Load Google Drive data to DuckDB

Google Drive API is a RESTful web service that allows applications to access and manipulate files and folders stored in Google Drive. Everything needed to build a working Google Drive → 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 Google Drive 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 Google Drive 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 Google Drive 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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Google Drive API at a glance

These values come from the Google Drive API documentation. Check them against the vendor's current reference before relying on them in production.

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How do I authenticate with the Google Drive API?

Google Drive API uses OAuth 2.0 authentication. Requests must include an Authorization header with the value 'Bearer {access_token}'.

1. Get your credentials

To obtain credentials for the Google Drive REST API, follow these steps in the Google Cloud Console: 1. Navigate to the Google Cloud Console and select or create a project. 2. Open the navigation menu, go to APIs & Services, then select Dashboard. 3. Click + ENABLE APIS AND SERVICES, search for "Google Drive API", and click Enable. 4. Navigate to the Credentials tab in the left-hand menu. 5. Click CREATE CREDENTIALS and select either API key (for public data) or OAuth client ID (for user data). For OAuth 2.0, you must first configure the OAuth consent screen in the same menu. 6. Once created, copy the generated key or download the JSON credentials file for use in your application.

2. Add them to .dlt/secrets.toml

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[sources.google_drive_source]
access_token = "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 Google Drive data can I load into DuckDB?

These are the Google Drive endpoints dlt can load into DuckDB:

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How do I load only new Google Drive records?

Google Drive exposes pageToken on drive/v3/files, 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": "files", "endpoint": {
    "path": "drive/v3/files",
    "data_selector": "files",
    "incremental": {"cursor_path": "pageToken", "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 Google Drive pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading files and drives from the Google Drive API into DuckDB:

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

@dlt.source
def google_drive_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://www.googleapis.com",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "files", "endpoint": {"path": "drive/v3/files", "data_selector": "files"}},
            {"name": "changes", "endpoint": {"path": "drive/v3/changes", "data_selector": "changes"}}
        ],
    }
    yield from rest_api_resources(config)


def load_google_drive_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="google_drive_pipeline",
        destination="duckdb",
        dataset_name="google_drive_data",
    )
    load_info = pipeline.run(google_drive_source())
    print(load_info)


if __name__ == "__main__":
    load_google_drive_to_duckdb()

Run it with python google_drive_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 Google Drive 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("google_drive_pipeline").dataset()
df = data.files.df()
print(df.head())

SQL:

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SELECT * FROM google_drive_data.files LIMIT 10;

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

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How do I deploy the Google Drive 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 Google Drive 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 Google Drive 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