DataHub Python Builds

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

Build context

Built at 2026-09-12T19:57:51.724613+00:00.

{
  "timestamp": "2026-09-12T19:57:51.724613+00:00",
  "branch": "databricks-pipeline-expectations",
  "commit": {
    "hash": "b658a62c9616a9417b17c94fc5c0055a33cf2fb2",
    "message": "fix(unity): harden pipeline expectation extraction (PR review)\n\nAddress review feedback on the Lakeflow expectations extractor:\n\n- Per-pipeline target lookup failures are caught and reported, so one bad\n  pipeline no longer aborts extraction for the rest.\n- Read the pipeline event log to page-token exhaustion via a lazy generator,\n  stopping once the newest update is consumed. Removes the fixed 20-page cap\n  that could silently truncate events and undercount failures.\n- Include the metastore id in the assertion's dataset URN when\n  include_metastore is enabled, so it resolves to the published dataset.\n- Split dataset identifiers on unquoted dots (handles backtick-quoted parts).\n- Extract expectations before the warehouse-gated profiling block, so the\n  REST-only path still runs when the SQL warehouse fails to start.\n- Add tests for schema-qualified/quoted/metastore URN resolution, per-pipeline\n  target errors, and graceful degradation on malformed event payloads.\n\nCo-authored-by: Cursor "
  },
  "base": {
    "hash": "030ac00044291bf7340c19d7364fa948ebfb63e6",
    "message": "refactor(unity): extract shared warehouse-start helper; tidy DQ tests\n\n- Extract _start_warehouse_or_report() so the hive, profiling, and data-quality\n  stages no longer duplicate the start / not-found-failure / wait sequence.\n- Hoist the duplicated mock_proxy fixture to module level in the proxy tests.\n- Move the DQ test window_end inside the extractor's query window so the golden\n  timestamps mirror a real _profile_metrics row.\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

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Package Size Install command
acryl-datahub 5.192 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'