# 🇸🇬 Singapore data.gov.sg Scraper — HDB, COE, Singstat (`nexgendata/sg-datagov-multi-dataset`) Actor

Query any of 1000+ Singapore government open datasets (data.gov.sg) - transport, environment, economy, demographics, education, health, housing. One actor, one resource\_id, official CKAN API.

- **URL**: https://apify.com/nexgendata/sg-datagov-multi-dataset.md
- **Developed by:** [NexGenData](https://apify.com/nexgendata) (community)
- **Categories:** Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 singapore data.gov.sg records

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

## 🇸🇬 Singapore data.gov.sg Multi-Dataset Scraper — HDB Resale, COE, Singstat, MAS

A **universal wrapper for [data.gov.sg](https://data.gov.sg)** — the official Singapore Government open-data platform. One actor, one input field (`dataset_id`), and you can pull from **1,000+ official datasets** spanning transport, environment, economy, demographics, education, health, housing, and finance.

This is the fastest path to **programmatic, paginated, schema-tagged** access for journalists, researchers, policy analysts, fintech builders, prop-tech founders, and data scientists working with Singapore public data. The actor wraps the CKAN `datastore_search` API so you don't have to build pagination, filtering, full-text search, or rate-limit handling yourself.

**No authentication. No API keys. No anti-bot risk.** This is an *official Government of Singapore API*, free for public use under the [Singapore Open Data Licence](https://beta.data.gov.sg/open-data-licence).

---

### Why this beats the data.gov.sg portal, Singstat Table Builder, EDB & paid statistics vendors

- **The data.gov.sg portal is browse-only.** It gives you a CSV download per dataset and a manual UI. No bulk pulls, no scheduled refresh, no programmatic filter, no pipeline-ready output. This actor fixes that.
- **Singstat Table Builder is a UI, not an API.** You click through facets to compose a table, then export. There is no clean CKAN-style endpoint behind it. Our actor goes straight to the underlying CKAN datastore_search.
- **World Bank, Statista, Knoema, Trading Economics, CEIC** all republish Singapore data behind **$200–$5,000/month** paywalls — the same data the Government of Singapore publishes free. You're paying them to copy a free firehose.
- **Pay-per-row, not per-month.** $0.01 per run start + $0.02 per record. A 500-row HDB Tampines pull is $10.01. A 10,000-row environmental scan is $200.01. Compare to the $129–$799/month "Singapore data" SKUs from paid statistics vendors.
- **CKAN filtering, full-text search, and 1,000-row chunked pagination — all handled.** Pass `{"town": "TAMPINES"}` to filter HDB resale. Pass `search_query: "Bukit Timah"` for free-text search across all columns. Set `limit: 10000` to pull the full historical slice.

---

### What You Get

Every record returned by the actor is **flattened and tagged** with provenance fields, then unioned with whatever the underlying dataset's native columns are.

| Field | Purpose |
|---|---|
| `dataset_id` | The CKAN resource_id you queried (e.g. `d_8b84c4ee58e3cfc0ece0d773c8ca6abc`). |
| `dataset_name` | Friendly label stamped on every row (e.g. `HDB Resale Prices 2017+`). |
| `category` | One of Transport, Environment, Economy, Demographics, Education, Health, Housing, Finance, Other. |
| `data_source` | Always `data.gov.sg (CKAN datastore_search)` — preserved for attribution. |
| `last_updated` | Provenance timestamp from CKAN `_links.start`. |
| `_id` | CKAN row primary key. |
| `…native columns…` | Every column the underlying dataset publishes (e.g. for HDB resale: `town`, `flat_type`, `block`, `street_name`, `storey_range`, `floor_area_sqm`, `flat_model`, `lease_commence_date`, `remaining_lease`, `resale_price`, `month`). |

The native columns vary per dataset — that's the trade-off of a universal wrapper. Run with `limit: 5` first to inspect the exact shape before wiring a downstream pipeline.

