Load Ato Gov Au data to DuckDB

The ATO API Portal provides a gateway for digital service providers to access and develop against various Australian Taxation Office APIs for business reporting and service integration. Everything needed to build a working Ato Gov Au → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your Ato Gov Au to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Ato Gov Au to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Ato Gov Au API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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Ato Gov Au API at a glance

These values come from the Ato Gov Au API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Ato Gov Au API?

The ATO API Gateway requires a two-part authentication mechanism: an access token obtained via OAuth 2.0 (client_credentials flow with signed JWT) must be provided in the 'Authorization' header as a Bearer token, and an 'apikey' (consumer key) must be provided in a custom header.

1. Get your credentials

1. Register on the ATO API Portal using your myID credential. 2. Create a team and then create a team application within that team. 3. Once the team application is created, navigate to the Team apps page and select your application. 4. Your sandbox consumer key (API key) will be displayed there immediately. 5. For production access, complete the security questionnaire and request production approval from the Digital Partnership Office (DPO); once approved, your production consumer key will become available in the same team application view.

2. Add them to .dlt/secrets.toml

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[sources.ato_gov_au_source]
api_key = "REPLACE_ME"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What Ato Gov Au data can I load into DuckDB?

These are the Ato Gov Au endpoints dlt can load into DuckDB:

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How do I load only new Ato Gov Au records?

The Ato Gov Au API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

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{"name": "individuals", "endpoint": {
    "path": "individuals",
    # Replace with a field that increases on every write.
    "incremental": {"cursor_path": "REPLACE_ME", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated Ato Gov Au pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading The two most common endpoints for OAuth-based interaction are the token endpoint (for requesting access tokens) and the register endpoint (from the OAuth Dynamic Client Registration API). from the Ato Gov Au API into DuckDB:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def ato_gov_au_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://apiportal.ato.gov.au/",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "individuals", "endpoint": {"path": "individuals"}},
            {"name": "organisations", "endpoint": {"path": "organisations"}}
        ],
    }
    yield from rest_api_resources(config)


def load_ato_gov_au_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="ato_gov_au_pipeline",
        destination="duckdb",
        dataset_name="ato_gov_au_data",
    )
    load_info = pipeline.run(ato_gov_au_source())
    print(load_info)


if __name__ == "__main__":
    load_ato_gov_au_to_duckdb()

Run it with python ato_gov_au_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query Ato Gov Au data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("ato_gov_au_pipeline").dataset()
df = data.individuals.df()
print(df.head())

SQL:

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SELECT * FROM ato_gov_au_data.individuals LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the Ato Gov Au to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw Ato Gov Au loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Ato Gov Au data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack