GoldenMatch

v1.17.1 Feature

This release adds 3 notable features 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 throughput ceiling, achieving ~10‑100× faster bulk writes to gm_match_log.

Full changelog

goldenmatch 1.17.1 -- 2026-05-22

Patch release for the throughput fix landed in PR #426.

Fix

User reported post-#423 ceiling at ~125 rows/sec writing to
gm_match_log. Root cause: psycopg3 executemany is NOT pipelined
without an explicit with conn.pipeline(): context, so each batch
incurred N round-trips at ~7ms RTT to managed Postgres.

Three changes:

cursor.copy() on psycopg3 in log_matches_batch. ~10-100x
faster on bulk loads. Falls back to executemany for non-psycopg3
cursors (SQLite / DuckDB test paths).
Buffer pairs across blocks before flushing. Default
GOLDENMATCH_MATCH_LOG_FLUSH_PAIRS=10000. Set to 1 for per-block
flushing (preserves historical incremental-progress behavior).
GOLDENMATCH_SKIP_MATCH_LOG=1 opt-out for nightly-cron
pipelines that only consume gm_clusters / gm_golden_records.

Expected impact

User's ~3M-pair workload: previously ~5 hours of writes -> projected
< 5 min.

Full CHANGELOG: https://github.com/benseverndev-oss/goldenmatch/blob/v1.17.1/packages/python/goldenmatch/CHANGELOG.md

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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.