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close out a few first issues #670

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Merged
merged 1 commit into from
May 2, 2023
Merged

close out a few first issues #670

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12 changes: 6 additions & 6 deletions pandas-stubs/core/indexes/interval.pyi
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Expand Up @@ -371,7 +371,7 @@ def interval_range(
start: _TimestampLike,
end: _TimestampLike = ...,
periods: int | None = ...,
freq: str | BaseOffset | None = ...,
freq: str | BaseOffset | pd.Timedelta | dt.timedelta | None = ...,
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is pd.Timedelta a subclass of datetime.timedelta? Could simplify this union (or keep, if it is more explicit).

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Yes, it is a subclass. We're inconsistent in the stubs. Some places we just say pd.Timedelta, others we have the union. I like the explicit aspect to make it clear that dt.timedelta is accepted.

name: Hashable = ...,
closed: IntervalClosedType = ...,
) -> IntervalIndex[Interval[pd.Timestamp]]: ...
Expand All @@ -381,7 +381,7 @@ def interval_range(
start: None = ...,
end: _TimestampLike,
periods: int | None = ...,
freq: str | BaseOffset | None = ...,
freq: str | BaseOffset | pd.Timedelta | dt.timedelta | None = ...,
name: Hashable = ...,
closed: IntervalClosedType = ...,
) -> IntervalIndex[Interval[pd.Timestamp]]: ...
Expand All @@ -391,7 +391,7 @@ def interval_range(
*,
end: None = ...,
periods: int | None = ...,
freq: str | BaseOffset | None = ...,
freq: str | BaseOffset | pd.Timedelta | dt.timedelta | None = ...,
name: Hashable = ...,
closed: IntervalClosedType = ...,
) -> IntervalIndex[Interval[pd.Timestamp]]: ...
Expand All @@ -400,7 +400,7 @@ def interval_range(
start: _TimedeltaLike,
end: _TimedeltaLike = ...,
periods: int | None = ...,
freq: str | BaseOffset | None = ...,
freq: str | BaseOffset | pd.Timedelta | dt.timedelta | None = ...,
name: Hashable = ...,
closed: IntervalClosedType = ...,
) -> IntervalIndex[Interval[pd.Timedelta]]: ...
Expand All @@ -410,7 +410,7 @@ def interval_range(
start: None = ...,
end: _TimedeltaLike,
periods: int | None = ...,
freq: str | BaseOffset | None = ...,
freq: str | BaseOffset | pd.Timedelta | dt.timedelta | None = ...,
name: Hashable = ...,
closed: IntervalClosedType = ...,
) -> IntervalIndex[Interval[pd.Timedelta]]: ...
Expand All @@ -420,7 +420,7 @@ def interval_range(
*,
end: None = ...,
periods: int | None = ...,
freq: str | BaseOffset | None = ...,
freq: str | BaseOffset | pd.Timedelta | dt.timedelta | None = ...,
name: Hashable = ...,
closed: IntervalClosedType = ...,
) -> IntervalIndex[Interval[pd.Timedelta]]: ...
2 changes: 1 addition & 1 deletion pandas-stubs/core/indexes/timedeltas.pyi
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Expand Up @@ -72,7 +72,7 @@ def timedelta_range(
start: TimedeltaConvertibleTypes = ...,
end: TimedeltaConvertibleTypes = ...,
periods: int | None = ...,
freq: str | DateOffset | None = ...,
freq: str | DateOffset | Timedelta | dt.timedelta | None = ...,
name: Hashable | None = ...,
closed: Literal["left", "right"] | None = ...,
) -> TimedeltaIndex: ...
10 changes: 8 additions & 2 deletions pandas-stubs/core/series.pyi
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Expand Up @@ -179,7 +179,13 @@ class _LocIndexerSeries(_LocIndexer, Generic[S1]):
@overload
def __getitem__(
self,
idx: MaskType | Index | Sequence[float] | list[str] | slice | _IndexSliceTuple,
idx: MaskType
| Index
| Sequence[float]
| list[str]
| slice
| _IndexSliceTuple
| Callable,
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Happy to keep it as is - it is probably not worth to try to enumerate all allowed arguments/return values.

