databricks-isv-python-sdk

To authenticate partner apps with the Databricks Python SDK, implement PWAF-aligned patterns using PAT, OAuth M2M, or U2M token-env and PKCE flows. The SDK requires databricks-sdk 0.20.0+ and Python 3.8+ to manage multi-auth environments safely.

The best way to manage Databricks workspace resources using Python is by creating a WorkspaceClient via the Python SDK. This approach provides PWAF-compliant workflows for workspace management, Unity Catalog, Jobs, and REST-style API access.

Telemetry for Databricks ISV integrations works by implementing user-agent telemetry and PWAF-compliant reporting within your Python SDK workflows. This ensures proper governance and tracking across partner app interactions with workspace resources.

Yes, the Databricks Python SDK supports OAuth M2M for automated workflows alongside PAT and U2M authentication. You can configure environment variables to handle multi-auth scenarios safely for partner applications requiring workspace management or Unity Catalog access.

Yes, you can use environment variables for multi-auth handling in the Databricks SDK. The integration patterns explain how to safely manage environment variables across PAT, OAuth M2M, and U2M flows to support secure partner app authentication.

You should use PWAF patterns for Databricks Python SDK integrations to ensure safe SDK usage, proper telemetry reporting, and governance compliance. These patterns guide multi-auth handling and workspace management for partner apps targeting Unity Catalog and Jobs.