GoldenMatch

vgolden-suite-v0.3.5 scope: golden-suite Breaking

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

Published 20h 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

Minimum Polars version for goldenmatch raised to 3.10.

Full changelog

Lockstep floor bump after the goldenmatch 3.10.0 release: goldenmatch[polars] floor >=3.8 -> >=3.10 (3.9/3.10 close MCP surface parity both directions, 82->90 tools, mcp_tools.ts_only now empty). No other member floors changed.

Breaking Changes

Minimum Polars version for goldenmatch increased from >=3.8 to >=3.10

View diff on GitHub

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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.