# European Real Estate Aggregator (`delightful_unicorn/european-real-estate-aggregator`) Actor The first Apify actor for European residential real estate. Scrape listings from Idealista and Immobiliare.it, run market analytics, compare cross-platform prices, and batch-scan multiple cities. - **URL**: https://apify.com/delightful\_unicorn/european-real-estate-aggregator.md - **Developed by:** [Alessandro Amato](https://apify.com/delightful_unicorn) (community) - **Categories:** Lead generation, Automation, Real estate - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.50 / 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. 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 ## European Real Estate Aggregator **The first Apify actor for Central European residential real estate.** Scrapes listings from **Sreality.cz** (Czech Republic — 100K+ active listings) and runs market analytics, city comparisons, and batch scans. While Western EU portals like Idealista and Immobiliare.it are locked behind DataDome, Sreality.cz offers rich structured data via SSR — making reliable scraping possible without browser automation. ### Features - **Search listings** by Czech city with pagination - **Listing details** — full description, price, sqm, floor, condition, photos, agency, GPS coordinates - **Market summary** ⭐ — average/median price, price-per-sqm, price histogram, room distribution, district-level price map - **Multi-city scan** — batch process 2–10 cities in one run with error isolation - **City comparison** — rank cities by avg price-per-sqm and surface the most/least expensive markets - **No API key required** — pure HTTP scraping with zero external dependencies ### Supported Markets | Source | Country | Listings | Access | |--------|---------|----------|--------| | Sreality.cz | Czech Republic | 100,000+ | HTTP SSR (stable) | *Planned expansions:* Otodom.pl (Poland), Nehnutelnosti.sk (Slovakia) — pending proxy testing. ### Actions #### `searchListings` Search for-sale apartments by city. **Input:** ```json { "action": "searchListings", "city": "Praha", "limit": 25 } ```` **Output fields per listing:** - `listingId`, `title`, `price`, `pricePerSqm`, `currency` - `sqm`, `rooms`, `location`, `city`, `district`, `street` - `latitude`, `longitude`, `thumbnail`, `url` #### `getListingDetails` Get full details for a specific Sreality listing. **Input:** ```json { "action": "getListingDetails", "listingId": "3047198796" } ``` #### `marketSummary` ⭐ (Recommended) Run full market intelligence on a city. **Input:** ```json { "action": "marketSummary", "city": "Praha", "limit": 50 } ``` **Output example:** ```json { "city": "Praha", "listingsAnalyzed": 50, "avgPrice": 8450000, "medianPrice": 7900000, "avgPricePerSqm": 145800, "avgSqm": 62, "priceRange": { "min": 3200000, "max": 24500000 }, "priceHistogram": [ { "range": "0-3M", "count": 3 }, { "range": "3-5M", "count": 12 }, { "range": "5-7M", "count": 18 }, { "range": "7-10M", "count": 10 }, { "range": "10M+", "count": 7 } ], "roomDistribution": { "1+kk": 5, "2+kk": 18, "3+kk": 20, "4+kk": 7 }, "districtPriceMap": [ { "district": "Praha 1", "avgPricePerSqm": 198000, "listings": 8 }, { "district": "Praha 2", "avgPricePerSqm": 156000, "listings": 12 } ], "topListings": [...] } ``` #### `multiCityScan` Batch scan multiple cities. **Input:** ```json { "action": "multiCityScan", "cities": "Praha, Brno, Ostrava, Plzen", "limit": 25 } ``` #### `compareCities` Rank cities by real estate affordability/expensive-ness. **Input:** ```json { "action": "compareCities", "cities": "Praha, Brno, Ostrava", "limit": 30 } ``` ### Input Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `action` | string | yes | — | One of the 5 actions above | | `city` | string | no | `Praha` | City to search (Czech names) | | `cities` | string | no | — | Comma-separated for batch/compare | | `listingId` | string | no | — | Sreality listing ID | | `listingUrl` | string | no | — | Full Sreality URL (alt to ID) | | `limit` | integer | no | `25` | Max listings (1–100) | ### Data Methodology - **Source:** `sreality.cz` search pages + detail API - **SSR extraction:** Parses `__NEXT_DATA__` JSON