GoldenMatch

vgoldenmatch-native-v0.1.2 scope: goldenmatch-native Bugfix

This release fixes issues for SREs watching stability and regressions.

Published 1mo Data Pipelines & ETL

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Topics

data-cleaning data-engineering data-matching data-quality deduplication entity-resolution

+14 more

fellegi-sunter fuzzy-matching knowledge-graph llm master-data-management mcp-server polars pprl python record-linkage rust splink typescript zero-config

Summary

AI summary

Fixes the bucket_score slowdown caused by the pre‑built 0.1.0 wheel.

Changes in this release

Type	Severity	Summary	CVE
Bugfix	Medium	Fixes ~44x slowdown of bucket_score in the published wheel. Fixes ~44x slowdown of bucket_score in the published wheel. Source: llm_adapter@2026-06-04 Confidence: high	—

Full changelog

Republish of the native acceleration kernels. The 0.1.0 wheel (2026-05-27) predated build_exclude_set / ExcludeSet (#552, 2026-05-28), so any env that pip-installed it instead of building in-tree fell to the per-bucket-call HashSet rebuild and saw bucket_score run ~44x slower (issue #688). This wheel ships the Arc-handle exclude path plus all kernel work since.

Fixes the bucket_score slowdown for users on the published wheel. See #688 and #689.

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Earlier breaking changes

v3.1.0 `GOLDENMATCH_FRAME=polars` now requires the `[polars]` extra; raises error without it.
vgoldencheck-v3.0.0 `inferred_type` emits neutral dtype vocabulary (str/int/uint/float/date/datetime/bool/other) instead of raw Polars dtypes.
vgoldencheck-v3.0.0 'inferred_type' now emits a neutral dtype vocabulary instead of raw Polars dtype strings.
vgoldencheck-v3.0.0 `scan_file`, `scan_dataframe`, and CLI `check` now run without Polars, using Arrow-native pyarrow.Table.
v3.0.0 Result frames now return pyarrow.Table instead of Polars DataFrame.