# Edc.dk Property Search Scraper (`stealth_mode/edc-dk-property-search-scraper`) Actor Scrape property listings from EDC.dk with precision. This scraper extracts search results including property details, prices, locations, images, and 47+ fields — perfect for real estate professionals, market researchers, and property aggregators. - **URL**: https://apify.com/stealth\_mode/edc-dk-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 ## EDC.dk Property Scraper: Extract Danish Real Estate Data at Scale --- ### What Is EDC.dk? EDC.dk is one of Denmark's leading property search platforms, offering access to thousands of residential and commercial real estate listings across Danish municipalities. The platform aggregates property data from various sources, making it a valuable resource for buyers, sellers, investors, and market analysts. Extracting listing data manually is inefficient; the **EDC.dk Property Scraper** automates this process, delivering structured property records from search result pages. --- ### Overview The **EDC.dk Property Scraper** extracts property listings from EDC.dk search result pages, converting individual property cards into complete, machine-readable records. It is designed for: - **Real estate professionals** tracking market inventory and pricing trends - **Property investors** analyzing markets across Danish regions - **Market researchers** building datasets on property availability and values - **Aggregator platforms** feeding property data into third-party portals - **Data analysts** conducting comparative market analysis (CMA) Key strengths include high-volume extraction (up to 200 items per URL), flexible municipality and region filtering, robust error handling via `ignore_url_failures`, and comprehensive property metadata spanning physical characteristics, pricing, and media assets. --- ### Input Format The scraper accepts a JSON configuration object: ```json { "urls": [ "https://www.edc.dk/soeg/?pageNr=2&kommune=Ballerup" ], "ignore_url_failures": true, "max_items_per_url": 200 } ```` | Field | Type | Description | |---|---|---| | `urls` | Array | Direct links to EDC.dk property search result pages. URLs may include filters (page number, municipality, property type). One URL per entry. | | `max_items_per_url` | Integer | Maximum number of property listings to extract per URL (1–200). Default: `20`. Use `200` for comprehensive market coverage. | | `ignore_url_failures` | Boolean | If `true`, the scraper continues running even if individual URLs fail to load. Recommended: `true` for large batches. | #### URL Construction Tips EDC.dk uses query parameters to filter results: - `pageNr=2` — Page number of search results - `kommune=Ballerup` — Danish municipality code (e.g., Ballerup, Copenhagen, Aarhus) You can build URLs directly from EDC.dk's search interface or construct them programmatically for bulk region coverage. *** ### Output Format **Sample output** ```json { "id": 2447492, "case_guid": "51c0f16c-f94a-49cc-bbb9-e124a40dd44e", "case_number": "29704283", "case_type_group": "Private", "case_classification": "Sale", "trade_classification": "None", "estate_type": "f507e41c-ee54-473f-b324-5b620716a363", "estate_type_name": "Sommerhus", "source": "EDC", "source_model": "Edc", "agency_guid": "f86683ee-72ed-4aca-aa0a-88f48fbbff2f", "address": "Gefionvej 53", "is_sold": false, "is_rented": false, "zip_code": "2740", "city": "Skovlunde", "status_change_date": "2026-01-27T11:27:10.133", "is_advertised": false, "is_edc_case": true, "case_status": "None", "rooms": { "value": 2.0, "unit_code": "ROM", "unit_text": "rum", "description": "2" }, "living_area": { "value": 51.0, "unit_code": "MKT", "unit_text": "m²", "description": "51 m²" }, "price": { "value": 1595000.0, "unit_code": "DKK", "unit_text": "kr.", "description": "1.595.000 kr." }, "area_land": { "value": 450.0, "unit_code": "MKT", "unit_text": "m²", "description": "450 m²" }, "area_floor": { "value": 0.0, "unit_code": "MKT", "unit_text": "m²", "description": "0 m²" }, "rent": { "value": 0.0, "unit_code": "DKK", "unit_text": "kr.", "description": "0 kr." }, "year_build": 1978, "cash_price_change": { "value": 0.0, "unit_code": "DKK", "unit_text": "kr.", "description": "0 kr." }, "vignet_custom_text": "", "is_new_case": false, "has_new_price": false, "image_path": "https://billeder.edc.dk/edcmedia/2026/05-May/25/95c9bbf1-c162-493e-a1e5-299c144ab818_Size210x140.jpg", "date_open_house": "2026-06-11T10:00:00", "date_open_house_end": "2026-06-11T17:00:00", "open_house_activity_subscription": true, "open_house_activity_id": "0b781307-a145-4cfe-98a6-5a8f8441845b", "geo_coordinates": { "latitude": 