Load Planview Portfolios data to DuckDB

Planview Portfolios is a project portfolio management platform that exposes public REST APIs for data integration and extraction. Everything needed to build a working Planview Portfolios → 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 Planview Portfolios 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 Planview Portfolios 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 Planview Portfolios 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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Planview Portfolios API at a glance

These values come from the Planview Portfolios 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 Planview Portfolios API?

All requests to the Planview Portfolios public REST API require an OAuth2 access token passed in the Authorization header using the Bearer scheme. The token must be obtained from the OAuth token endpoint using a client_id and client_secret with the client_credentials grant type.

1. Get your credentials

To obtain credentials for the Planview Portfolios REST API: 1. Log in to your Planview instance as an administrator. 2. Navigate to the main menu and select Administration > Users and Roles (or Users) > OAuth clients (or OAuth2 credentials). 3. Click Create to add a new OAuth client. 4. Note the generated Client ID and Client Secret. Note: The Client Secret is typically displayed only once upon creation, so ensure you store it securely. You may also need your Tenant ID or organization instance URL.

2. Add them to .dlt/secrets.toml

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[sources.planview_portfolios_source]
client_id = "your_client_id_here"
client_secret = "your_client_secret_here"

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 Planview Portfolios data can I load into DuckDB?

These are the Planview Portfolios endpoints dlt can load into DuckDB:

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How do I load only new Planview Portfolios records?

The Planview Portfolios 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": "work_for_project", "endpoint": {
    "path": "work?filter=project.Id%20.eq%20{projectId}",
    # 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 Planview Portfolios pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading oauth/token and work from the Planview Portfolios API into DuckDB:

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

@dlt.source
def planview_portfolios_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{your_account}.pvcloud.com/{your_server}/public-api/v1",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "work_for_project", "endpoint": {"path": "work?filter=project.Id%20.eq%20{projectId}", "data_selector": "Data"}},
            {"name": "odataservice_workdimension", "endpoint": {"path": "odataservice/odataservice.svc/WorkDimension"}}
        ],
    }
    yield from rest_api_resources(config)


def load_planview_portfolios_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="planview_portfolios_pipeline",
        destination="duckdb",
        dataset_name="planview_portfolios_data",
    )
    load_info = pipeline.run(planview_portfolios_source())
    print(load_info)


if __name__ == "__main__":
    load_planview_portfolios_to_duckdb()

Run it with python planview_portfolios_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 Planview Portfolios 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("planview_portfolios_pipeline").dataset()
df = data.work_for_project.df()
print(df.head())

SQL:

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SELECT * FROM planview_portfolios_data.work_for_project LIMIT 10;

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

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How do I deploy the Planview Portfolios 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 Planview Portfolios 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 Planview Portfolios 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