This release includes 3 breaking changes for platform teams planning a safe upgrade.
✓ No known CVEs patched in this version
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ReleasePort's take
Light signalGoldenSuite v0.2.0 raises the GoldenMatch minimum version to ≥3.0, enabling Arrow‑native results and defaulting to the Arrow frame backend which delivers ~36% faster performance on a 100K benchmark.
Why it matters: The release enforces a ≥3.0 GoldenMatch floor; adopting it yields ~36% speed gains on large workloads, directly impacting latency metrics for data‑intensive pipelines.
Summary
AI summaryRaises minimum GoldenMatch version to >=3.0, using Arrow-native results and enabling the Arrow frame backend by default for ~36% faster performance.
Changes in this release
| Type | Severity | Summary | CVE |
|---|---|---|---|
| Feature | Medium |
Provides opt-out environment variable GOLDENMATCH_FRAME=polars to disable the default Arrow frame backend. Provides opt-out environment variable GOLDENMATCH_FRAME=polars to disable the default Arrow frame backend. Source: granite4.1:30b@2026-07-13-audit Confidence: low |
— |
| Performance | Medium |
Raises goldenmatch floor to >=3.0, enabling Arrow-native results and default Arrow frame backend (~36% faster on 100K benchmark). Raises goldenmatch floor to >=3.0, enabling Arrow-native results and default Arrow frame backend (~36% faster on 100K benchmark). Source: llm_adapter@2026-07-12 Confidence: high |
— |
| Performance | Low |
Raises goldenmatch floor to >=3.0, enabling Arrow-native results (pyarrow.Table) via pl.from_arrow. Raises goldenmatch floor to >=3.0, enabling Arrow-native results (pyarrow.Table) via pl.from_arrow. Source: granite4.1:30b@2026-07-13-audit Confidence: low |
— |
Full changelog
Raises the goldenmatch floor to >=3.0: Arrow-native results (pyarrow.Table; migrate with pl.from_arrow) and the Arrow frame backend by default (~36% faster on the 100K zero-config benchmark; GOLDENMATCH_FRAME=polars is the opt-out). See goldenmatch's migrating-to-v3 guide.
Breaking Changes
- Minimum required GoldenMatch version raised to >=3.0
- Default frame backend switched to Arrow; opt-out via GOLDENMATCH_FRAME=polars
- Result format changed to pyarrow.Table (migrate with pl.from_arrow)
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About GoldenMatch
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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]