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Yes. We have it this way in DataFrame.loc as well.

# _IndexSliceTuple is when having a tuple that includes a slice. Could just
# be s.loc[1, :], or s.loc[pd.IndexSlice[1, :]]
) -> Series[S1]: ...
Expand Down Expand Up @@ -775,7 +781,7 @@ class Series(IndexOpsMixin, NDFrame, Generic[S1]):
@overload
def apply(
self,
func: Callable[..., Scalar | Sequence | set | Mapping],
func: Callable[..., Scalar | Sequence | set | Mapping | None],
convertDType: _bool = ...,
args: tuple = ...,
**kwds,
Expand Down
44 changes: 44 additions & 0 deletions tests/test_indexes.py
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Expand Up @@ -291,6 +291,30 @@ def test_interval_range():
pd.IntervalIndex,
pd.Interval,
)
check(
assert_type(
pd.interval_range(
pd.Timestamp(2000, 1, 1),
pd.Timestamp(2010, 1, 1),
freq=pd.Timedelta(days=30),
),
"pd.IntervalIndex[pd.Interval[pd.Timestamp]]",
),
pd.IntervalIndex,
pd.Interval,
)
check(
assert_type(
pd.interval_range(
pd.Timestamp(2000, 1, 1),
pd.Timestamp(2010, 1, 1),
freq=dt.timedelta(days=30),
),
"pd.IntervalIndex[pd.Interval[pd.Timestamp]]",
),
pd.IntervalIndex,
pd.Interval,
)
check(
assert_type(
pd.interval_range(pd.Timestamp(2000, 1, 1), dt.datetime(2010, 1, 1), 5),
Expand All @@ -308,6 +332,26 @@ def test_interval_range():
pd.IntervalIndex,
pd.Interval,
)
check(
assert_type(
pd.interval_range(
pd.Timedelta("1D"), pd.Timedelta("10D"), freq=pd.Timedelta("2D")
),
"pd.IntervalIndex[pd.Interval[pd.Timedelta]]",
),
pd.IntervalIndex,
pd.Interval,
)
check(
assert_type(
pd.interval_range(
pd.Timedelta("1D"), pd.Timedelta("10D"), freq=dt.timedelta(days=2)
),
"pd.IntervalIndex[pd.Interval[pd.Timedelta]]",
),
pd.IntervalIndex,
pd.Interval,
)
check(
assert_type(
pd.interval_range(end=pd.Timedelta("10D"), periods=10, freq="D"),
Expand Down
12 changes: 12 additions & 0 deletions tests/test_series.py
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Expand Up @@ -1820,3 +1820,15 @@ def test_convert_dtypes_dtype_backend() -> None:
s = pd.Series([1, 2, 3, 4])
s1 = s.convert_dtypes(dtype_backend="numpy_nullable")
check(assert_type(s1, pd.Series), pd.Series)


def test_apply_returns_none() -> None:
# GH 557
s = pd.Series([1, 2, 3])
check(assert_type(s.apply(lambda x: None), pd.Series), pd.Series)


def test_loc_callable() -> None:
# GH 586
s = pd.Series([1, 2])
check(assert_type(s.loc[lambda x: x > 1], pd.Series), pd.Series)
14 changes: 14 additions & 0 deletions tests/test_timefuncs.py
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Expand Up @@ -1071,6 +1071,20 @@ def test_timedelta_range() -> None:
),
pd.TimedeltaIndex,
)
check(
assert_type(
pd.timedelta_range("1 day", "10 days", freq=pd.Timedelta("2 days")),
pd.TimedeltaIndex,
),
pd.TimedeltaIndex,
)
check(
assert_type(
pd.timedelta_range("1 day", "10 days", freq=dt.timedelta(days=2)),
pd.TimedeltaIndex,
),
pd.TimedeltaIndex,
)


def test_dateoffset_freqstr() -> None:
Expand Down