "", "open_house_text": "", "open_house_intro": "", "type": "Villa", "total_number_of_rooms": 5, "property_size": 1493, "plot_size_ha": 0.1, "living_space": 189, "farmbuildings_size": 62, "basement_size": 66, "energy_classification": "B", "has_charger": false, "has_balcony": false, "has_elevator": false, "pets_allowed": false, "flex_property": false, "from_url": "https://www.nybolig.dk/soegeresultat-boliger?displayNames=Aalborg&municipalityNames=Aalborg&caseCounts=2166" } ``` Each scraped property returns a detailed record with 48 fields covering identification, location, pricing, physical characteristics, and listing metadata: #### Identification & URLs | Field | Meaning | |---|---| | `ID` | Unique identifier for the property within Nybolig's database | | `Site Name` | Name of the Nybolig site/section the listing appears in | | `Case Number` | Official case or reference number for the property | | `URL` | Direct link to the property detail page on Nybolig.dk | #### Location & Address | Field | Meaning | |---|---| | `Address Display Name` | Full address as displayed to users | | `Address First Line` | Primary address line (street and house number) | | `Address Second Line` | Secondary address line (apartment/floor info) | | `Street Address` | Street name component | | `House Number` | Building number | | `Floor` | Floor level (e.g., 1st, 2nd, ground) | | `Floor Side` | Side designation (e.g., left, right) if applicable | | `Address City` | City name | | `Address Latitude` | Decimal latitude coordinate | | `Address Longitude` | Decimal longitude coordinate | | `Address WKT Point` | Well-Known Text (WKT) geometry for mapping integration | #### Images & Media | Field | Meaning | |---|---| | `Image URL` | Primary property image URL | | `Image Alt` | Alt text description for the image | | `Primary Images` | Collection of primary property image URLs | #### Pricing & Financial | Field | Meaning | |---|---| | `Price` | Total sale price (if for sale) | | `Cash Price` | Purchase price in cash value | | `Rent` | Rental amount (if rental property) | | `Rent Monthly` | Monthly rent figure | | `New Price Label Event End` | Expiration date for "new price" promotion label | | `Has New Price` | Boolean flag indicating recent price change | #### Property Type & Classification | Field | Meaning | |---|---| | `Type` | Property type (e.g., villa, apartment, cottage, farm) | | `Is Rental` | Boolean: true if property is available for rent | | `Is Portfolio Case` | Boolean: property is part of a portfolio/bulk listing | | `Is Shared Agricultural Case` | Boolean: shared agricultural property | | `Flex Property` | Boolean: flexible/adaptable property designation | #### Physical Characteristics | Field | Meaning | |---|---| | `Total Number Of Rooms` | Total room count (excluding bathrooms/hallways) | | `Property Size` | Total building size in square meters | | `Living Space` | Usable living area in square meters | | `Plot Size Ha` | Land plot size in hectares | | `Basement Size` | Basement or cellar area in square meters | | `Farmbuildings Size` | Outbuilding or farm structure size in square meters | | `Energy Classification` | Energy efficiency rating (e.g., A–G scale) | #### Amenities & Features | Field | Meaning | |---|---| | `Has Balcony` | Boolean: property includes a balcony | | `Has Elevator` | Boolean: building has an elevator | | `Has Charger` | Boolean: electric vehicle charger present | | `Pets Allowed` | Boolean: rental allows pets | #### Listing Status & Flags | Field | Meaning | |---|---| | `Is Active` | Boolean: listing is currently active | | `Is New` | Boolean: property is newly listed | | `Has Been Sold` | Boolean: property has been sold (historical data) | | `Is Sale In Progress` | Boolean: sale negotiations are underway | | `Project Case Reserved` | Boolean: property is reserved in a development project | | `Show Offers Label` | Boolean: display "offers" label to encourage bidding | | `General Label Text` | Custom label text (e.g., "Price reduced") | | `Open House Text` | Description of open house event | | `Open House Intro` | Introductory text for open house | | `New Label Event End` | Expiration date for "new listing" badge | *** ### How to Use 1. **Find Nybolig URLs** — Go to Nybolig.dk and apply your desired filters (location, price, type, amenities). Copy the resulting URL from your browser's address bar. 2. **Configure input** — Paste the URL(s) into the `urls` array. You can include multiple search result pages. 