# Dot Property Southeast Asia Real Estate Listings Scraper (`scrapers_lat/dotproperty-sea-scraper`) Actor
Scrape Dot Property listings across Thailand, Philippines and Indonesia with price, type, bedrooms, bathrooms, size in sqm, city, coordinates and advertiser. Export to JSON, CSV or Excel.
- **URL**: https://apify.com/scrapers\_lat/dotproperty-sea-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** Real estate, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $17.00 / 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.
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 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/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
## Dot Property Southeast Asia Real Estate Listings Scraper
> Collect Dot Property real estate listings across Thailand, the Philippines and Indonesia with price, property type, size, bedrooms, bathrooms, location, map coordinates and the advertiser. Filter by country, sale or rent, area and property type and export clean structured data for market research, lead generation and investment analysis.
Price & size beds, baths, sqm
Location city, region, lat / long
JSON / CSV / Excel output formats
### What you get
Each record is one property listing, ready for a spreadsheet, a dashboard or a CRM:
- **title**: the listing headline
- **price** and **priceCurrency**: the asking price in local currency
- **listingType**: for sale or for rent
- **propertyType**: house, condo, townhouse, apartment, villa or land
- **bedrooms**, **bathrooms**: room counts
- **area**: usable size in square metres, plus **landAreaSqm** for houses and land
- **city**, **region**, **country**: where the property is
- **latitude**, **longitude**: map coordinates
- **project**: the development or building name when available
- **parkingSpots**, **storeys**, **furnitureStatus**, **petPolicy**, **amenities**: extra property details
- **listedBy**, **agencyName**, **advertiserType**: who is advertising (agency or private owner)
- **unitId**, **totalViews**, **datePosted**: reference and interest signals
- **image** and **listingUrl**: cover photo and a direct link
- **observedAt**: when the record was captured
### Who is it for
| Use case | Who benefits |
|---|---|
| Market research | Analysts tracking asking prices, size and inventory by area |
| Lead generation | Agencies and portals finding active advertisers and listings |
| Investment | Buyers and funds comparing yield, size and price per sqm |
| Data & dashboards | Builders feeding Southeast Asia property data into their apps |
### How to use it
1. Pick a **country** (Thailand, Philippines or Indonesia) and whether you want properties **for sale or for rent**.
2. Enter a **location** (for example `bangkok`, `phuket` or `chiang-mai`) and a **property type**, or leave it on **All property types**.
3. Set **Max Items** and run. Export as JSON, CSV or Excel, or pull it through the Apify API.
### Frequently Asked Questions
**Which countries are covered?**
Thailand, the Philippines and Indonesia. Thailand has the deepest inventory. Choose the country in the input.
**Can I get only condos or only houses?**
Yes. Use the property type selector to focus on houses, condos, townhouses, apartments, villas or land, or keep All property types for everything.
**What currency are prices in?**
Prices are returned in the local currency of the selected country, with a `priceCurrency` field so you always know the unit.
**Do I get the size and coordinates?**
Yes. Each listing includes usable area in square metres (and land size for houses and land) plus latitude and longitude for mapping.
**How fresh is the data?**
Listings are read live at run time, so each record reflects what is published at the moment of the run (see observedAt).
### Related scrapers
- [Singapore PropertyGuru Listings Scraper](https://apify.com/scrapers_lat/singapore-propertyguru-scraper)
- [Lamudi Mexico Real Estate Listings Scraper](https://apify.com/scrapers_lat/lamudi-scraper)
- [Booking.com Hotels & Prices Scraper](https://apify.com/scrapers_lat/booking-hotels-scraper)
### 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 Dot Property. It only accesses publicly available listing data. Use the results in accordance with the source's terms.
# Actor input Schema
## `country` (type: `string`):
Which Dot Property site to search: Thailand, the Philippines or Indonesia.
## `listingType` (type: `string`):
Whether to collect properties for sale or for rent.
## `locations` (type: `array`):
One or more cities, provinces or areas to search. One run searches every location in the list, for example 'bangkok', 'phuket', 'chiang-mai' or 'pattaya'.
## `propertyType` (type: `string`):
Type of property to collect. Choose 'All property types' to include every kind.
## `maxListings` (type: `integer`):
Maximum number of listings to collect across all locations in this run.
## Actor input object example
```json
{
"country": "th",
"listingType": "sale",
"locations": [
"bangkok",
"phuket"
],
"propertyType": "property",
"maxListings": 24
}
````
# 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 = {
"country": "th",
"listingType": "sale",
"locations": [
"bangkok",
"phuket"
],
"propertyType": "property",
"maxListings": 24
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/dotproperty-sea-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 = {
"country": "th",
"listingType": "sale",
"locations": [
"bangkok",
"phuket",
],
"propertyType": "property",
"maxListings": 24,
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/dotproperty-sea-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 '{
"country": "th",
"listingType": "sale",
"locations": [
"bangkok",
"phuket"
],
"propertyType": "property",
"maxListings": 24
}' |
apify call scrapers_lat/dotproperty-sea-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/dotproperty-sea-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Dot Property Southeast Asia Real Estate Listings Scraper",
"description": "Scrape Dot Property listings across Thailand, Philippines and Indonesia with price, type, bedrooms, bathrooms, size in sqm, city, coordinates and advertiser. Export to JSON, CSV or Excel.",
"version": "0.1",
"x-build-id": "SjhvrDWROdaJ4p7wf"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~dotproperty-sea-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-dotproperty-sea-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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~dotproperty-sea-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-dotproperty-sea-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~dotproperty-sea-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-dotproperty-sea-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"country": {
"title": "Country",
"enum": [
"th",
"ph",
"id"
],
"type": "string",
"description": "Which Dot Property site to search: Thailand, the Philippines or Indonesia.",
"default": "th"
},
"listingType": {
"title": "Sale or rent",
"enum": [
"sale",
"rent"
],
"type": "string",
"description": "Whether to collect properties for sale or for rent.",
"default": "sale"
},
"locations": {
"title": "Locations",
"type": "array",
"description": "One or more cities, provinces or areas to search. One run searches every location in the list, for example 'bangkok', 'phuket', 'chiang-mai' or 'pattaya'.",
"items": {
"type": "string"
}
},
"propertyType": {
"title": "Property type",
"enum": [
"property",
"house",
"condo",
"townhouse",
"apartment",
"villa",
"land"
],
"type": "string",
"description": "Type of property to collect. Choose 'All property types' to include every kind.",
"default": "property"
},
"maxListings": {
"title": "Max Listings To Scrape",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of listings to collect across all locations in this run."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```