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PerformanceMemory or execution speed performanceMemory or execution speed performance
Description
Pandas version checks
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Reproducible Example
👋 Hello there!
I've found quite some classes declaring __slots__
whose bases classes do not. This negates some of the performance benefits. Fixing this should be a relatively easy performance win.
After some experimentation I've found it's not quite as easy as adding __slots__ = ()
to the bases classes. But, it should still be relatively simple.
List of affected classes I could find:
pandas.core.internals.array_manager.BaseArrayManager
pandas.core.internals.array_manager.SingleArrayManager
pandas.core.internals.blocks.Block
pandas.core.internals.blocks.CategoricalBlock
pandas.core.internals.blocks.DatetimeLikeBlock
pandas.core.internals.blocks.NumericBlock
pandas.core.internals.blocks.ObjectBlock
pandas.core.internals.managers.BaseBlockManager
pandas.core.internals.managers.SingleBlockManager
Installed Versions
n/a
Prior Performance
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PerformanceMemory or execution speed performanceMemory or execution speed performance