DataHub Python Builds

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

Build context

Built at 2026-06-19T19:31:28.711903+00:00.

{
  "timestamp": "2026-06-19T19:31:28.711903+00:00",
  "branch": "fix/unity-usage-drain-before-parse",
  "commit": {
    "hash": "9b7c423f409c4f2a651d3e754961ba3abf97fc8c",
    "message": "feat(ingest/unity): cache drained query-history audit log via local_temp_path\n\nMirrors the Snowflake query extractor's use_cached_audit_log optimization. When the\n(hidden, dev/advanced) local_temp_path is set, the drained query history is buffered into\na named, window-keyed SQLite file under that directory and KEPT across runs: the next run\nover the same time window reloads it and skips re-fetching, including after a crash\n(the reload-from-file route). The filename is keyed by usage source (system-tables vs API)\nand the start/end window, so a leftover file is never reused for a stale window; files for\nother windows are not pruned automatically. When local_temp_path is unset, behavior is\nunchanged: an ephemeral, self-cleaning FileBackedList with no caching.\n\nUnlike BigQuery (which deletes the file after every run) this persists like Snowflake, but\nthe window-keyed name avoids Snowflake's stale-cache caveat. Adds cache persist/reload and\ncache-hit unit tests; live-validated the named shared-connection drain path."
  },
  "base": {
    "hash": "c914c27831ee9bc1af2a0fb20c0e40a2fb820894",
    "message": "feat(databricks): optimize usage extraction via system-table lineage (#17961)"
  },
  "pr": {
    "number": 17971,
    "title": "fix(ingest/unity): drain query history before parsing to avoid operation-handle eviction",
    "url": "https://github.com/datahub-project/datahub/pull/17971"
  }
}

Usage

Current base URL: unknown

Package Size Install command
acryl-datahub 4.143 MB uv pip install 'acryl-datahub @ <base-url>/artifacts/wheels/acryl_datahub-0.0.0.dev1-py3-none-any.whl'
acryl-datahub-actions 0.118 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 0.067 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 0.012 MB uv pip install 'prefect-datahub @ <base-url>/artifacts/wheels/prefect_datahub-0.0.0.dev1-py3-none-any.whl'