# UK Land Registry Sold House Prices Scraper (`scrapers_lat/uk-land-registry-prices-scraper`) Actor
Scrape recorded UK house sale prices from HM Land Registry Price Paid Data for England and Wales. Get full address, price paid, sale date, property type, tenure, new-build flag and transaction category by postcode or town. Export to JSON, CSV or Excel.
- **URL**: https://apify.com/scrapers\_lat/uk-land-registry-prices-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** Real estate, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $6.80 / 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.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Sold House Prices Scraper
> Pull recorded UK house sale prices for England and Wales with full address, price paid, sale date, property type, tenure and new-build flag. Search by postcode or town, filter by price and date, and export clean structured data for valuations, research and market analysis.
**๐ฅ [Input](https://apify.com/scrapers_lat/uk-land-registry-prices-scraper/input-schema) ยท ๐ค [Output](https://apify.com/scrapers_lat/uk-land-registry-prices-scraper/output-schema) ยท ๐ฐ [Pricing](https://apify.com/scrapers_lat/uk-land-registry-prices-scraper/pricing) ยท โถ๏ธ [Examples](https://apify.com/scrapers_lat/uk-land-registry-prices-scraper/examples)**
Actual sold prices not asking prices
Full address plus type, tenure, date
JSON / CSV / Excel output formats
### Who is it for
| Use case | Who benefits |
|---|---|
| Valuations | Surveyors and agents pricing homes from real comparable sales |
| Market research | Analysts tracking price trends by area, type and tenure |
| Lending and risk | Mortgage and insurance teams checking recorded transaction history |
| Property tech | Builders feeding sold-price data into portals, tools and dashboards |
### How to use it
1. Add one or more **postcodes** (fastest and most precise) or **towns**.
2. Optionally narrow by **property type**, **minimum / maximum price** and a **sold-from / sold-to** date range.
3. Set **Max Records To Scrape** and run. Export as JSON, CSV or Excel, or pull it through the Apify API.
### Frequently Asked Questions
**Are these asking prices or actual sold prices?**
These are actual recorded sale prices for completed transactions, not listing or asking prices.
**Which areas are covered?**
Residential property sales in England and Wales.
**How do I get the most recent sales for a street?**
Search by the full postcode. Postcode searches are precise and return the sales newest first.
**Why does a town search return so much data?**
Towns can contain decades of sales. Pair a town with a date range and a price range to focus on the sales you care about, and set Max Records To Scrape.
**How fresh is the data?**
Records reflect what is published in the public register at the time of the run (see observedAt). Newly completed sales appear once they have been registered.
### More scrapers at scrapers.lat
This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish scrapers for public platforms: finance, news, real estate, jobs, e-commerce and government data. Browse the full catalog or ask us for a custom scraper at [scrapers.lat](https://scrapers.lat).
---
> This actor is an independent tool and has no affiliation with HM Land Registry. It only accesses publicly available open data. Contains public sector information licensed under the Open Government Licence. Use the results in accordance with the source's terms.
# Actor input Schema
## `postcodes` (type: `array`):
One or more full UK postcodes to search (for example 'PL6 8RU', 'SW1A 1AA'). Each postcode returns every recorded sale registered against it. Fastest and most precise way to search.
## `towns` (type: `array`):
One or more town names to search (for example 'PLYMOUTH', 'LONDON'). Town searches can return large volumes, so pair them with a date range and price range below.
## `propertyTypes` (type: `array`):
Optional. Keep only these property types. Use codes D (Detached), S (Semi-detached), T (Terraced), F (Flat / Maisonette), O (Other). Leave empty for all types.
## `minPrice` (type: `integer`):
Optional. Only return sales at or above this price paid, in pounds.
## `maxPrice` (type: `integer`):
Optional. Only return sales at or below this price paid, in pounds.
## `fromDate` (type: `string`):
Optional. Only return sales on or after this date. Format YYYY-MM-DD (for example 2023-01-01).
## `toDate` (type: `string`):
Optional. Only return sales on or before this date. Format YYYY-MM-DD (for example 2023-12-31).
## `maxRecords` (type: `integer`):
Maximum number of recorded sales to collect across all searches. Optional.
## Actor input object example
```json
{
"postcodes": [
"PL6 8RU"
],
"maxRecords": 50
}
````
# 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 = {
"postcodes": [
"PL6 8RU"
],
"maxRecords": 50
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/uk-land-registry-prices-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ 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);
});
// ๐ Want to learn more ๐? Go to โ 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 = {
"postcodes": ["PL6 8RU"],
"maxRecords": 50,
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/uk-land-registry-prices-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"postcodes": [
"PL6 8RU"
],
"maxRecords": 50
}' |
apify call scrapers_lat/uk-land-registry-prices-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/uk-land-registry-prices-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "UK Land Registry Sold House Prices Scraper",
"description": "Scrape recorded UK house sale prices from HM Land Registry Price Paid Data for England and Wales. Get full address, price paid, sale date, property type, tenure, new-build flag and transaction category by postcode or town. Export to JSON, CSV or Excel.",
"version": "0.1",
"x-build-id": "n071VCuHi5RMEZmYp"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~uk-land-registry-prices-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-uk-land-registry-prices-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~uk-land-registry-prices-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-uk-land-registry-prices-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~uk-land-registry-prices-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-uk-land-registry-prices-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"postcodes": {
"title": "Postcodes",
"type": "array",
"description": "One or more full UK postcodes to search (for example 'PL6 8RU', 'SW1A 1AA'). Each postcode returns every recorded sale registered against it. Fastest and most precise way to search.",
"items": {
"type": "string"
}
},
"towns": {
"title": "Towns",
"type": "array",
"description": "One or more town names to search (for example 'PLYMOUTH', 'LONDON'). Town searches can return large volumes, so pair them with a date range and price range below.",
"items": {
"type": "string"
}
},
"propertyTypes": {
"title": "Property Types",
"type": "array",
"description": "Optional. Keep only these property types. Use codes D (Detached), S (Semi-detached), T (Terraced), F (Flat / Maisonette), O (Other). Leave empty for all types.",
"items": {
"type": "string"
}
},
"minPrice": {
"title": "Minimum Price (GBP)",
"minimum": 0,
"type": "integer",
"description": "Optional. Only return sales at or above this price paid, in pounds."
},
"maxPrice": {
"title": "Maximum Price (GBP)",
"minimum": 0,
"type": "integer",
"description": "Optional. Only return sales at or below this price paid, in pounds."
},
"fromDate": {
"title": "Sold From Date",
"type": "string",
"description": "Optional. Only return sales on or after this date. Format YYYY-MM-DD (for example 2023-01-01)."
},
"toDate": {
"title": "Sold To Date",
"type": "string",
"description": "Optional. Only return sales on or before this date. Format YYYY-MM-DD (for example 2023-12-31)."
},
"maxRecords": {
"title": "Max Records To Scrape",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of recorded sales to collect across all searches. Optional."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```