DataHub Python Builds

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

Build context

Built at 2026-03-22T20:46:16.515502+00:00.

{
  "timestamp": "2026-03-22T20:46:16.515502+00:00",
  "branch": "worktree-init-sso-browser",
  "commit": {
    "hash": "1a64d2c148cf34abadb83da9fe7afcfe0b5a67ef",
    "message": "feat(cli): warn about existing CLI tokens during `datahub init --sso`\n\nAfter SSO login, query existing access tokens for the user and print a\ncount of CLI tokens with a link to manage them in the UI. This gives\nusers visibility into token accumulation without auto-revoking tokens\nthat may be in use elsewhere. Also removes the broken _revoke_old_cli_tokens\ncall that would crash at runtime and the unused List import.\n\nCo-Authored-By: Claude Opus 4.6 (1M context) "
  },
  "base": {
    "hash": "efac72b4218dfe86138fea62eb080c3401fa4b40",
    "message": "feat(cli): add caller context to User-Agent header for operator auditability (#16655)\n\nfeat(cli): add caller context to CLI requests for operator auditability\n\nAdds best-effort caller identification (claude-code, cursor, github-actions,\nlangchain, gradle, terminal, etc.) to:\n- Mixpanel telemetry events (caller property)\n- REST emitter User-Agent header (component/caller format)\n- YAUAA parsing on the backend (agentName field)\n\nDetection uses a three-tier approach: explicit DATAHUB_CALLER env var,\nknown env-var signatures, then process-tree heuristics. Cross-platform\n(Linux + macOS), never raises, cached per-process.\n\nAlso includes: input sanitization, lazy initialization to avoid subprocess\ncalls at import time, and diagnostic CLI (python -m datahub.utilities.caller_context).\n\nCo-Authored-By: Claude Opus 4.6 (1M context) "
  },
  "pr": {
    "number": 16715,
    "title": "feat(cli): add `datahub init --sso` for browser-based SSO login",
    "url": "https://github.com/datahub-project/datahub/pull/16715"
  }
}

Usage

Current base URL: unknown

Package	Size	Install command
acryl-datahub	3.233 MB	uv pip install 'acryl-datahub @ <base-url>/artifacts/wheels/acryl_datahub-0.0.0.dev1-py3-none-any.whl'
acryl-datahub-actions	0.105 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	0.108 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	0.011 MB	uv pip install 'prefect-datahub @ <base-url>/artifacts/wheels/prefect_datahub-0.0.0.dev1-py3-none-any.whl'