DataHub Python Builds

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

Build context

Built at 2026-08-27T23:20:46.206832+00:00.

{
  "timestamp": "2026-08-27T23:20:46.206832+00:00",
  "branch": "bq-profiling/08-profiler-core",
  "commit": {
    "hash": "e01f5e46fed41c8c6fe13f072380b80d98cb8b8b",
    "message": "fix(ingest/bigquery): correct profiler sampling + date-window interactions\n\nAddress reviewer findings on the profiler core:\n\n- Date windowing no longer ANDs a today-based range onto a discovered range\n  predicate (half-open month/timestamp partitions). Columns already bounded by a\n  range are left untouched; the today fallback applies only to unpinned columns.\n- Unpartitioned sampling no longer emits an inline TABLESAMPLE. The SQLAlchemy\n  profiler adapter (mirrored by the GE profiler) already samples the source table\n  once; emitting it here double-sampled and changed the default path vs. the\n  pre-rewrite profiler. Sampling is deferred downstream.\n- The per-dataset partition-metadata cache is now guarded by a lock and warmed in\n  the main thread before deferred external discovery fans out, so worker threads\n  no longer race to run the dataset-wide INFORMATION_SCHEMA query.\n\nCo-authored-by: Cursor "
  },
  "base": {
    "hash": "cf410e25b8e25921da3c9da31ff90f153c58dea6",
    "message": "fix(bigquery-profiling): resolve scan/probe review comments\n\n- direct discovery: widen DATETIME/TIMESTAMP latest-row value to a\n  granularity-aware half-open range instead of an instant equality\n- sampling: build the composite filter from one co-occurring row\n  (_first_complete_row) and skip when no row covers all partition columns,\n  avoiding fabricated / partial tuples that pass existence verification\n- fallback: pass resolved column_types so typed predicates (e.g. INT64\n  year/month/day) aren't quoted as strings\n- tests: extract make_partition_info helper; cover the co-occurrence and\n  direct-temporal-range fixes\n\nCo-authored-by: Cursor "
  },
  "pr": {
    "number": 19486,
    "title": "feat(ingest/bigquery): profiler core rewrite + BigQueryProfilingConfig",
    "url": "https://github.com/datahub-project/datahub/pull/19486"
  }
}

Usage

Current base URL: unknown

Package	Size	Install command
acryl-datahub	5.097 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'