DataHub Python Builds

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

Build context

Built at 2026-08-28T00:03:04.142055+00:00.

{
  "timestamp": "2026-08-28T00:03:04.142055+00:00",
  "branch": "bq-profiling/08-profiler-core",
  "commit": {
    "hash": "85aac261545595972bf543a76d31315be18b7dbe",
    "message": "Merge branch 'bq-profiling/07-discovery-scanprobe' into bq-profiling/08-profiler-core\n\nCo-authored-by: Cursor \n\n# Conflicts:\n#\tmetadata-ingestion/tests/unit/bigquery/test_bigquery_profiler.py\n#\tmetadata-ingestion/tests/unit/bigquery/test_bigquery_profiling.py"
  },
  "base": {
    "hash": "c255f74f82d933d2ed17a5db981701ec16ed99c0",
    "message": "fix(ingestion/bigquery): run sampling before IS-NOT-NULL fallback; cheap probe\n\nResolve scan/probe review comments on partition discovery:\n- _get_partitions_with_sampling now accepts the already-resolved partition\n  columns/types and reuses them when INFORMATION_SCHEMA.COLUMNS and DDL are both\n  unavailable, so the TABLESAMPLE/date-sample last resort still runs.\n- _find_real_partition_values tries sampling for a real latest value before the\n  IS NOT NULL fallback, so the date-sample path is reachable for DATE/TIMESTAMP\n  partitions instead of being pre-empted by an unpruned full-scan filter.\n- The require-filter probe uses the cheap PARTITION_FILTER_PROBE (SELECT 1 ...\n  LIMIT) rather than the renamed COUNT(*) constant, which full-scanned a\n  non-require-filter table.\n\nMerges PR6 up. Adds regression tests for the max_partition_id DATETIME range,\nsampling-with-known-columns, and updates probe-detection test mocks to the new\nSELECT 1 probe shape.\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	5.100 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'