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Fix issue for pandera allowing generic Series to work #492

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merged 3 commits into from
Jan 3, 2023
Merged

Fix issue for pandera allowing generic Series to work #492

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c24eeb0
split Series[IntervalT] into separate __new__
Dr-Irv Jan 2, 2023
80a9a94
add test for generic series
Dr-Irv Jan 2, 2023
1c9de71
Update reference to GH issue
Dr-Irv Jan 2, 2023
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36 changes: 33 additions & 3 deletions pandas-stubs/core/series.pyi
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Original file line number Diff line number Diff line change
Expand Up @@ -70,6 +70,7 @@ from typing_extensions import (
)
import xarray as xr

from pandas._libs.interval import Interval
from pandas._libs.missing import NAType
from pandas._libs.tslibs import BaseOffset
from pandas._typing import (
Expand All @@ -94,7 +95,6 @@ from pandas._typing import (
IgnoreRaise,
IndexingInt,
IntervalClosedType,
IntervalT,
JoinHow,
JsonSeriesOrient,
Level,
Expand Down Expand Up @@ -216,13 +216,43 @@ class Series(IndexOpsMixin, NDFrame, Generic[S1]):
@overload
def __new__(
cls,
data: IntervalIndex[IntervalT],
data: IntervalIndex[Interval[int]],
index: Axes | None = ...,
dtype=...,
name: Hashable | None = ...,
copy: bool = ...,
fastpath: bool = ...,
) -> Series[IntervalT]: ...
) -> Series[Interval[int]]: ...
@overload
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might be nice to add a TODO referencing the mypy issue

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might be nice to add a TODO referencing the mypy issue

I didn't research whether there exists a mypy issue, or how to create a small sample to replicate.

I could add a comment indicating that we prefer the Series[IntervalT] notation, but that it doesn't seem to work and reference the original pandas-stubs issue. Let me know if I should do that.

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Would something like the following work?

T = TypeVar("T", float, int, Timestamp, Timedelta)

        data: IntervalIndex[Interval[T]],
        ....
    ) -> Series[Interval[T]]: ...

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I can't see how this would work, because we have:

class IntervalIndex(IntervalMixin, ExtensionIndex, Generic[IntervalT]):

Since IntervalIndex is generic, and Interval is generic, you can't make IntervalIndex depend on the "inner" generic type.

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Okay, sorry for the trouble.

def __new__(
cls,
data: IntervalIndex[Interval[float]],
index: Axes | None = ...,
dtype=...,
name: Hashable | None = ...,
copy: bool = ...,
fastpath: bool = ...,
) -> Series[Interval[float]]: ...
@overload
def __new__(
cls,
data: IntervalIndex[Interval[Timestamp]],
index: Axes | None = ...,
dtype=...,
name: Hashable | None = ...,
copy: bool = ...,
fastpath: bool = ...,
) -> Series[Interval[Timestamp]]: ...
@overload
def __new__(
cls,
data: IntervalIndex[Interval[Timedelta]],
index: Axes | None = ...,
dtype=...,
name: Hashable | None = ...,
copy: bool = ...,
fastpath: bool = ...,
) -> Series[Interval[Timedelta]]: ...
@overload
def __new__(
cls,
Expand Down
15 changes: 15 additions & 0 deletions tests/test_series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,11 +7,13 @@
TYPE_CHECKING,
Any,
Dict,
Generic,
Hashable,
Iterable,
Iterator,
List,
Sequence,
TypeVar,
cast,
)

Expand Down Expand Up @@ -1362,3 +1364,16 @@ def test_AnyArrayLike_and_clip() -> None:
s2 = ser.clip(upper=ser)
check(assert_type(s1, pd.Series), pd.Series)
check(assert_type(s2, pd.Series), pd.Series)


def test_pandera_generic() -> None:
# GH 471
T = TypeVar("T")

class MySeries(pd.Series, Generic[T]):
...

def func() -> MySeries[float]:
return MySeries[float]([1, 2, 3])

func()