#### Popular datasets you can plug straight in

- **Housing (HDB / URA)** — HDB Resale Flat Prices (1990 → present, split across 5 vintage tables), HDB Property Info, HDB Carpark Info.
- **Transport (LTA)** — COE Bidding Results, Annual Motor Vehicle Population, Monthly Motor Vehicle Registrations, Public Transport Ridership, Bus Stops, MRT/LRT Station Codes, ERP Rates.
- **Environment (NEA)** — Monthly Rainfall, Daily Rainfall, Mean Air Temperature, Relative Humidity, Wind Speed, PSI (24-hour, by region), Dengue Cases, Beach Water Quality.
- **Economy & Finance (MAS, MTI, SingStat)** — Consumer Price Index (CPI), GDP by Industry, Unemployment Rate, Foreign Reserves, SIBOR rates, MAS Exchange Rates (end-of-period), Total Trade Imports & Exports.
- **Demographics (SingStat, ICA, DOS)** — Residents by Planning Area & Sex, Residents by Age Group, Births & Deaths, Marriages & Divorces, Population Trends.
- **Education (MOE)** — General Information of Schools, Subjects Offered by Schools, CCAs Offered.
- **Health (MOH)** — Weekly Infectious Disease Bulletin, Hospital Bed Capacity.

Browse the full catalogue at [data.gov.sg/datasets](https://data.gov.sg/datasets) and paste any `resource_id` into the actor's `dataset_id` field.

---

### Use Cases

- **Prop-tech founders & PropertyGuru / 99.co competitors** — pull the full HDB Resale Flat Prices history (230K+ rows) and join to your listings, compute $/sqft, lease-decay-adjusted price, and town-level price indices without scraping URA's PDF reports.
- **Singapore journalists & data desks (ST, CNA, Today, MOTHERSHIP)** — paginate the COE bidding history, quarterly CPI prints, dengue weekly bulletins, or housing transaction records for stories on cost of living, transport policy, and public health.
- **Fintech & wealth-tech (StashAway, Endowus, Syfe, Saxo)** — refresh MAS Exchange Rates, SIBOR, and CPI directly from the source feed for in-app charts and macro panels.
- **Academic researchers & think-tanks (IPS, LKYSPP, NUS, NTU, SUTD)** — reproducible, dated, version-controlled pulls for working papers on housing affordability, transport demand, demographic shifts, and public health.
- **Policy analysts (URA, MTI, EDB partners, consultancies)** — bulk-pull dataset slices for ministry presentations and regression input without manually exporting CSVs from the portal.
- **Civic-tech & data-journalism hackathons** — fast onboarding to Singapore open data for hack projects on dengue, MRT crowding, school admissions, or carpark availability.
- **BI / analytics consultancies** — drop straight into BigQuery, Snowflake, DuckDB, or Postgres; categorize and tag each row at ingest time using `category` and `dataset_name`.

---

### Quick Start

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

## HDB Resale Prices in Tampines, 5-room flats, latest 500 transactions
run = client.actor("nexgendata/sg-datagov-multi-dataset").call(run_input={
    "dataset_id": "d_8b84c4ee58e3cfc0ece0d773c8ca6abc",
    "filters": {"town": "TAMPINES", "flat_type": "5 ROOM"},
    "limit": 500,
    "dataset_name": "HDB Resale Prices (2017+)",
    "category": "Housing",
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["town"], item["flat_type"], item["floor_area_sqm"], item["resale_price"])
````

#### COE bidding history

```python
run = client.actor("nexgendata/sg-datagov-multi-dataset").call(run_input={
    "dataset_id": "d_2d493bbc98a652d0009dd58172e2da80",
    "limit": 1000,
    "category": "Transport",
    "dataset_name": "COE Bidding Results",
})
```

Returns the 1,000 most recent COE bidding rounds (categories A/B/C/D/E) with `premium`, `bidding_no`, `vehicle_class`, `quota`, `bids_success`, `bids_received`.

#### Free-text search

