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test(preflight): pin #152's schema-type-aware label diversity in the parity harness - #154
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…parity harness #152 shipped the labelSchemaType/isStringSQLType refinement without parity coverage — the exact case it fixes (labels '1' vs '1.0' under a VARCHAR label, which the blanket collapse falsely rejected) was pinned by nothing. Two new golden cases close that: - tabular-varchar-numeric-labels: VARCHAR label → dtype=str in-cluster, no collapse, 2 classes → accept on BOTH sides - tabular-float-numeric-labels: FLOAT label → numeric read collapses 1/1.0 → reject on BOTH sides The harness now honors an explicit per-case schema (mirroring the --schema flow) on both the generator and the Go side, so dtype- sensitive verdicts stay comparable. Goldens regenerated from the real Python validators (25 cases green). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
saadqbal
approved these changes
Jul 7, 2026
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Summary
#152's refinement (label diversity keyed on the label's SQL type) is correct — but it merged with no parity coverage: the exact case it fixes was pinned by nothing, so a regression back to the blanket collapse would pass every test.
Two golden cases close that, verified against the real Python validators (
_label_read_kwargsdtype=str pinning):tabular-varchar-numeric-labels— '1' vs '1.0' under a VARCHAR label = 2 classes → accept/accept (the case the blanket collapse falsely rejected)tabular-float-numeric-labels— same values under a FLOAT label collapse → reject/rejectPlus harness support for an explicit per-case
schema(mirroring--schema) so both sides derive dtype-sensitive verdicts from the same source. 25 parity cases green; full suite green.🤖 Generated with Claude Code