# 4zida Scraper - Serbian Real Estate Listings (`studio-amba/4zida-scraper`) Actor Scrape property listings from 4zida.rs, Serbia's largest real estate portal. Extract prices, locations, areas, rooms, images, and details for apartments, houses, and land. Supports sale and rent listings. No login needed. - **URL**: https://apify.com/studio-amba/4zida-scraper.md - **Developed by:** [Studio Amba](https://apify.com/studio-amba) (community) - **Categories:** Real estate - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## 4zida Scraper - Serbian Real Estate Listings Scrape property listings from [4zida.rs](https://www.4zida.rs), Serbia's largest real estate portal. Extract detailed data from apartments, houses, land, offices, and garages — for sale or rent. No login or cookies needed. ### What data can you extract? For each listing the scraper returns: | Field | Description | |-------|------------| | `listingTitle` | Property listing title | | `price` | Listing price | | `currency` | EUR or RSD | | `area` | Property area in square meters | | `rooms` | Number of rooms | | `floor` | Floor number | | `location` | City, district, or neighbourhood | | `propertyType` | apartment, house, land, office, or garage | | `transactionType` | sale or rent | | `imageUrl` | Primary listing photo URL | | `url` | Direct link to the listing on 4zida.rs | | `listingDescription` | Property description text | | `scrapedAt` | ISO 8601 timestamp | ### How to scrape 4zida.rs data 1. Go to the [4zida Scraper](https://apify.com/studio-amba/4zida-scraper) page on Apify. 2. Click **Start** to open the actor configuration. 3. Enter a **Search Location** — any Serbian city name like `Beograd`, `Novi Sad`, `Niš`, or `Kragujevac`. 4. Choose a **Listing Type** — `sale` (Prodaja) or `rent` (Izdavanje). 5. Choose a **Property Type** — apartment, house, land, office, or garage. 6. Set **Max Results** to control how many listings you want. 7. Click **Start** and wait for the run to finish. 8. Download your data as JSON, CSV, Excel, or connect via API. #### Example input ```json { "searchQuery": "Beograd", "listingType": "sale", "propertyType": "apartment", "maxResults": 50 } ```` #### Example output ```json { "listingTitle": "Jednosoban stan, Beograd na vodi", "price": 145000, "currency": "EUR", "area": 30, "rooms": 1, "floor": "5", "location": "Beograd Na Vodi Savski Venac Beograd", "propertyType": "apartment", "transactionType": "sale", "imageUrl": "https://img.4zida.rs/...", "url": "https://www.4zida.rs/prodaja-stanova/beograd-na-vodi-savski-venac-beograd/jednosoban-stan/67474b0a72ae77784305c3e3", "listingDescription": "Luksuzan jednosoban stan u kompleksu Beograd na vodi...", "scrapedAt": "2026-06-09T12:00:00.000Z" } ``` ### Supported cities The scraper works with all cities and municipalities on 4zida.rs, including: - **Beograd** (Belgrade) — capital, largest market - **Novi Sad** — second largest city - **Niš** — southern Serbia hub - **Kragujevac** — central Serbia - **Subotica**, **Zrenjanin**, **Pančevo**, **Čačak**, **Novi Pazar**, **Kraljevo**, **Smederevo**, **Leskovac**, **Valjevo**, **Kruševac**, **Vranje**, **Šabac**, **Užice**, **Sombor**, **Požarevac**, **Pirot** You can also provide direct URLs to specific search result pages or individual listing pages via the **Start URLs** input. ### Property types | Input value | Serbian name | Description | |------------|-------------|-------------| | `apartment` | Stan | Apartments and flats | | `house` | Kuća | Houses and villas | | `land` | Plac | Building plots and agricultural land | | `office` | Poslovni prostor | Commercial and office space | | `garage` | Garaža | Garages and parking spots | ### Proxy configuration Residential proxies are recommended for reliable scraping. The actor uses Apify residential proxies by default when running on the platform. If you experience blocks, try using Serbian IP addresses for the best results. ### How much does it cost? The actor uses Playwright with Chromium to render pages, which requires more compute than simple HTTP scrapers. Typical usage: | Listings | Estimated cost | |----------|---------------| | 50 | ~$0.10 | | 200 | ~$0.30 | | 1,000 | ~$1.20 | Costs depend on page complexity, number of retries, and proxy usage. ### Use cases - **Real estate market research** — track prices across Serbian cities - **Investment analysis** — monitor property prices in Belgrade and Novi Sad - **Price comparison** — compare listings across different platforms - **Academic research** — analyze housing market trends in Serbia - **Relocation planning** — search for rentals in specific neighbourhoods - **Portfolio monitoring** — track changes in listed properties ### Tips for best results 1. **Start with a specific city** rather than scraping all of Serbia — results are faster and more relevant. 