```python
run = client.actor("nexgendata/sg-datagov-multi-dataset").call(run_input={
    "dataset_id": "d_8b84c4ee58e3cfc0ece0d773c8ca6abc",
    "search_query": "Bukit Timah",
    "limit": 200,
    "category": "Housing",
})
```

The CKAN `q=` parameter matches across every column of the dataset, so this returns every HDB resale row that mentions Bukit Timah anywhere (town, street, block, etc.).

#### Inputs

| Field | Type | Required | Description |
|---|---|---|---|
| `dataset_id` | string | **yes** | CKAN `resource_id`. Format `d_<32-hex>`. |
| `filters` | object | no | Column → value equality filters (e.g. `{"town": "ANG MO KIO"}`). |
| `search_query` | string | no | Free-text search across all columns. |
| `limit` | int 1–10,000 | no | Max records (paginated internally in chunks of 1,000). Default 100. |
| `dataset_name` | string | no | Friendly label stamped on every output row. |
| `category` | enum | no | One of Transport / Environment / Economy / Demographics / Education / Health / Housing / Finance / Other. |

***

### Pricing

Pay-per-event, no subscription.

| Event | Price |
|---|---|
| Actor start | **$0.01 / run** |
| data.gov.sg record | **$0.02 / record** |

**Examples:**

- 100-row preview: **$2.01**
- 500-row HDB Tampines pull: **$10.01**
- 1,000-row COE bidding history: **$20.01**
- 10,000-row environmental scan: **$200.01**

For very-high-volume historical pulls (full HDB resale ≈ 230K rows), reach out and we'll quote a bulk arrangement.

***

### Comparison vs the obvious alternatives

| Vendor | Singapore data coverage | Bulk / programmatic | Cost | Schema-stable JSON |
|---|---|---|---|---|
| **NexGenData sg-datagov-multi-dataset** | 1,000+ datasets via CKAN | **Yes — JSON, CSV, XLSX out of the box** | **$0.01 + $0.02/row** | Yes |
| data.gov.sg portal (official) | All of them | UI only — CSV per dataset, no bulk endpoint exposed in the UI | Free | N/A (manual) |
| Singstat Table Builder (official) | SingStat subset (economy / demo) | UI faceted, manual export | Free | N/A (manual) |
| EDB Singapore data hub | Curated economic snapshots | Mostly PDF / dashboard | Free | No |
| World Bank Singapore | Macro indicators only | API present, but Singapore-specific micro datasets absent | Free | Partial |
| Statista — Singapore | Republishes a subset behind a paywall | Limited API | **$1,950+/year Pro** | Yes |
| CEIC / Trading Economics | Macro + some micro | API with seat licence | **~$5,000+/year Enterprise** | Yes |
| Knoema / TheGlobalEconomy | Republished macro | API with quota | $200–$1,000+/mo | Partial |

If you need just one Singapore macro indicator with a 10-year tail, the **World Bank** API is free. If you need 1,000+ datasets with bulk pulls, filters, and pipeline-ready JSON output — this actor is the right tool.

***

### Sister Actors in the NexGenData Singapore Fleet

Pair this universal wrapper with our **specialized Singapore actors** when you want richer, opinionated schemas:

| Use case | Actor |
|---|---|
| MAS register of licensed banks, FIs, capital-markets services, and payment institutions | [sg-mas-financial-institutions](https://apify.com/nexgendata/sg-mas-financial-institutions) |
| HDB resale with town-level enrichment, $/sqft, lease decay | [sg-hdb-resale-prices](https://apify.com/nexgendata/sg-hdb-resale-prices) |
| URA private residential transactions (condos, landed) | [sg-ura-property-transactions](https://apify.com/nexgendata/sg-ura-property-transactions) |
| SGX IPO calendar and prospectus links | [sg-sgx-ipo-calendar](https://apify.com/nexgendata/sg-sgx-ipo-calendar) |
| ACRA Singapore company registry lookup | [singapore-acra-companies](https://apify.com/nexgendata/singapore-acra-companies) |
| SGX listed-equity screener (Straits Times fundamentals, REITs, banks) | [sgx-singapore-stock-screener](https://apify.com/nexgendata/sgx-singapore-stock-screener) |
| HK Companies Registry — cross-border SG↔HK corporate research | [hk-companies-registry](https://apify.com/nexgendata/hk-companies-registry) |

***

### FAQ

**Is this legal? Can I redistribute the data?**
Yes. All data is republished from data.gov.sg under the [Singapore Open Data Licence](https://beta.data.gov.sg/open-data-licence). Attribution is required when you publish derivative work; the actor preserves `data_source` on every record so you can comply automatically. This actor is **not endorsed by or affiliated with the Government of Singapore** — it is an independent CKAN client.