55.70553323963271, "longitude": 12.38630399237 }, "is_contract_signed": false, "business_return_percentage": { "value": 0.0, "unit_code": "", "unit_text": "%", "description": "0,00 %" }, "rent_year": { "value": 0.0, "unit_code": "DKK", "unit_text": "kr.", "description": "0 kr." }, "url_path": "/alle-boliger/sommerhus/2740-skovlunde/gefionvej-53/29704283/", "images": [ { "src": "https://billeder.edc.dk/edcmedia/2026/05-May/25/95c9bbf1-c162-493e-a1e5-299c144ab818_Size300x200.jpg", "height": 200, "width": 300 }, { "src": "https://billeder.edc.dk/edcmedia/2026/05-May/25/95c9bbf1-c162-493e-a1e5-299c144ab818_Size400x256.jpg", "height": 256, "width": 400 }, { "src": "https://billeder.edc.dk/edcmedia/2026/05-May/25/95c9bbf1-c162-493e-a1e5-299c144ab818_Size620x414.jpg", "height": 414, "width": 620 }, { "src": "https://billeder.edc.dk/edcmedia/2026/05-May/25/95c9bbf1-c162-493e-a1e5-299c144ab818_Size210x140.jpg", "height": 140, "width": 210 }, { "src": "https://billeder.edc.dk/edcmedia/2026/05-May/25/95c9bbf1-c162-493e-a1e5-299c144ab818_Size1080x720crop.jpg", "height": 720, "width": 1080 } ], "view_count": 0, "view_count_type": "ViewedWithinLastWeek", "show_view_count": false, "can_be_followed": true, "active_project_cases": 0, "total_project_cases": 0, "is_project": false, "from_url": "https://www.edc.dk/soeg/?pageNr=2&kommune=Ballerup" } ``` Each scraped property returns a detailed record with 47+ fields: #### Identification & Source | Field | Meaning | |---|---| | `ID` | Unique identifier for the property within EDC.dk | | `Case Guid` | Global unique identifier (UUID) for the listing | | `Case Number` | EDC.dk case/reference number | | `Source` | Data origin (e.g., real estate agency, private seller) | | `Source Model` | Classification of source type | | `Agency Guid` | GUID of the listing agency or broker | | `URL Path` | Relative path to the property detail page | #### Property Classification | Field | Meaning | |---|---| | `Case Type Group` | Broad category (residential, commercial, land, etc.) | | `Case Classification` | Specific classification (apartment, house, villa, etc.) | | `Trade Classification` | Market segment classification | | `Estate Type` | Code for property type | | `Estate Type Name` | Human-readable property type name | #### Location & Address | Field | Meaning | |---|---| | `Address` | Full street address of the property | | `Zip Code` | Danish postal code (postnummer) | | `City` | Municipality or city name | | `Geo Coordinates` | Latitude/longitude for mapping and distance calculations | #### Property Specifications | Field | Meaning | |---|---| | `Rooms` | Number of rooms (integer) | | `Living Area` | Usable floor space in m² | | `Area Floor` | Total floor area in m² | | `Area Land` | Land plot size in m² (for detached properties) | | `Year Build` | Construction year (integer) | #### Financial Information | Field | Meaning | |---|---| | `Price` | Asking price in Danish krone (DKK) | | `Rent` | Monthly rental price (for rental properties) | | `Rent Year` | Annual rental yield or rent amount | | `Cash Price Change` | Price change from previous listing (absolute value) | | `Business Return Percentage` | Estimated return on investment (ROI) percentage | #### Listing Status & Dates | Field | Meaning | |---|---| | `Is Sold` | Boolean flag indicating if property has sold | | `Is Rented` | Boolean flag for rental status | | `Case Status` | Current listing status (active, sold, archived, etc.) | | `Status Change Date` | Timestamp of last status change | | `Is New Case` | Boolean flag for newly listed properties | | `Has New Price` | Boolean flag if price was recently updated | | `Is Advertised` | Boolean flag for featured/promoted listings | | `Is EDC Case` | Boolean flag for properties listed directly via EDC.dk | | `Is Contract Signed` | Boolean flag indicating closed transactions | #### Open House & Viewings | Field | Meaning | |---|---| | `Date Open House` | Scheduled open house start date/time | | `Date Open House End` | Open house end date/time | | `Open House Activity Subscription` | Subscription ID for viewing notifications | | `Open House Activity ID` | Activity identifier for the open house event | | `View Count` | Number of times the listing has been viewed | | `View Count Type` | Classification of view metrics | | `Show View Count` | Boolean flag to display view count publicly | #### Media & Visuals | Field | Meaning | |---|---| | `Image