Comments (4)
Can you verify that the version of numpy used at runtime was unchanged?
Unfortunately no - unless we have a hard pin, we don't save what version was used in the benchmark.
Also, not sure how you've automated the reporting, but it would be cool to put the regression factor next to the benchmark name (some of the regressions are small ~10% change).
Great idea - I'm thinking something like
- algos.isin.IsInWithLongTupples.time_isin - 14% (0.2ms)
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Surprised by the one. Is it possible the building with NumPy 2.0rc1 induced a performance regression?
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Potentially.
Can you verify that the version of numpy used at runtime was unchanged?
The is_monotonic
change looks concerning.
Also, not sure how you've automated the reporting, but it would be cool to put the regression factor next to the benchmark name (some of the regressions are small ~10% change).
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@lithomas1 - I've updated the OP with the new format.
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