**How fresh is the data?**
Each request hits data.gov.sg live, no cached layer. Update cadence depends on the owning agency — HDB resale updates monthly, COE bidding twice a month, weather datasets daily, CPI monthly. The `last_updated` field on each row carries CKAN's own provenance timestamp.

**The columns are different across datasets — how do I write stable ETL?**
That's the trade-off of a universal wrapper. **Pin one dataset per Apify schedule**, tag it with `dataset_name` + `category`, and treat each schedule as a separate ETL job. The five provenance fields (`dataset_id`, `dataset_name`, `category`, `data_source`, `last_updated`) are stable across all datasets and are safe to model as a parent table; the native columns go in a per-dataset child table.

**Why does my filter return zero rows?**
CKAN `filters` is an exact-match equality predicate. Capitalization and whitespace must match the dataset's actual values. Run `{"limit": 5}` first with no filter to inspect actual column values, then add the filter. Some datasets use `"ANG MO KIO"` (with spaces) for town names; others use codes like `AMK`.

**Resource IDs sometimes change — what happens then?**
Singapore agencies occasionally re-publish datasets with a new `resource_id`. If a query returns zero rows or a 404, confirm against [data.gov.sg/datasets](https://data.gov.sg/datasets). The dataset name and content survive; only the ID changes.

**Are there rate limits?**
data.gov.sg does not publish a strict rate limit on its CKAN endpoint; in practice it tolerates the actor's 1,000-row chunked pagination comfortably. For pulls > 50K rows we recommend spacing runs out by a few minutes.

**Can I get data older than data.gov.sg publishes?**
No. The data.gov.sg portal is the source of record. For deeper history (e.g. 1990s HDB resale before the official series begins), there is no programmatic source — those rows simply do not exist in the public CKAN feed.

**What output formats are supported?**
Apify dataset native — JSON, CSV, XLSX, RSS, HTML table. Stream directly into webhooks, Snowflake, BigQuery, DuckDB, Postgres, or any S3-compatible store. The `apify_client` SDK works for Python, Node, and any HTTP client.

***

### About NexGenData

NexGenData publishes 200+ buyer-intent actors covering SEC filings, YC alumni, Delaware DOC, lead generation, competitive intelligence, stock fundamentals across 30+ exchanges, IPO calendars, ETF holdings, treasury yields, commodity futures, FX rates, crypto, and **a deep Singapore / APAC government-data cluster**. All pay-per-result, no subscriptions. Browse the full catalog at **https://apify.com/nexgendata?fpr=2ayu9b**.

# Actor input Schema

## `dataset_id` (type: `string`):

The data.gov.sg CKAN resource\_id of the dataset to query. Examples: d\_8b84c4ee58e3cfc0ece0d773c8ca6abc (HDB resale prices 2017+), d\_ebc5ab87086db484f88045ce46f1cc6f (HDB resale 2015-2016), d\_2d493bbc98a652d0009dd58172e2da80 (COE bidding results), d\_3f9e17c08ce0e003a2c08c4ef02c6453 (Weather - rainfall), d\_a7b94d0aabfa8c3da6d80c1f1b8b6bda (MRT/LRT station ridership). Browse all datasets at https://data.gov.sg/datasets

## `filters` (type: `object`):

Optional CKAN datastore filters: map a column name to an exact match value. Columns differ per dataset. For HDB resale (d\_8b84c4ee58e3cfc0ece0d773c8ca6abc) try {"town": "ANG MO KIO", "flat\_type": "4 ROOM"}. Leave empty to scan the whole dataset. Use Preview rows first to see available columns.

## `search_query` (type: `string`):

Free-text search across all columns of the dataset (CKAN q= parameter). Useful when you don't know exact column values. Example for HDB: 'ANG MO KIO' would match across town, street\_name, etc. Leave blank to disable.

## `limit` (type: `integer`):

Maximum records to return (1-10000). The actor paginates internally in chunks of 1000. data.gov.sg can return large datasets - HDB resale alone has 230K+ rows.

## `dataset_name` (type: `string`):

Friendly name to stamp on each output record (e.g. 'HDB Resale Prices 2017+'). Purely cosmetic - helps when you wire multiple runs into one downstream pipeline.

## `category` (type: `string`):

Category label stamped on each record. Pick the closest match: Transport, Environment, Economy, Demographics, Education, Health, Housing, Finance, Other.

## Actor input object example

