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TYP: make typing DatetimeLikeScalar a Union instead of TypeVar #40540

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Merged
merged 2 commits into from
Mar 21, 2021
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TYP: make typing DatetimeLikeScalar a Union instead of TypeVar #40540

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01fb73b
make typing DatetimeLikeScalar a Union instead of TypeVar
Dr-Irv Mar 20, 2021
6bf5628
Merge remote-tracking branch 'upstream/master' into typevardatetime
Dr-Irv Mar 21, 2021
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2 changes: 1 addition & 1 deletion pandas/_typing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -80,7 +80,7 @@
# scalars

PythonScalar = Union[str, int, float, bool]
DatetimeLikeScalar = TypeVar("DatetimeLikeScalar", "Period", "Timestamp", "Timedelta")
DatetimeLikeScalar = Union["Period", "Timestamp", "Timedelta"]
PandasScalar = Union["Period", "Timestamp", "Timedelta", "Interval"]
Scalar = Union[PythonScalar, PandasScalar]

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12 changes: 4 additions & 8 deletions pandas/core/arrays/datetimelike.py
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Expand Up @@ -563,8 +563,7 @@ def _validate_comparison_value(self, other):
raise InvalidComparison(other)

if isinstance(other, self._recognized_scalars) or other is NaT:
# error: Too many arguments for "object"
other = self._scalar_type(other) # type: ignore[call-arg]
other = self._scalar_type(other)
try:
self._check_compatible_with(other)
except (TypeError, IncompatibleFrequency) as err:
Expand Down Expand Up @@ -614,16 +613,14 @@ def _validate_shift_value(self, fill_value):
if is_valid_na_for_dtype(fill_value, self.dtype):
fill_value = NaT
elif isinstance(fill_value, self._recognized_scalars):
# error: Too many arguments for "object"
fill_value = self._scalar_type(fill_value) # type: ignore[call-arg]
fill_value = self._scalar_type(fill_value)
else:
# only warn if we're not going to raise
if self._scalar_type is Period and lib.is_integer(fill_value):
# kludge for #31971 since Period(integer) tries to cast to str
new_fill = Period._from_ordinal(fill_value, freq=self.freq)
else:
# error: Too many arguments for "object"
new_fill = self._scalar_type(fill_value) # type: ignore[call-arg]
new_fill = self._scalar_type(fill_value)

# stacklevel here is chosen to be correct when called from
# DataFrame.shift or Series.shift
Expand Down Expand Up @@ -684,8 +681,7 @@ def _validate_scalar(
raise TypeError(msg)

elif isinstance(value, self._recognized_scalars):
# error: Too many arguments for "object"
value = self._scalar_type(value) # type: ignore[call-arg]
value = self._scalar_type(value)

else:
msg = self._validation_error_message(value, allow_listlike)
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