Path` | URL path to primary property image | | `Images` | Array of all property image URLs | #### Project & Investment Properties | Field | Meaning | |---|---| | `Is Project` | Boolean flag for development/construction projects | | `Active Project Cases` | Number of active sub-cases in a project | | `Total Project Cases` | Total number of project phases | #### Additional Metadata | Field | Meaning | |---|---| | `Is Contract Signed` | Indicates if the transaction has been finalized | | `Can Be Followed` | Boolean flag to allow watch-list subscriptions | | `Vignet Custom Text` | Custom promotional text or banner | *** ### How to Use 1. **Identify search URLs** — Navigate to EDC.dk, apply filters (municipality, property type, price range), and copy the result page URL from your browser. 2. **Configure input** — Paste one or more URLs into the `urls` array. For regional market analysis, add multiple pages or municipalities. 3. **Set extraction limits** — Adjust `max_items_per_url`: - Use `20–50` for targeted single-page scrapes - Use `200` (maximum) for comprehensive market snapshots 4. **Enable error handling** — Set `ignore_url_failures: true` when scraping many URLs to prevent interruptions. 5. **Run the scraper** — Start the actor and monitor progress via the log console. 6. **Export results** — Download output as JSON, CSV, or Excel for analysis in spreadsheets, databases, or BI tools. **Troubleshooting:** - If no results are returned, verify the URL is a search result page (not a detail page). - For filter-specific data, customize the URL with query parameters before adding to `urls`. - If results seem incomplete, increase `max_items_per_url` or run separate scrapes per page. *** ### Use Cases & Business Value - **Market analysis:** Track property availability, pricing trends, and inventory levels by municipality - **Investment screening:** Identify underpriced properties or emerging markets using price and ROI fields - **Competitive intelligence:** Monitor competitor listings, open house schedules, and promotional activity - **Lead generation:** Extract property owner and agent data for outreach campaigns - **Data warehousing:** Feed structured records into CRM, analytics, or real estate management systems - **Research & academia:** Build datasets for thesis work on Danish property markets The EDC.dk Property Scraper converts unstructured search results into actionable business intelligence, enabling professionals to make faster, data-driven decisions. *** ### Conclusion The **EDC.dk Property Scraper** is an essential tool for anyone working in Danish real estate. With 47+ data fields per property and flexible filtering options, it delivers comprehensive market intelligence that would take days to gather manually. Whether you're an agent, investor, researcher, or analyst, this scraper accelerates data collection and unlocks insights into Denmark's dynamic property market. # 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.edc.dk/soeg/?pageNr=2&kommune=Ballerup" ], "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.edc.dk/soeg/?pageNr=2&kommune=Ballerup" ], "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/edc-dk-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.edc.dk/soeg/?pageNr=2&kommune=Ballerup"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/edc-dk-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.edc.dk/soeg/?pageNr=2&kommune=Ballerup" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/edc-dk-property-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/edc-dk-property-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Edc.dk Property Search Scraper", "description": "Scrape property listings from EDC.dk with precision. This scraper extracts search results including property details, prices, locations, images, and 47+ fields — perfect for real estate professionals, market researchers, and property aggregators.", "version": "0.0", "x-build-id": "ya3iTz5ZRMCZ8z3xB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~edc-dk-property-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-edc-dk-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/stealth_mode~edc-dk-property-search-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-edc-dk-property-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/stealth_mode~edc-dk-property-search-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-edc-dk-property-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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 } } } } } } } } } } ```