GoldenMatch

vgolden-suite-v0.2.1 scope: golden-suite Breaking

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

Published 15d Data Pipelines & ETL

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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 14d

The golden-suite release v0.2.1 now requires goldencheck version ≥ 3.0.0 and defaults to an Arrow‑native scan path, removing the mandatory Polars dependency.

Why it matters: If your project uses goldencheck, update its requirement to >=3.0.0; otherwise the default Arrow‑native mode eliminates the need for Polars integration.

Summary

AI summary

Minimum goldencheck version raised to >=3.0.0 with Arrow-native default and optional Polars support.

Changes in this release

Type	Severity	Summary	CVE
Dependency	Medium	goldencheck floor raised to goldencheck[polars]>=3.0.0 goldencheck floor raised to goldencheck[polars]>=3.0.0 Source: llm_adapter@2026-07-12 Confidence: high	—
Refactor	Low	default scan path switched to Arrow-native, Polars-free (pyarrow base dependency) default scan path switched to Arrow-native, Polars-free (pyarrow base dependency) Source: llm_adapter@2026-07-12 Confidence: high	—

Full changelog

Lockstep follow-on to goldencheck 3.0.0 (now on PyPI).

goldencheck floor raised to goldencheck[polars]>=3.0.0. goldencheck 3.0.0 flips the default scan path to Arrow-native and Polars-free (pyarrow is a base dep); [polars] is kept for the scan_dataframe(pl.DataFrame) overload the bundled goldenmatch quality bridge uses.

Cut after goldencheck 3.0.0 landed on PyPI (member-on-PyPI-first).

Breaking Changes

Minimum required goldencheck version increased to >=3.0.0 (base dependency pyarrow added; polars support optional via goldencheck[polars])

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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.