# UK Sold House Prices Scraper — Land Registry Price Paid (`vladignatyev/uk-land-registry-scraper`) Actor Download UK sold house prices (HM Land Registry Price Paid Data) as clean JSON, CSV or Excel — uncapped, by postcode, town, county or year, with a monthly monitor for new sales. Price, date, address, property type and tenure. The sold-price dataset for valuers, PropTech, investors and analysts. - **URL**: https://apify.com/vladignatyev/uk-land-registry-scraper.md - **Developed by:** [Vladimir Ignatev](https://apify.com/vladignatyev) (community) - **Categories:** Real estate, Integrations, Lead generation - **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 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 ## UK Land Registry Price Paid — Sold House Prices Download **UK sold house prices** (HM Land Registry *Price Paid Data*) into clean JSON, CSV or Excel — **uncapped**, by postcode / town / county / year, with a **monthly monitor** for new transactions. Every record: sale price, date, full address, postcode, property type, tenure, new-build flag and transaction category. Unlike the public Linked-Data API (England & Wales only, **500-row cap**, full-postcode required), this actor pulls the **bulk data and SPARQL endpoint** so you can export **whole towns, counties or years with no row limit** — the dataset valuers, PropTech, mortgage/insurance analysts and investors actually need. ### Modes - **monitor** — newest sold transactions (the monthly-update file). Schedule it monthly for a rolling feed of new sold prices. - **bulk** — a whole year (`pp-YYYY.csv`), filter by county / town / district / postcode prefix / type / price / date. Use `"complete"` for the full ~28M-row history. - **postcodes** — precise full sold history for given postcodes via the SPARQL endpoint (paginated, uncapped). ### Input ```json { "mode": "bulk", "years": ["2025"], "county": "GREATER LONDON", "maxItems": 5000 } ```` ```json { "mode": "monitor", "postcodeArea": "SW1A", "maxItems": 1000 } ``` ```json { "mode": "postcodes", "postcodes": ["PL6 8RU", "SW1A 1AA"] } ``` Filters (bulk/monitor): `county`, `town`, `district`, `postcodeArea` (prefix), `propertyType`, `minPrice`, `maxPrice`, `fromDate`, `toDate`, `maxItems`. ### Output fields `id, price, date, postcode, propertyType, isNewBuild, tenure, paon, saon, street, locality, town, district, county, category, country, source, attribution, scrapedAt` ### Licence / attribution (required) This actor uses HM Land Registry Price Paid Data under the **Open Government Licence v3.0**. Every record carries the required attribution; if you redistribute the data you must display: > Contains HM Land Registry data © Crown copyright and database right 2026. This data is licensed under the Open Government Licence v3.0. Price Paid Data tracks the address-level transactions HM Land Registry publishes; it is not a complete record of all sales and excludes certain transaction types. # Actor input Schema ## `mode` (type: `string`): monitor = newest sold transactions (monthly update, great for recurring runs). bulk = a whole year (filterable by area). postcodes = precise per-postcode history via SPARQL. ## `years` (type: `array`): Years to pull in bulk mode, e.g. \["2024","2025"]. Use "complete" for the full ~28M-row history (large). ## `postcodes` (type: `array`): Full UK postcodes, e.g. \["PL6 8RU","SW1A 1AA"]. Returns full sold history per postcode. ## `county` (type: `string`): e.g. GREATER LONDON, ESSEX (bulk/monitor). ## `town` (type: `string`): e.g. LONDON, MANCHESTER. ## `district` (type: `string`): Local-authority district, e.g. HARINGEY, BRENTWOOD (bulk/monitor). ## `postcodeArea` (type: `string`): e.g. SW1A, PL6, M (matches start of postcode). ## `propertyType` (type: `string`): Filter by property type (bulk/monitor). ## `minPrice` (type: `integer`): Only include sales at or above this price. ## `maxPrice` (type: `integer`): Only include sales at or below this price. ## `fromDate` (type: `string`): Only include sales on/after this date. ## `toDate` (type: `string`): Only include sales on/before this