Google Bid Manager Python API Docs | dltHub

Google Bid Manager is a platform for creating, managing, and reporting on programmatic advertising queries and reports. The REST API base URL is https://doubleclickbidmanager.googleapis.com and All requests require an OAuth 2.0 Bearer token for authentication..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Google Bid Manager data in under 10 minutes.

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What data can I load from Google Bid Manager?

Here are some of the endpoints you can load from Google Bid Manager:

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How do I authenticate with the Google Bid Manager API?

Use OAuth 2.0 to obtain an access token and include it in the request header as Authorization: Bearer {access_token}.

1. Get your credentials

1. Open the Google Cloud Console and create a new project. 2. In the navigation menu select APIs & Services > Library and enable the DoubleClick Bid Manager API. 3. Go to APIs & Services > Credentials, click Create credentials > OAuth client ID. 4. Choose application type, fill in required details, and click Create. 5. Copy the client ID and client secret; you will use them to obtain an access token via the OAuth 2.0 flow.

2. Add them to .dlt/secrets.toml

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[sources.google_bid_manager_source]
access_token = "your_access_token_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Google Bid Manager API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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python google_bid_manager_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline google_bid_manager_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset google_bid_manager_data
The duckdb destination used duckdb:/google_bid_manager.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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dlt pipeline google_bid_manager_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads queries and reports from the Google Bid Manager API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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

@dlt.source
def google_bid_manager_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://doubleclickbidmanager.googleapis.com",
            "auth": {
                "type": "bearer",
                "access_token": access_token,
            },
        },
        "resources": [
            {"name": "queries", "endpoint": {"path": "v2/queries", "data_selector": "queries"}},
            {"name": "reports", "endpoint": {"path": "v2/queries/{queryId}/reports", "data_selector": "reports"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="google_bid_manager_pipeline",
        destination="duckdb",
        dataset_name="google_bid_manager_data",
    )
    load_info = pipeline.run(google_bid_manager_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("google_bid_manager_pipeline").dataset()
sessions_df = data.queries.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM google_bid_manager_data.queries LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("google_bid_manager_pipeline").dataset()
data.queries.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Google Bid Manager data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication Errors

• 401 Unauthorized – Indicates an invalid or expired access token. Refresh the token using the OAuth refresh flow.
• 403 Forbidden – The token does not have the required scopes (https://www.googleapis.com/auth/doubleclickbidmanager). Ensure the OAuth consent screen includes the correct scope.

Rate Limiting

• 429 Too Many Requests – The API enforces per‑project quotas. Reduce request frequency or request a quota increase in the Google Cloud Console.

Pagination

• Many list endpoints return a nextPageToken. Include this token in the pageToken query parameter to retrieve subsequent pages.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack