Load Regulations.gov data to DuckDB

Regulations.gov is a federal government portal providing programmatic access to regulatory dockets, documents, and public comments. Everything needed to build a working Regulations.gov → 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 Regulations.gov 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 Regulations.gov 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 Regulations.gov 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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Regulations.gov API at a glance

These values come from the Regulations.gov API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Regulations.gov API?

Requests require an API key to be passed in the X-Api-Key HTTP header. A DEMO_KEY is available for testing purposes, but production use requires registering for a unique key via api.data.gov.

1. Get your credentials

To obtain API credentials for the Regulations.gov REST API, visit the official GSA API portal at https://open.gsa.gov/api/regulationsgov/ and follow the registration link (provided via api.data.gov) to sign up for an API key. Once registered, you will receive a unique 40-character API key string which must be included in the 'X-Api-Key' HTTP header of your requests. For demonstration purposes only, the API accepts the string 'DEMO_KEY'.

2. Add them to .dlt/secrets.toml

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[sources.regulations_gov_source]
api_key = "YOUR_REGS_GOV_API_KEY"

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 Regulations.gov data can I load into DuckDB?

These are the Regulations.gov endpoints dlt can load into DuckDB:

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How do I load only new Regulations.gov records?

Regulations.gov exposes lastModifiedDate on v4/documents, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "documents", "endpoint": {
    "path": "v4/documents",
    "data_selector": "data",
    "incremental": {"cursor_path": "lastModifiedDate", "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 Regulations.gov pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /v4/documents and /v4/comments from the Regulations.gov API into DuckDB:

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

@dlt.source
def regulations_gov_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.regulations.gov",
            "auth": {"type": "api_key", "api_key": api_key, "name": "X-Api-Key", "location": "header"},
        },
        "resources": [
            {"name": "documents", "endpoint": {"path": "v4/documents", "data_selector": "data"}},
            {"name": "comments", "endpoint": {"path": "v4/comments", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def load_regulations_gov_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="regulations_gov_pipeline",
        destination="duckdb",
        dataset_name="regulations_gov_data",
    )
    load_info = pipeline.run(regulations_gov_source())
    print(load_info)


if __name__ == "__main__":
    load_regulations_gov_to_duckdb()

Run it with python regulations_gov_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 Regulations.gov 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("regulations_gov_pipeline").dataset()
df = data.documents.df()
print(df.head())

SQL:

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SELECT * FROM regulations_gov_data.documents LIMIT 10;

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

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How do I deploy the Regulations.gov 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 Regulations.gov 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 Regulations.gov 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