date. ## `maxItems` (type: `integer`): Stop after this many records. ## Actor input object example ```json { "mode": "monitor", "years": [ "2025" ], "postcodes": [], "propertyType": "", "maxItems": 1000 } ``` # Actor output Schema ## `soldPrices` (type: `string`): All sold-price transactions from this run. ## `soldPricesCsv` (type: `string`): Same data, ready for Excel / Google Sheets. ## `datasetInConsole` (type: `string`): Browse the results table in the UI. # 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("vladignatyev/uk-land-registry-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 = {} # Run the Actor and wait for it to finish run = client.actor("vladignatyev/uk-land-registry-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 '{}' | apify call vladignatyev/uk-land-registry-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=vladignatyev/uk-land-registry-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "UK Sold House Prices Scraper — Land Registry Price Paid", "description": "Download UK sold house prices (HM Land Registry Price Paid Data) as clean JSON, CSV or Excel — uncapped, by postcode, town, county or year, with a monthly monitor for new sales. Price, date, address, property type and tenure. The sold-price dataset for valuers, PropTech, investors and analysts.", "version": "0.1", "x-build-id": "h4bWOuNu7kDr12zOf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/vladignatyev~uk-land-registry-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-vladignatyev-uk-land-registry-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/vladignatyev~uk-land-registry-scraper/runs": { "post": { "operationId": "runs-sync-vladignatyev-uk-land-registry-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/vladignatyev~uk-land-registry-scraper/run-sync": { "post": { "operationId": "run-sync-vladignatyev-uk-land-registry-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": { "mode": { "title": "Mode", "enum": [ "monitor", "bulk", "postcodes" ], "type": "string", "description": "monitor = newest sold transactions (monthly update, great for recurring runs). bulk = a whole year (filterable by area). postcodes = precise per-postcode history via SPARQL.", "default": "monitor" }, "years": { "title": "Years (bulk mode)", "type": "array", "description": "Years to pull in bulk mode, e.g. [\"2024\",\"2025\"]. Use \"complete\" for the full ~28M-row history (large).", "default": [ "2025" ], "items": { "type": "string" } }, "postcodes": { "title": "Postcodes (postcodes mode)", "type": "array", "description": "Full UK postcodes, e.g. [\"PL6 8RU\",\"SW1A 1AA\"]. Returns full sold history per postcode.", "default": [], "items": { "type": "string" } }, "county": { "title": "County filter", "type": "string", "description": "e.g. GREATER LONDON, ESSEX (bulk/monitor)." }, "town": { "title": "Town/City filter", "type": "string", "description": "e.g. LONDON, MANCHESTER." }, "district": { "title": "District filter", "type": "string", "description": "Local-authority district, e.g. HARINGEY, BRENTWOOD (bulk/monitor)." }, "postcodeArea": { "title": "Postcode prefix filter", "type": "string", "description": "e.g. SW1A, PL6, M (matches start of postcode)." }, "propertyType": { "title": "Property type", "enum": [ "", "detached", "semi-detached", "terraced", "flat", "other" ], "type": "string", "description": "Filter by property type (bulk/monitor).", "default": "" }, "minPrice": { "title": "Min price (£)", "type": "integer", "description": "Only include sales at or above this price." }, "maxPrice": { "title": "Max price (£)", "type": "integer", "description": "Only include sales at or below this price." }, "fromDate": { "title": "From date (YYYY-MM-DD)", "type": "string", "description": "Only include sales on/after this date." }, "toDate": { "title": "To date (YYYY-MM-DD)", "type": "string", "description": "Only include sales on/before this date." }, "maxItems": { "title": "Max items", "type": "integer", "description": "Stop after this many records.", "default": 1000 } } }, "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 } } } } } } } } } } ```