DataHub Python Builds

These prebuilt wheel files can be used to install our Python packages as of a specific commit.

Build context

Built at 2026-04-28T11:54:37.958267+00:00.

{
  "timestamp": "2026-04-28T11:54:37.958267+00:00",
  "branch": "feat/fivetran-managed-data-lake-iceberg-rest",
  "commit": {
    "hash": "c360bac67656b3348cf625e45f103f34fca1137b",
    "message": "feat(ingest/fivetran): add FivetranDestinationDetails response model"
  },
  "base": {
    "hash": "c49689c68272c54d0aa0370519191cfa5be14ef5",
    "message": "docs(ingest/fivetran): document Glue platform_instance for Managed Data Lake\n\nAdds discoverability for the cross-connector URN-matching contract: when a\ncustomer ingests their AWS Glue catalog with the Glue source connector\n*and* their Fivetran Managed Data Lake destination, both connectors must\nagree on `platform_instance` for the emitted URNs to refer to the same\ndatasets and for lineage to render end-to-end.\n\nThe mechanism (`destination_to_platform_instance` keyed by Fivetran\ndestination ID) was already wired up; this commit just makes it\ndiscoverable for MDL users via:\n\n- A new \"Matching the Glue source connector's `platform_instance`\" section\n  in `fivetran_pre.md` explaining when it's needed and how to set it.\n- An updated example recipe showing the override.\n- A clarifying comment in `fivetran_recipe.yml` for the existing\n  `destination_to_platform_instance` block.\n\nAlso tightens type annotations in `fivetran_log_api.py`:\n- `_query() -> List[Dict]` \u2192 `List[Dict[str, Any]]`\n- `_get_column_lineage_metadata` and `_get_table_lineage_metadata` return\n  types similarly tightened to surface the row-shape through mypy."
  },
  "pr": {
    "number": 17217,
    "title": "feat(ingest/fivetran): support Iceberg REST Catalog and Polaris for Managed Data Lake destination",
    "url": "https://github.com/datahub-project/datahub/pull/17217"
  }
}

Usage

Current base URL: unknown

Package	Size	Install command
acryl-datahub	3.574 MB	uv pip install 'acryl-datahub @ <base-url>/artifacts/wheels/acryl_datahub-0.0.0.dev1-py3-none-any.whl'
acryl-datahub-actions	0.105 MB	uv pip install 'acryl-datahub-actions @ <base-url>/artifacts/wheels/acryl_datahub_actions-0.0.0.dev1-py3-none-any.whl'
acryl-datahub-airflow-plugin	0.108 MB	uv pip install 'acryl-datahub-airflow-plugin @ <base-url>/artifacts/wheels/acryl_datahub_airflow_plugin-0.0.0.dev1-py3-none-any.whl'
acryl-datahub-dagster-plugin	0.020 MB	uv pip install 'acryl-datahub-dagster-plugin @ <base-url>/artifacts/wheels/acryl_datahub_dagster_plugin-0.0.0.dev1-py3-none-any.whl'
acryl-datahub-gx-plugin	0.011 MB	uv pip install 'acryl-datahub-gx-plugin @ <base-url>/artifacts/wheels/acryl_datahub_gx_plugin-0.0.0.dev1-py3-none-any.whl'
prefect-datahub	0.011 MB	uv pip install 'prefect-datahub @ <base-url>/artifacts/wheels/prefect_datahub-0.0.0.dev1-py3-none-any.whl'