# Zoopla Propertydetails Spider (`getdataforme/zoopla-propertydetails-spider`) Actor Extract comprehensive property data from Zoopla.co.uk listings, including prices, features, images, and agent details. Ideal for real estate analysis, investment decisions, and automated workflows. Reliable, fast, and outputs clean JSON for easy integration. - **URL**: https://apify.com/getdataforme/zoopla-propertydetails-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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. 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 ### Description Extract comprehensive property data from Zoopla.co.uk listings, including prices, features, images, and agent details. Ideal for real estate analysis, investment decisions, and automated workflows. Reliable, fast, and outputs clean JSON for easy integration. --- ## Zoopla Propertydetails Spider ### Introduction The Zoopla Propertydetails Spider is a powerful Apify Actor designed to extract detailed property information from Zoopla.co.uk listings. It efficiently scrapes comprehensive data such as property details, pricing, features, images, and agent information from specified URLs, enabling users to gather valuable real estate insights quickly and reliably. This tool is ideal for professionals needing structured data for market analysis, investment decisions, or automated workflows. ### Features - **Comprehensive Data Extraction**: Captures key property attributes including price, bedrooms, bathrooms, location coordinates, and features. - **High Reliability**: Built with robust error handling to ensure consistent data retrieval from Zoopla's dynamic pages. - **Flexible Input**: Accepts multiple URLs for batch processing, with customizable item limits to control output volume. - **Structured Output**: Delivers clean, JSON-formatted data ready for integration into databases, analytics tools, or reports. - **Performance Optimized**: Utilizes efficient scraping techniques to minimize runtime while respecting site policies. - **Agent and Contact Info**: Includes details about listing agents, such as names, phone numbers, and IDs for follow-up. - **Image and Media Support**: Extracts high-quality image URLs for visual property assessments. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|---------|----------|-----------------------------------------------------------------------------|---------| | ItemLimit | integer | No | Specifies the maximum number of items to process. Default is 20. | 20 | | Urls | array | Yes | An array of URLs to scrape property details from. Must be valid HTTP/HTTPS URLs. | ["https://www.zoopla.co.uk/for-sale/details/72529283/?search_identifier=981b3921dcdf7acf59f815957ba4a861da68b9e91e6115460efce227fb92417f"] | ### Example Usage #### Input Configuration ```json { "ItemLimit": 20, "Urls": [ "https://www.zoopla.co.uk/for-sale/details/72529283/?search_identifier=981b3921dcdf7acf59f815957ba4a861da68b9e91e6115460efce227fb92417f" ] } ```` #### Output Example ```json [ { "id": "72529283", "url": "https://www.zoopla.co.uk/for-sale/details/72529283/?search_identifier=981b3921dcdf7acf59f815957ba4a861da68b9e91e6115460efce227fb92417f", "title": "Chesterfield Gardens, London W1K, 2 bed flat for sale, £3,850,000 - Zoopla", "description": "2 bed flat for sale in Chesterfield Gardens, London W1K, selling for £3,850,000 from Savills - Mayfair & St James's. See property details on Zoopla or browse all our range of properties in Chesterfield Gardens, London W1K.", "type": "flat", "status": "for_sale", "price": 3850000, "bedrooms": 2, "bathrooms": 2, "area": { "size": "", "unit": "sq_ft" }, "address": "Chesterfield Gardens, London W1K", "city": "London", "state": "London", "zipCode": "W1K 1HA", "coordinates": { "lat": 51.506829, "lng": -0.150256 }, "features": [ "Views towards Hyde Park", "24-Hour Porter", "Lift", "Private Balcony", "Lateral living", "EPC Rating = C" ], "images": [ "https://lc.zoocdn.com/11d1e046f449955e92a47d87feeae181ce9ae1c0.jpg", "https://lc.zoocdn.com/f90bfde84a761e67f6ed897aeb166eed6ae02c14.jpg", "https://lc.zoocdn.com/e72a0585299a8b0717102b09d6b411a0dde360d1.jpg", "https://lc.zoocdn.com/e7e072fe57663bf585cdb1fd9a439f9af25749b2.jpg", "https://lc.zoocdn.com/b017990dd2e40ff3dd874872c5257400ccc3a35c.jpg", "https://lc.zoocdn.com/1148a86789db376e05bb5f3cd25dd12f3a1788f2.jpg", "https://lc.zoocdn.com/f8c72e8309d5fb1269babf104fb091b7b6d9ef9e.jpg", "https://lc.zoocdn.com/0d5960fc2c8962c5ccd1de9e5c147bc392f3968d.jpg" ], "agent_id": "79949", "agent_name": "Savills - Mayfair & St James's", "agent_phone": "020 8022 3362", "actor_id": "b8QAPhX5HRYMUl9IV", "run_id": "Tmf52UQ3WrDKhWVcu" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather data on property prices, features, and locations to identify trends in real estate markets. - **Competitive Intelligence**: Monitor competitor listings and pricing strategies for informed business decisions. - **Price Monitoring**: Track property values over time to support investment portfolios or rental yield calculations. - **Content Aggregation**: Build databases of property listings for websites, apps, or marketing campaigns. - **Academic Research**: Collect structured data for studies on housing affordability, urban development, or economic indicators. - **Business Automation**: Integrate with CRM systems or dashboards for automated lead generation and property alerts. ### Installation and Usage 1. Search for "Zoopla Propertydetails Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters (e.g., URLs and item limit). 4. Click "Start" to begin extraction. 5. Monitor progress in the log. 6. Export results in your preferred format (JSON, CSV, Excel). ### Output Format The Actor outputs data in JSON format, with each item representing a scraped property. Key fields include: `id` (unique property identifier), `url` (source link), `title` and `description` (listing details), `price`, `bedrooms`, `bathrooms`, `address`, `coordinates` (latitude and longitude), `features` (array of property amenities), `images` (array of image URLs), and agent information (`agent_name`, `agent_phone`). This structured format ensures easy parsing and integration. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! # Actor input Schema ## `ItemLimi` (type: `integer`): Specifies the maximum number of items to process. ## `Urls` (type: `array`): The urls for the spider. ## Actor input object example ```json { "ItemLimi": 20, "Urls": [ "https://www.zoopla.co.uk/for-sale/details/72529283/?search_identifier=981b3921dcdf7acf59f815957ba4a861da68b9e91e6115460efce227fb92417f" ] } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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 = { "ItemLimi": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/zoopla-propertydetails-spider").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 = { "ItemLimi": 20 } # Run the Actor and wait for it to finish run = client.actor("getdataforme/zoopla-propertydetails-spider").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 '{ "ItemLimi": 20 }' | apify call getdataforme/zoopla-propertydetails-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/zoopla-propertydetails-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Zoopla Propertydetails Spider", "description": "Extract comprehensive property data from Zoopla.co.uk listings, including prices, features, images, and agent details. Ideal for real estate analysis, investment decisions, and automated workflows. Reliable, fast, and outputs clean JSON for easy integration.", "version": "0.0", "x-build-id": "bhh8HQVadEVQL9yHf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~zoopla-propertydetails-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-zoopla-propertydetails-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~zoopla-propertydetails-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-zoopla-propertydetails-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~zoopla-propertydetails-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-zoopla-propertydetails-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "ItemLimi": { "title": "Item Limit", "type": "integer", "description": "Specifies the maximum number of items to process.", "default": 20 }, "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://www.zoopla.co.uk/for-sale/details/72529283/?search_identifier=981b3921dcdf7acf59f815957ba4a861da68b9e91e6115460efce227fb92417f" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```