GoldenMatch

v1.7.1 Feature

This release adds 1 notable feature for engineering teams evaluating rollout.

Published 2mo 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

Fixed duplicate web/static/.gitkeep causing PyPI publish failure and ensured frontend assets are included in goldenmatch[web] wheels.

Full changelog

Patch release fixing the v1.7.0 PyPI publish failure.

What changed

Wheel build no longer ships duplicate web/static/.gitkeep (was: force-include + packages both included it -> PyPI 400).
Publish workflow now runs scripts/build_web.py before python -m build, so goldenmatch[web] actually ships the staged frontend assets in the wheel.

v1.7.0 was tagged on GitHub but never landed on PyPI; v1.7.1 is the first 1.7.x to reach PyPI.

See PR #96 for details.

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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.