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PERF/TYP: typing cast in __getitem__ gives quite some overhead #44624

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Merged
merged 4 commits into from
Dec 3, 2021
Merged

PERF/TYP: typing cast in __getitem__ gives quite some overhead #44624

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PERF/TYP: typing cast in __getitem__ gives quite some overhead
jorisvandenbossche Nov 26, 2021
4f5f41f
Merge remote-tracking branch 'upstream/master' into perf-datetime-get…
jorisvandenbossche Dec 3, 2021
9c1a110
stringify
jorisvandenbossche Dec 3, 2021
be77452
categorical as well
jorisvandenbossche Dec 3, 2021
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2 changes: 1 addition & 1 deletion pandas/core/arrays/categorical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -509,7 +509,7 @@ def astype(self, dtype: AstypeArg, copy: bool = True) -> ArrayLike:
result = self.copy() if copy else self

elif is_categorical_dtype(dtype):
dtype = cast(Union[str, CategoricalDtype], dtype)
dtype = cast("Union[str, CategoricalDtype]", dtype)

# GH 10696/18593/18630
dtype = self.dtype.update_dtype(dtype)
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7 changes: 5 additions & 2 deletions pandas/core/arrays/datetimelike.py
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Expand Up @@ -331,10 +331,13 @@ def __getitem__(
This getitem defers to the underlying array, which by-definition can
only handle list-likes, slices, and integer scalars
"""
# Use cast as we know we will get back a DatetimeLikeArray or DTScalar
# Use cast as we know we will get back a DatetimeLikeArray or DTScalar,
# but skip evaluating the Union at runtime for performance
# (see https://github.com/pandas-dev/pandas/pull/44624)
result = cast(
Union[DatetimeLikeArrayT, DTScalarOrNaT], super().__getitem__(key)
"Union[DatetimeLikeArrayT, DTScalarOrNaT]", super().__getitem__(key)
)
result = super().__getitem__(key)
if lib.is_scalar(result):
return result
else:
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