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GoldenMatch

v1.25.0 Feature

This release adds 3 notable features for engineering teams evaluating rollout.

Published 1mo Data Pipelines & ETL
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ 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

Summary

AI summary

Fix GoldenCheck quality scan now serializes findings correctly.

Changes in this release

Feature Medium

Adds columnar pair-stream scorer entry points.

Adds columnar pair-stream scorer entry points.

Source: granite4.1:30b@2026-06-04-audit

Confidence: low

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Feature Medium

Implements two-frame ClusterFrames representation.

Implements two-frame ClusterFrames representation.

Source: granite4.1:30b@2026-06-04-audit

Confidence: low

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Feature Medium

Adds hash-by-cluster_id partitioner.

Adds hash-by-cluster_id partitioner.

Source: granite4.1:30b@2026-06-04-audit

Confidence: low

 —
Performance High

Introduces native Rust kernel for score_blocks_columnar inner loop.

Introduces native Rust kernel for score_blocks_columnar inner loop.

Source: granite4.1:30b@2026-06-04-audit

Confidence: low

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Performance High

Provides native Rust/Arrow-C kernels for build_clusters, record_fingerprints, dedup_pairs, and max-weight-spanning-tree oversized-split path.

Provides native Rust/Arrow-C kernels for build_clusters, record_fingerprints, dedup_pairs, and max-weight-spanning-tree oversized-split path.

Source: granite4.1:30b@2026-06-04-audit

Confidence: low

 —
Performance Medium

Enables default memory slimming via golden/bucket optimizations (‑2.6 GB, ‑3.8 GB at 10M rows).

Enables default memory slimming via golden/bucket optimizations (‑2.6 GB, ‑3.8 GB at 10M rows).

Source: granite4.1:30b@2026-06-04-audit

Confidence: low

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Bugfix Medium

Fixes serialization of findings in GoldenCheck quality scan-only path.

Fixes serialization of findings in GoldenCheck quality scan-only path.

Source: llm_adapter@2026-06-04

Confidence: high

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Bugfix Low

Fixes flaky behavior of prep-cache id() recycle function.

Fixes flaky behavior of prep-cache id() recycle function.

Source: llm_adapter@2026-06-04

Confidence: high

 —
Full changelog

Arrow-native pipeline groundwork (roadmap Phases 0-6), single-node memory/wall optimizations, an optional native Rust kernel for the cluster oversized-split path, and several user-facing bug fixes.

All Arrow / native work is additive and opt-in: the default pure-Python + Polars pipeline is behavior-unchanged, and remains the byte-for-byte reference. The columnar entry points and goldenmatch._native kernels are exercised by the bench/profiler harnesses and wired in behind follow-up parity work.

Highlights:

  • Columnar pair-stream scorer entry points + native columnar inner loop for score_blocks_columnar; two-frame ClusterFrames representation; hash-by-cluster_id partitioner.
  • Native (Rust / Arrow-C) kernels in the optional goldenmatch._native extension: build_clusters, record_fingerprints, dedup_pairs, and a max-weight-spanning-tree oversized-split kernel.
  • Standardization native Polars chains (name_proper, address) and golden/bucket memory slimming (default ON): -2.6 GB and -3.8 GB peak at 10M rows.
  • Fix: GoldenCheck quality scan silently dropped every finding in the scan-only path (MCP scan_quality, A2A quality skill, web /api/v1/quality). Findings now serialize correctly.
  • Fix: prep-cache id() recycle flake.

Full detail: packages/python/goldenmatch/CHANGELOG.md (section 1.25.0). PRs #588-#650.

Note: 1.25.0 was published to PyPI via workflow_dispatch on 2026-06-01; this Release backfills the missing tag/Release object so release history stays consistent.

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Related context

Related tools

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.

Beta — feedback welcome: [email protected]