3. **Set item limits** — Adjust `max_items_per_url` based on your needs: - `20` for quick test runs - `50–100` for moderate datasets - `200` for comprehensive market analysis 4. **Enable fault tolerance** — Set `ignore_url_failures: true` if running multiple URLs to prevent a single failure from stopping the entire job. 5. **Run the scraper** — Launch the actor and monitor the run log for progress. 6. **Export data** — Download results as JSON, CSV, or Excel for analysis in spreadsheets, databases, or BI tools. **Best practices:** - Use filtered Nybolig search URLs to target specific regions or property types, reducing unnecessary data collection. - Schedule runs during off-peak hours to minimize server load. - Validate geolocation data (latitude/longitude) before mapping. *** ### Use Cases & Business Value - **Market analysis:** Track price trends, property sizes, and availability by city or neighborhood - **Investment research:** Identify undervalued properties, analyze rental yields, and monitor competitor listings - **Lead generation:** Build prospect lists for real estate agents and property developers - **Academic research:** Study housing market dynamics, affordability, and energy efficiency trends - **Real estate platforms:** Aggregate and republish Danish property data with proper attribution The Nybolig Property Search Scraper transforms hours of manual data entry into minutes, delivering market-ready datasets that inform strategy, pricing, and investment decisions. *** ### Conclusion The **Nybolig Property Search Scraper** is the fastest way to extract structured Danish real estate data from Nybolig.dk. With 48 detailed fields and support for large-scale collection, it empowers investors, analysts, and developers to make data-driven decisions in the Danish property market. Start scraping today and unlock insights that manual browsing cannot match. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the property list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. ## `ignore_url_failures` (type: `boolean`): If true, the scraper will continue running even if some URLs fail to be scraped. ## `max_items_per_url` (type: `integer`): The maximum number of items to scrape per URL. ## Actor input object example ```json { "urls": [ "https://www.nybolig.dk/soegeresultat-boliger?displayNames=Aalborg&municipalityNames=Aalborg&caseCounts=2166" ], "ignore_url_failures": true, "max_items_per_url": 20 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "urls": [ "https://www.nybolig.dk/soegeresultat-boliger?displayNames=Aalborg&municipalityNames=Aalborg&caseCounts=2166" ], "ignore_url_failures": true, "max_items_per_url": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("stealth_mode/nybolig-property-search-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "urls": ["https://www.nybolig.dk/soegeresultat-boliger?displayNames=Aalborg&municipalityNames=Aalborg&caseCounts=2166"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/nybolig-property-search-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "urls": [ "https://www.nybolig.dk/soegeresultat-boliger?displayNames=Aalborg&municipalityNames=Aalborg&caseCounts=2166" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/nybolig-property-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/nybolig-property-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Nybolig Property Search Scraper", "description": "Scrape comprehensive property listings from Nybolig.dk with 48 detailed fields. Perfect for real estate analysts, investors, and researchers gathering Danish housing market data — addresses, prices, property features, and more in structured format.", "version": "0.0", "x-build-id": "CdifUhXYu1zfpUPl6" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~nybolig-property-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-nybolig-property-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/stealth_mode~nybolig-property-search-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-nybolig-property-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/stealth_mode~nybolig-property-search-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-nybolig-property-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "urls": { "title": "URLs of the property list urls to scrape", "type": "array", "description": "Add the URLs of the property list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.", "items": { "type": "string" } }, "ignore_url_failures": { "title": "Continue running even if some URLs fail to be scraped", "type": "boolean", "description": "If true, the scraper will continue running even if some URLs fail to be scraped." }, "max_items_per_url": { "title": "Max items per URL", "type": "integer", "description": "The maximum number of items to scrape per URL." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```