GoldenMatch

vgolden-suite-v0.2.2 scope: golden-suite Breaking

This release includes 1 breaking change for platform teams planning a safe upgrade.

Published 13d Data Pipelines & ETL

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✓ No known CVEs patched

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✓ No known CVEs patched in this version

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

ReleasePort's take

Light signal

editorial:auto 13d

The golden-suite release v0.2.2 now requires polars version 3.1 or higher for the goldenmatch[polars] runtime dependency.

Why it matters: Projects using goldenmatch must ensure their polars dependency meets the >=3.1 gate to avoid incompatibility.

Summary

AI summary

Minimum goldenmatch[polars] version bumped to 3.1.

Changes in this release

Type	Severity	Summary	CVE
Dependency	Low	Bump minimum polars version to 3.1 (goldenmatch[polars]>=3.1). Bump minimum polars version to 3.1 (goldenmatch[polars]>=3.1). Source: llm_adapter@2026-07-14 Confidence: high	—

Full changelog

Lockstep floor bump: goldenmatch[polars]>=3.1 (3.1.0 = Arrow-native engine, polars optional upstream; the suite pins the [polars] extra so wall optimizations and the classic GOLDENMATCH_FRAME=polars lane stay on for suite installs).

Breaking Changes

Minimum required goldenmatch[polars] version increased to 3.1 (3.1.0 includes Arrow-native engine).

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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.