GoldenMatch

v0.3.1 Feature

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

Published 4mo 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 What's New, New CLI Commands, and Community across a mixed release.

Full changelog

What's New

Domain Packs (7 built-in)

Pre-built YAML rulebooks for instant domain-specific entity resolution:

Electronics -- model numbers, SKUs, specs (36 brands)
Software -- versions, editions, platforms (23 brands)
Healthcare -- NDC, NPI, ICD-10, pharma brands (20 brands)
Financial -- CUSIP, ISIN, LEI, institutions (20 brands)
Real Estate -- ZIP, APN, MLS, property attributes (10 brokerages)
People -- SSN, DOB, phone, email patterns
Retail -- UPC, EAN, GTIN, CPG brands (20 brands)

Custom packs: drop a YAML file in .goldenmatch/domains/ and it's auto-discovered.

New CLI Commands

goldenmatch evaluate -- measure precision/recall/F1 against ground truth CSV
goldenmatch incremental -- match new CSV records against an existing base dataset without re-running the full pipeline

GitHub Actions "Try It"

Zero-install demo: paste a CSV URL into the workflow_dispatch form, get deduplication results as a downloadable artifact. No setup required.

Codespaces

One-click dev environment via .devcontainer. Open a Codespace, start coding immediately.

dbt Integration

New dbt-goldenmatch package for DuckDB-based entity resolution in dbt pipelines.

Community

GitHub Discussions enabled with seed posts
Bug report and feature request issue templates
Contributing guide, Code of Conduct, Security policy
Download count badge on README

Stats

855 tests passing (+ 6 skipped)
19 CLI commands
268 PyPI downloads in first 3 days

Install / Upgrade

pip install --upgrade goldenmatch

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.