DataHub Python Builds

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

Build context

Built at 2026-08-27T19:41:54.583396+00:00.

{
  "timestamp": "2026-08-27T19:41:54.583396+00:00",
  "branch": "bq-profiling/08-profiler-core",
  "commit": {
    "hash": "d82c6fd00f8f19e59984bf52d51e3499c8b08be1",
    "message": "fix(bigquery-profiling): drop TABLESAMPLE from partition path; label + cache deferred external\n\n- P1: _build_partition_profiling_sql no longer emits TABLESAMPLE. BigQuery\n  applies TABLESAMPLE to whole-table blocks before the partition WHERE and\n  sizes the percentage from the whole-table row count, so a small target\n  partition of a large table could come back empty/undersized. Rely on the\n  WHERE + row limit and let the downstream SQLAlchemy profiler sample the\n  materialized partition instead.\n- P2: the deferred external-table path now threads the dataset partition\n  metadata cache into discovery and labels the profile with the single\n  partition ID (type=PARTITION) when the predicate scanned exactly one\n  partition, mirroring the inline path.\n- P3: correct a stale comment (skip_stale_tables is opt-in, not default-on).\n\nTests updated to assert the partition path never samples and the unpartitioned\npath still does; added a regression test for the deferred external label+cache.\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	5.096 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'