embedded in Next.js HTML - **Pagination:** `?strana={page}` with 20 listings per page - **Rate limiting:** 500ms delay between page requests - **Detail API:** `https://www.sreality.cz/api/cs/v2/estates/{id}` ### Pricing **Pay Per Event** - Start event: **$0.0005** - Result event: **$0.0005** Approx. **$1 per 1,000 listings analyzed**. ### Use Cases - **Real Estate Investors:** Compare price-per-sqm across Czech cities before buying - **Relocation Agencies:** Batch-scan multiple cities for client budgets - **Market Researchers:** Track district-level price trends in Prague - **Proptech Startups:** Seed your database with structured Czech listings ### Disclaimer This actor extracts publicly available data from Sreality.cz. Always comply with the portal’s Terms of Service. The market insights are statistical estimates based on active listings and should be validated with professional appraisal data. # Actor input Schema ## `action` (type: `string`): What do you want to do? ## `city` (type: `string`): City to search. Use Czech city names: Praha, Brno, Ostrava, Plzen, Liberec. ## `cities` (type: `string`): Comma-separated cities for multiCityScan or compareCities (e.g. Praha, Brno, Ostrava). ## `listingId` (type: `string`): Sreality.cz listing ID for getListingDetails. ## `listingUrl` (type: `string`): Full Sreality.cz listing URL (optional alternative to listingId). ## `limit` (type: `integer`): Max listings to fetch per city (1-100). ## Actor input object example ```json { "action": "marketSummary", "city": "Praha", "limit": 25 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("delightful_unicorn/european-real-estate-aggregator").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 = {} # Run the Actor and wait for it to finish run = client.actor("delightful_unicorn/european-real-estate-aggregator").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 '{}' | apify call delightful_unicorn/european-real-estate-aggregator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delightful_unicorn/european-real-estate-aggregator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "European Real Estate Aggregator", "description": "The first Apify actor for European residential real estate. Scrape listings from Idealista and Immobiliare.it, run market analytics, compare cross-platform prices, and batch-scan multiple cities.", "version": "1.0", "x-build-id": "fwlsLay3LLsGe5X0f" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delightful_unicorn~european-real-estate-aggregator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delightful_unicorn-european-real-estate-aggregator", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delightful_unicorn~european-real-estate-aggregator/runs": { "post": { "operationId": "runs-sync-delightful_unicorn-european-real-estate-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delightful_unicorn~european-real-estate-aggregator/run-sync": { "post": { "operationId": "run-sync-delightful_unicorn-european-real-estate-aggregator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "action" ], "properties": { "action": { "title": "Action", "enum": [ "searchListings", "getListingDetails", "marketSummary", "multiCityScan", "compareCities" ], "type": "string", "description": "What do you want to do?", "default": "marketSummary" }, "city": { "title": "City", "type": "string", "description": "City to search. Use Czech city names: Praha, Brno, Ostrava, Plzen, Liberec.", "default": "Praha" }, "cities": { "title": "Cities (batch/comma-separated)", "type": "string", "description": "Comma-separated cities for multiCityScan or compareCities (e.g. Praha, Brno, Ostrava)." }, "listingId": { "title": "Listing ID", "type": "string", "description": "Sreality.cz listing ID for getListingDetails." }, "listingUrl": { "title": "Listing URL", "type": "string", "description": "Full Sreality.cz listing URL (optional alternative to listingId)." }, "limit": { "title": "Limit", "minimum": 1, "maximum": 100, "type": "integer", "description": "Max listings to fetch per city (1-100).", "default": 25 } } }, "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 } } } } } } } } } } ```