GoldenMatch

v0.6.1 Feature

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

Published 4mo 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

Summary

AI summary

GoldenMatch adds automatic PPRL parameter tuning and a 13x speedup for similarity computation.

Full changelog

PPRL Auto-Configuration

GoldenMatch now automatically picks optimal PPRL parameters from your data -- zero manual tuning needed.

goldenmatch pprl auto-config data.csv

Profiles every column, scores usefulness for privacy-preserving linkage, recommends fields, bloom filter parameters, and threshold.

Results: auto-config beats manual tuning on both benchmark datasets:

| Dataset | Auto-Config F1 | Manual F1 |
|---------|---------------|-----------|
| FEBRL4 (synthetic, 5K vs 5K) | 92.4% | 89.8% |
| NCVR (real voter data, 5K+2.5K) | 76.1% | 65.8% |

Performance

Vectorized PPRL similarity computation: 13x speedup (183s -> 14s on 5Kx5K).

MCP Tools

Two new tools for Claude Desktop:

pprl_auto_config -- analyze data, recommend PPRL config
pprl_link -- run cross-party linkage

Stats

903 tests passing
CI green on Python 3.11/3.12/3.13

pip install --upgrade goldenmatch

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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.