CLN: FrameOrSeries(Union) (#272)

* CLN: FrameOrSeries(Union)

* let nightly pass for now; clean _typing a tiny bit

* revert workflow changes

Author: twoertwein

pandas-stubs/_typing.pyi

@@ -27,7 +27,6 @@ from typing import (
 import numpy as np
 from numpy import typing as npt
 from pandas.core.arrays import ExtensionArray
-from pandas.core.frame import DataFrame
 from pandas.core.generic import NDFrame
 from pandas.core.indexes.base import Index
 from pandas.core.series import Series
@@ -80,14 +79,10 @@ class WriteExcelBuffer(WriteBuffer[bytes], Protocol):
     def truncate(self, size: Union[int, None] = ...) -> int: ...
 
 FilePath = Union[str, PathLike[str]]
+FilePathOrBuffer = Union[
+    FilePath, IO[AnyStr], RawIOBase, BufferedIOBase, TextIOBase, TextIOWrapper, mmap
+]
 
-Buffer = Union[IO[AnyStr], RawIOBase, BufferedIOBase, TextIOBase, TextIOWrapper, mmap]
-FileOrBuffer = Union[str, Buffer[AnyStr]]
-FilePathOrBuffer = Union[PathLike[str], FileOrBuffer[AnyStr]]
-FilePathOrBytesBuffer = Union[PathLike[str], WriteBuffer[bytes]]
-
-FrameOrSeries = TypeVar("FrameOrSeries", bound=NDFrame)
-FrameOrSeriesUnion = Union[DataFrame, Series]
 Axis = Union[str, int]
 IndexLabel = Union[Hashable, Sequence[Hashable]]
 Label = Optional[Hashable]
@@ -130,21 +125,9 @@ Scalar = Union[
 ]
 ScalarT = TypeVar("ScalarT", bound=Scalar)
 # Refine the definitions below in 3.9 to use the specialized type.
-np_ndarray_int8 = npt.NDArray[np.int8]
-np_ndarray_int16 = npt.NDArray[np.int16]
-np_ndarray_int32 = npt.NDArray[np.int32]
 np_ndarray_int64 = npt.NDArray[np.int64]
-np_ndarray_uint8 = npt.NDArray[np.uint8]
-np_ndarray_uint16 = npt.NDArray[np.uint16]
-np_ndarray_uint32 = npt.NDArray[np.uint32]
-np_ndarray_uint64 = npt.NDArray[np.uint64]
-np_ndarray_int = Union[
-    np_ndarray_int8, np_ndarray_int16, np_ndarray_int32, np_ndarray_int64
-]
-np_ndarray_uint = Union[
-    np_ndarray_uint8, np_ndarray_uint16, np_ndarray_uint32, np_ndarray_uint64
-]
-np_ndarray_anyint = Union[np_ndarray_int, np_ndarray_uint]
+np_ndarray_int = npt.NDArray[np.signedinteger]
+np_ndarray_anyint = npt.NDArray[np.integer]
 np_ndarray_bool = npt.NDArray[np.bool_]
 np_ndarray_str = npt.NDArray[np.str_]
 

pandas-stubs/core/generic.pyi

@@ -12,8 +12,11 @@ from typing import (
 )
 
 import numpy as np
+from pandas import (
+    DataFrame,
+    Index,
+)
 from pandas.core.base import PandasObject
-from pandas.core.indexes.base import Index
 import pandas.core.indexing as indexing
 import sqlalchemy.engine
 
@@ -29,8 +32,6 @@ from pandas._typing import (
     FilePathOrBuffer,
     FileWriteMode,
     FillnaOptions,
-    FrameOrSeries,
-    FrameOrSeriesUnion,
     HashableT,
     HDFCompLib,
     IgnoreRaise,
@@ -55,11 +56,11 @@ class NDFrame(PandasObject, indexing.IndexingMixin):
     __hash__: ClassVar[None]  # type: ignore[assignment]
 
