fix(polars): fall back to plain collect when the streaming engine is rejected - #432
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…cted The native Polars backend requested collect(engine="streaming") and caught only TypeError, but polars 1.1-1.24 reject the value with ValueError (Invalid engine argument), which propagated and broke fd.clean on the declared polars floor. Broaden the catch to (TypeError, ValueError) so those versions fall back to a plain collect(); modern polars, which accepts the engine, is unchanged. Found by the production-readiness campaign (FDC-L1b-001).
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FreshData benchmark report —
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| fixture | n_rows | n_cols | p50 s | p95 s | peak MB | repair % | false-repair % | preserve % | trust | monotonic | export % |
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Authored-code reduction (Metric 6)
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Summary
The native Polars backend requests
collect(engine="streaming")and caught onlyTypeError. Polars 1.1–1.24 reject that value withValueError: Invalid engine argument engine='streaming', which propagated and brokefd.clean(df, engine="polars")at the declaredpolars>=1.0floor. (Modern polars — and the CI-pinned versions — accept the engine, so this was invisible in CI.)Change
Broaden the catch in
PolarsEngine._collectto(TypeError, ValueError), so an unsupported streaming engine falls back to a plaincollect()(correct, just non-streaming), exactly as it already did for the legacystreaming=keyword. No behaviour change on any polars that accepts the engine.Tests
tests/test_execution/test_dispatch_and_config.py: a fake lazy frame that raisesValueErrorforengine="streaming"now falls back to a plaincollect().Verification
ruff checkandmypyclean.Found by the production-readiness campaign (lane L1b, FDC-L1b-001). Two related floor findings are being handled separately: FDC-L1b-002 (scikit-learn 1.0.2 + missforest) and FDC-L1b-003 (pandas 2.0/2.1 nullable-Int64 band) — see the campaign report; both may call for a floor bump rather than a code change.