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Dbt Agent Readiness

v1.3.0 Feature

This release adds 1 notable feature for engineering teams evaluating rollout.

✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Topics

ai-agents analytics-engineering claude-code claude-code-skill data-quality dbt

Summary

AI summary

fan_out_joins now respects model‑level uniqueness guarantees from dbt_utils tests, reducing false positives.

Full changelog

fan_out_joins no longer flags a join whose key set is already covered by a model-level uniqueness guarantee.

Before this release the check only recognized a column-level unique test, so a model that declares uniqueness on a column tuple through dbt_utils.unique_combination_of_columns was still flagged, even when downstream models joined it on the whole tuple. Tuples attached through a YAML anchor alias were missed for the same reason: model-level tests were never read.

What changed:

  • Model-level data_tests / tests are now parsed. dbt_utils.unique_combination_of_columns (and the older unique_combination) tuples are read from both the classic combination_of_columns: form and the newer arguments: combination_of_columns: form. YAML anchors and aliases are expanded by the loader, so an anchored test is read the same as an inline one.
  • A join key is suppressed only when every join clause that uses it covers a uniqueness guarantee on the joined model: a column-level unique test or the tested PK among the clause keys, or a unique-combination tuple that is a subset of the clause keys. A join on the whole tuple or a superset cannot fan out and is not flagged. A join on a strict subset of the tuple still can, so it stays flagged.

Verified on three public projects: Cal-ITP fan_out_joins 6 to 2, with Mattermost (6) and GitLab (26) unchanged, so no real fan-out is suppressed. New regression fixture test-fixtures/fan-out-joins/ and scripts/tests/test_fan_out_joins.py.

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