This release adds 3 notable features for engineering teams evaluating rollout.
Published 2mo
Data Pipelines & ETL
✓ No known CVEs patched
✓ 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 summaryAdds AutoConfigController, ComplexityProfile, RunHistory, HeuristicRefitPolicy and related components.
Full changelog
Python v1.7+v1.8 parity. Adds AutoConfigController, ComplexityProfile, RunHistory, HeuristicRefitPolicy, 7 base refit rules, StopReason telemetry, best-effort commit. Public API: autoConfigureRowsIterate. 764 tests passing.
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About GoldenMatch
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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]