```json
{
  "dataset_id": "d_8b84c4ee58e3cfc0ece0d773c8ca6abc",
  "filters": {},
  "limit": 100,
  "dataset_name": "HDB Resale Prices (2017 onwards)",
  "category": "Housing"
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "dataset_id": "d_8b84c4ee58e3cfc0ece0d773c8ca6abc",
    "filters": {},
    "search_query": "",
    "limit": 100,
    "dataset_name": "HDB Resale Prices (2017 onwards)",
    "category": "Housing"
};

// Run the Actor and wait for it to finish
const run = await client.actor("nexgendata/sg-datagov-multi-dataset").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "dataset_id": "d_8b84c4ee58e3cfc0ece0d773c8ca6abc",
    "filters": {},
    "search_query": "",
    "limit": 100,
    "dataset_name": "HDB Resale Prices (2017 onwards)",
    "category": "Housing",
}

# Run the Actor and wait for it to finish
run = client.actor("nexgendata/sg-datagov-multi-dataset").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 '{
  "dataset_id": "d_8b84c4ee58e3cfc0ece0d773c8ca6abc",
  "filters": {},
  "search_query": "",
  "limit": 100,
  "dataset_name": "HDB Resale Prices (2017 onwards)",
  "category": "Housing"
}' |
apify call nexgendata/sg-datagov-multi-dataset --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=nexgendata/sg-datagov-multi-dataset",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "🇸🇬 Singapore data.gov.sg Scraper — HDB, COE, Singstat",
        "description": "Query any of 1000+ Singapore government open datasets (data.gov.sg) - transport, environment, economy, demographics, education, health, housing. One actor, one resource_id, official CKAN API.",
        "version": "0.0",
        "x-build-id": "waG4QvnEkbg7u6qlh"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/nexgendata~sg-datagov-multi-dataset/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-nexgendata-sg-datagov-multi-dataset",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/nexgendata~sg-datagov-multi-dataset/runs": {
            "post": {
                "operationId": "runs-sync-nexgendata-sg-datagov-multi-dataset",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/nexgendata~sg-datagov-multi-dataset/run-sync": {
            "post": {
                "operationId": "run-sync-nexgendata-sg-datagov-multi-dataset",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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",
                "required": [
                    "dataset_id"
                ],
                "properties": {
                    "dataset_id": {
                        "title": "Dataset ID (CKAN resource_id)",
                        "type": "string",
                        "description": "The data.gov.sg CKAN resource_id of the dataset to query. Examples: d_8b84c4ee58e3cfc0ece0d773c8ca6abc (HDB resale prices 2017+), d_ebc5ab87086db484f88045ce46f1cc6f (HDB resale 2015-2016), d_2d493bbc98a652d0009dd58172e2da80 (COE bidding results), d_3f9e17c08ce0e003a2c08c4ef02c6453 (Weather - rainfall), d_a7b94d0aabfa8c3da6d80c1f1b8b6bda (MRT/LRT station ridership). Browse all datasets at https://data.gov.sg/datasets"
                    },
                    "filters": {
                        "title": "Column filters (key-value pairs)",
                        "type": "object",
                        "description": "Optional CKAN datastore filters: map a column name to an exact match value. Columns differ per dataset. For HDB resale (d_8b84c4ee58e3cfc0ece0d773c8ca6abc) try {\"town\": \"ANG MO KIO\", \"flat_type\": \"4 ROOM\"}. Leave empty to scan the whole dataset. Use Preview rows first to see available columns."
                    },
                    "search_query": {
                        "title": "Full-text search query (optional)",
                        "type": "string",
                        "description": "Free-text search across all columns of the dataset (CKAN q= parameter). Useful when you don't know exact column values. Example for HDB: 'ANG MO KIO' would match across town, street_name, etc. Leave blank to disable."
                    },
                    "limit": {
                        "title": "Max records",
                        "minimum": 1,
                        "maximum": 10000,
                        "type": "integer",
                        "description": "Maximum records to return (1-10000). The actor paginates internally in chunks of 1000. data.gov.sg can return large datasets - HDB resale alone has 230K+ rows."
                    },
                    "dataset_name": {
                        "title": "Dataset display name (optional)",
                        "type": "string",
                        "description": "Friendly name to stamp on each output record (e.g. 'HDB Resale Prices 2017+'). Purely cosmetic - helps when you wire multiple runs into one downstream pipeline."
                    },
                    "category": {
                        "title": "Category tag",
                        "enum": [
                            "Transport",
                            "Environment",
                            "Economy",
                            "Demographics",
                            "Education",
                            "Health",
                            "Housing",
                            "Finance",
                            "Other"
                        ],
                        "type": "string",
                        "description": "Category label stamped on each record. Pick the closest match: Transport, Environment, Economy, Demographics, Education, Health, Housing, Finance, Other.",
                        "default": "Housing"
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```