# London Real Estate Scraper — Rightmove & Zoopla (`aurumworks/realestate-london`) Actor Scrape London property listings from Rightmove and Zoopla. Get prices in GBP, addresses, bedrooms, bathrooms, property types, and agent details. Filter by borough, price range, and listing type (sale/rent). UK's top property data extractor. - **URL**: https://apify.com/aurumworks/realestate-london.md - **Developed by:** [Aryan Saxena](https://apify.com/aurumworks) (community) - **Categories:** Automation, Real estate, Integrations - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $7.00 / 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 ## London Real Estate Scraper — Rightmove & Zoopla Listings **Scrape London property listings from Rightmove and Zoopla.** Get prices in GBP, addresses, bedrooms, bathrooms, property types, descriptions, and agent details. Filter by borough, price range, bedrooms, and property type. Rightmove is the UK's #1 property portal — this actor gives you structured access to its London listings alongside Zoopla data. ### Why use London Real Estate Scraper? - **UK-focused** — built for the London property market with 20+ boroughs and areas mapped - **Two major platforms** — Rightmove (#1 in UK) and Zoopla combined - **Smart filtering** — filter by area, price, bedrooms, and property type - **GBP pricing** — handles both sale prices (£X,XXX) and rental prices (£X,XXX pcm) - **Property type detection** — Flat, Detached, Semi-detached, Terraced, Bungalow, Maisonette, Penthouse - **Schedule it** — monitor the London market over time ### How to scrape London property data 1. Click **Try for free** on this page 2. Select **sale** or **rent** 3. Optionally enter a borough or area (e.g. "Kensington", "Camden", "Shoreditch") 4. Set price range and bedroom filters if needed 5. Click **Start** and wait for results 6. Download as JSON, CSV, or Excel ### Input | Field | Type | Description | Default | |-------|------|-------------|---------| | Listing Type | string | sale or rent | sale | | Area / Borough | string | London area name | All London | | Min Price | integer | Minimum price (£) | — | | Max Price | integer | Maximum price (£) | — | | Min Bedrooms | integer | Minimum bedrooms | — | | Property Type | string | all, flat, detached, semi-detached, terraced, bungalow | all | | Max Results | integer | Maximum listings to scrape | 100 | ### Supported areas Westminster, Camden, Kensington, Chelsea, Islington, Hackney, Tower Hamlets, Southwark, Lambeth, Greenwich, Canary Wharf, Shoreditch, Notting Hill, Mayfair, Brixton, Clapham, Fulham, Hammersmith, Richmond, Wimbledon, and more. ### Output ```json { "city": "London", "platform": "rightmove", "currency": "GBP", "listingType": "sale", "price": "£650,000", "address": "Kensington High Street, London W8", "bedrooms": "2", "bathrooms": "1", "propertyType": "Flat", "description": "A beautifully presented two bedroom flat...", "area": "Kensington", "url": "https://www.rightmove.co.uk/properties/12345678", "imageUrl": "https://..." } ```` ### Data fields | Field | Description | |-------|-------------| | price | Listing price in GBP (or £X,XXX pcm for rentals) | | address | Property address | | bedrooms | Number of bedrooms | | bathrooms | Number of bathrooms | | propertyType | Flat, Detached, Semi-detached, Terraced, Bungalow, etc. | | description | First 200 characters of the listing description | | area | London borough or neighborhood | | platform | rightmove or zoopla | | url | Direct link to the listing | ### How much does it cost? A typical run scraping 100 listings costs about **$0.10–$0.25** in platform usage. ### FAQ **Does this work for areas outside London?** This actor is optimized for London. The borough and area mappings are London-specific. **What's the difference between Rightmove and Zoopla?** Rightmove has the largest inventory in the UK. Zoopla often has different listings and additional data. Running both gives the most complete picture. **I found a bug or have a feature request.** Please open an issue in the Issues tab. # Actor input Schema ## `listingType` (type: `string`): Type of listing to scrape — sale or rent ## `area` (type: `string`): London area or borough (e.g. Kensington, Camden, Shoreditch, Canary Wharf) ## `minPrice` (type: `integer`): Minimum listing price in GBP ## `maxPrice` (type: `integer`): Maximum listing price in GBP ## `minBeds` (type: `integer`): Minimum number of bedrooms ## `propertyType` (type: `string`): Filter by property type ## `maxResults` (type: `integer`): Maximum number of listings to scrape ## Actor input object example ```json { "listingType": "sale", "propertyType": "all", "maxResults": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("aurumworks/realestate-london").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("aurumworks/realestate-london").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 aurumworks/realestate-london --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=aurumworks/realestate-london", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "London Real Estate Scraper — Rightmove & Zoopla", "description": "Scrape London property listings from Rightmove and Zoopla. Get prices in GBP, addresses, bedrooms, bathrooms, property types, and agent details. Filter by borough, price range, and listing type (sale/rent). UK's top property data extractor.", "version": "0.1", "x-build-id": "7OSj6Y7X98cA3OzS8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/aurumworks~realestate-london/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-aurumworks-realestate-london", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/aurumworks~realestate-london/runs": { "post": { "operationId": "runs-sync-aurumworks-realestate-london", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/aurumworks~realestate-london/run-sync": { "post": { "operationId": "run-sync-aurumworks-realestate-london", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "listingType": { "title": "Listing Type", "enum": [ "sale", "rent" ], "type": "string", "description": "Type of listing to scrape — sale or rent", "default": "sale" }, "area": { "title": "Area / Borough", "type": "string", "description": "London area or borough (e.g. Kensington, Camden, Shoreditch, Canary Wharf)" }, "minPrice": { "title": "Min Price (GBP)", "type": "integer", "description": "Minimum listing price in GBP" }, "maxPrice": { "title": "Max Price (GBP)", "type": "integer", "description": "Maximum listing price in GBP" }, "minBeds": { "title": "Min Bedrooms", "minimum": 0, "maximum": 10, "type": "integer", "description": "Minimum number of bedrooms" }, "propertyType": { "title": "Property Type", "enum": [ "all", "flat", "detached", "semi-detached", "terraced", "bungalow" ], "type": "string", "description": "Filter by property type", "default": "all" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of listings to scrape", "default": 100 } } }, "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 } } } } } } } } } } ```