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GoldenMatch

v1.7.0 Feature

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

Published 2mo Data Pipelines & ETL
✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ 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 What's new, Tests, and CCMS across a mixed release.

Full changelog

Ships the localhost web workbench as the optional [web] extra.

pip install 'goldenmatch[web]'
goldenmatch serve-ui my-project   # opens http://localhost:5050

What's new

  • New CLI: goldenmatch serve-ui
  • New endpoints: /api/v1/{project,rules,preview,run,labels,evaluation,unmerge,compare,sensitivity,domains,match,memory,quality,...}
  • 7-page React frontend: Project, Workbench (rule editor), Inspector (cluster + pair drilldown with NL prose), Match (target x reference), Compare (CCMS), Sensitivity (parameter sweep), Memory (Learning Memory browser).
  • Editorial gold-on-cream theme, single-process, no auth.
  • Pair drilldown shows one-line NL prose explanation (template-based, zero LLM cost).
  • Labels mirror to MemoryStore so the next pipeline run picks up steward decisions.

See packages/python/goldenmatch/README.md#web-ui for the per-page tour.

Tests

  • 106 web pytest tests
  • 12 vitest tests
  • 1500 total goldenmatch pytest passing

Background

Implementation plan: docs/superpowers/plans/2026-05-05-goldenmatch-web-ui.md
Design spec: docs/superpowers/specs/2026-05-05-goldenmatch-web-ui-design.md
PRs: #85 (feature), #87 (CI fix), #88 (docs hero), #89 (mermaid + path-filtered CI), #90 (mermaid overflow), #91 (CLAUDE.md learnings), #93 (version bump)

View diff on GitHub

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Related context

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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.

Beta — feedback welcome: [email protected]