GoldenMatch

v1.2.7 Bugfix

This release fixes issues for SREs watching stability and regressions.

Published 3mo 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

Updates Bug fixes, Testing, and df across a mixed release.

Full changelog

Fix: Auto-config cardinality guards

Auto-config (dedupe_df(df) with no config) failed on datasets with near-unique ID columns, low-cardinality categorical columns, or long-text description fields. This release fixes all three root causes.

Bug fixes

Blocking on unique IDs — Columns with cardinality_ratio >= 0.95 (e.g., rec_id, id) are now excluded from blocking key selection. Previously, these produced single-row blocks with zero comparisons.
Exact matchkeys on low-cardinality columns — Columns with cardinality_ratio < 0.01 (e.g., state, county) no longer get exact matchkeys. Previously, these caused quadratic pair explosions (50M+ pairs → MemoryError).
Description columns routed to fuzzy matching — Long-text columns (avg_len > 50) now get a token_sort fuzzy scorer in addition to record_embedding, ensuring they contribute to matching even without a sentence-transformer model.
Safe defaults — Guards only fire when cardinality_ratio was actually measured (> 0), so manually-constructed ColumnProfile objects are unaffected.
Config-altering decisions now log warnings instead of info-level messages.

Testing

64 autoconfig tests (was 49), including boundary value tests and integration tests on real Febrl and DBLP-ACM benchmark datasets.
Full suite: 1244 tests passing.

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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.