DataHub Python Builds

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

Build context

Built at 2026-09-12T22:26:29.142150+00:00.

{
  "timestamp": "2026-09-12T22:26:29.142150+00:00",
  "branch": "databricks-pipeline-expectations",
  "commit": {
    "hash": "7d805d3eabfce298e2387ea2e98af0ff868c4487",
    "message": "feat(unity): name pipeline expectations and reflect action severity\n\nGive each Lakeflow (DLT) expectation its own custom assertion type\n(\"Databricks Pipeline Expectation\") and carry the expectation name in the\ndescription so it is distinguishable in the assertions list (the list renders a\ncustom assertion's name from its description, not the structured native fields).\nSurface the expectation's action (ALLOW/DROP/FAIL) as a custom property and map\nit to failure severity: expect_or_fail / expect_or_drop are hard failures (HIGH),\na plain expect only warns (LOW).\n\nCo-authored-by: Cursor "
  },
  "base": {
    "hash": "3be504bba5d190f30dc7a9afac00bd6279454750",
    "message": "feat(unity): show column in data-quality assertion name and label source\n\nName each Databricks Lakehouse Monitoring completeness assertion with its\ncolumn (\"Null count for column X is 0\") and set the custom assertion type to\n\"Databricks Lakehouse Monitor\". The assertions list renders a custom\nassertion's name from its description and does not fetch the structured\nscope/aggregation fields, so the column is carried in the description while the\nstructured fields remain for future-proofing.\n\nCo-authored-by: Cursor "
  },
  "pr": {
    "number": 19755,
    "title": "feat(ingestion/unity): ingest Lakeflow pipeline expectations as assertions",
    "url": "https://github.com/datahub-project/datahub/pull/19755"
  }
}

Usage

Current base URL: unknown

Package	Size	Install command
acryl-datahub	5.193 MB	uv pip install 'acryl-datahub @ <base-url>/artifacts/wheels/acryl_datahub-0.0.0.dev1-py3-none-any.whl'
acryl-datahub-actions	0.117 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	0.072 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	0.021 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	0.019 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'