2. **Use Start URLs** for advanced searches — apply filters on 4zida.rs, copy the URL, and paste it as a Start URL. 3. **Set reasonable limits** — start with 20-50 results to test, then scale up. 4. **Residential proxies** are included and recommended. Datacenter proxies may get blocked. ### About 4zida.rs 4zida.rs is Serbia's leading real estate marketplace with over 34,000 active apartment listings and coverage across all major Serbian cities. The platform supports property sales, rentals, and new construction listings. The name "4 zida" means "4 walls" in Serbian. ### Integrations Connect 4zida Scraper with your existing tools: - **Google Sheets** — export data directly to spreadsheets - **Slack / Email** — get notifications when new listings match your criteria - **Zapier / Make** — automate workflows with scraped data - **API** — access results programmatically via the Apify API - **Webhooks** — trigger actions when a run completes ### Legal disclaimer This actor is provided for informational and research purposes. Users are responsible for complying with applicable laws and the target website's terms of service when using this tool. Always use scraped data ethically and responsibly. # Actor input Schema ## `searchQuery` (type: `string`): City or region to search for properties, e.g., 'Beograd', 'Novi Sad', 'Niš', 'Kragujevac'. Defaults to 'Beograd' if empty. ## `startUrls` (type: `array`): 4zida.rs search or property detail URLs. Overrides searchQuery if provided. ## `listingType` (type: `string`): Search for properties for sale or for rent. ## `propertyType` (type: `string`): Type of property to search for. ## `maxResults` (type: `integer`): Maximum number of property listings to scrape. ## `proxyConfiguration` (type: `object`): Residential proxies recommended for best results. Serbian IP addresses help avoid blocks. ## Actor input object example ```json { "searchQuery": "Beograd", "startUrls": [ { "url": "https://www.4zida.rs/prodaja-stanova/beograd" } ], "listingType": "sale", "propertyType": "apartment", "maxResults": 20, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "searchQuery": "Beograd", "startUrls": [ { "url": "https://www.4zida.rs/prodaja-stanova/beograd" } ], "maxResults": 20, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("studio-amba/4zida-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 = { "searchQuery": "Beograd", "startUrls": [{ "url": "https://www.4zida.rs/prodaja-stanova/beograd" }], "maxResults": 20, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("studio-amba/4zida-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 '{ "searchQuery": "Beograd", "startUrls": [ { "url": "https://www.4zida.rs/prodaja-stanova/beograd" } ], "maxResults": 20, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call studio-amba/4zida-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=studio-amba/4zida-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "4zida Scraper - Serbian Real Estate Listings", "description": "Scrape property listings from 4zida.rs, Serbia's largest real estate portal. Extract prices, locations, areas, rooms, images, and details for apartments, houses, and land. Supports sale and rent listings. No login needed.", "version": "0.1", "x-build-id": "eqKkqajGr3RYijI6K" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/studio-amba~4zida-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-studio-amba-4zida-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/studio-amba~4zida-scraper/runs": { "post": { "operationId": "runs-sync-studio-amba-4zida-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/studio-amba~4zida-scraper/run-sync": { "post": { "operationId": "run-sync-studio-amba-4zida-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQuery": { "title": "Search Location", "type": "string", "description": "City or region to search for properties, e.g., 'Beograd', 'Novi Sad', 'Niš', 'Kragujevac'. Defaults to 'Beograd' if empty." }, "startUrls": { "title": "Start URLs", "type": "array", "description": "4zida.rs search or property detail URLs. Overrides searchQuery if provided.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "listingType": { "title": "Listing Type", "enum": [ "sale", "rent" ], "type": "string", "description": "Search for properties for sale or for rent.", "default": "sale" }, "propertyType": { "title": "Property Type", "enum": [ "apartment", "house", "land", "office", "garage" ], "type": "string", "description": "Type of property to search for.", "default": "apartment" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of property listings to scrape.", "default": 100 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Residential proxies recommended for best results. Serbian IP addresses help avoid blocks." } } }, "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 } } } } } } } } } } ```