     def set_flags(
-        self: FrameOrSeries,
+        self: NDFrameT,
         *,
         copy: bool = ...,
         allows_duplicate_labels: bool | None = ...,
-    ) -> FrameOrSeries: ...
+    ) -> NDFrameT: ...
     @property
     def attrs(self) -> dict[Hashable | None, Any]: ...
     @attrs.setter
@@ -290,7 +291,7 @@ class NDFrame(PandasObject, indexing.IndexingMixin):
         axis: SeriesAxisType = ...,
         level: Level | None = ...,
         drop_level: _bool = ...,
-    ) -> FrameOrSeriesUnion: ...
+    ) -> DataFrame | Series: ...
     def __delitem__(self, idx: Hashable): ...
     def get(self, key: object, default: Dtype | None = ...) -> Dtype: ...
     def reindex_like(
@@ -357,8 +358,8 @@ class NDFrame(PandasObject, indexing.IndexingMixin):
         regex: _str | None = ...,
         axis=...,
     ) -> NDFrame: ...
-    def head(self: FrameOrSeries, n: int = ...) -> FrameOrSeries: ...
-    def tail(self: FrameOrSeries, n: int = ...) -> FrameOrSeries: ...
+    def head(self: NDFrameT, n: int = ...) -> NDFrameT: ...
+    def tail(self: NDFrameT, n: int = ...) -> NDFrameT: ...
     def pipe(
         self, func: Callable[..., T] | tuple[Callable[..., T], str], *args, **kwargs
     ) -> T: ...
@@ -369,22 +370,22 @@ class NDFrame(PandasObject, indexing.IndexingMixin):
     @property
     def dtypes(self): ...
     def astype(
-        self: FrameOrSeries,
+        self: NDFrameT,
         dtype,
         copy: _bool = ...,
         errors: IgnoreRaise = ...,
-    ) -> FrameOrSeries: ...
-    def copy(self: FrameOrSeries, deep: _bool = ...) -> FrameOrSeries: ...
+    ) -> NDFrameT: ...
+    def copy(self: NDFrameT, deep: _bool = ...) -> NDFrameT: ...
     def __copy__(self, deep: _bool = ...) -> NDFrame: ...
     def __deepcopy__(self, memo=...) -> NDFrame: ...
     def infer_objects(self) -> NDFrame: ...
     def convert_dtypes(
-        self: FrameOrSeries,
+        self: NDFrameT,
         infer_objects: _bool = ...,
         convert_string: _bool = ...,
         convert_integer: _bool = ...,
         convert_boolean: _bool = ...,
-    ) -> FrameOrSeries: ...
+    ) -> NDFrameT: ...
     def fillna(
         self,
         value=...,

pandas-stubs/core/groupby/generic.pyi

@@ -17,6 +17,7 @@ from matplotlib.axes import (
 )
 import numpy as np
 from pandas.core.frame import DataFrame
+from pandas.core.generic import NDFrame
 from pandas.core.groupby.groupby import (  # , get_groupby as get_groupby
     GroupBy as GroupBy,
 )
@@ -28,7 +29,6 @@ from pandas._typing import (
     AggFuncType,
     AggFuncTypeBase,
     AxisType,
-    FrameOrSeries,
     Level,
     ListLike,
     Scalar,
@@ -41,7 +41,7 @@ class NamedAgg(NamedTuple):
     column: str = ...
     aggfunc: AggScalar = ...
 
-def generate_property(name: str, klass: type[FrameOrSeries]): ...
+def generate_property(name: str, klass: type[NDFrame]): ...
 
 class _SeriesGroupByScalar(SeriesGroupBy[S1]):
     def __iter__(self) -> Iterator[tuple[Scalar, Series]]: ...

pandas-stubs/core/groupby/groupby.pyi

@@ -12,7 +12,6 @@ from pandas.core.series import Series
 
 from pandas._typing import (
     AxisType,
-    FrameOrSeriesUnion,
     KeysArgType,
     NDFrameT,
 )
@@ -63,24 +62,24 @@ class BaseGroupBy(PandasObject, SelectionMixin[NDFrameT]):
     def get_group(self, name, obj: DataFrame | None = ...) -> DataFrame: ...
 
 class GroupBy(BaseGroupBy[NDFrameT]):
-    def count(self) -> FrameOrSeriesUnion: ...
-    def mean(self, **kwargs) -> FrameOrSeriesUnion: ...
-    def median(self, **kwargs) -> FrameOrSeriesUnion: ...
-    def std(self, ddof: int = ...) -> FrameOrSeriesUnion: ...
-    def var(self, ddof: int = ...) -> FrameOrSeriesUnion: ...
-    def sem(self, ddof: int = ...) -> FrameOrSeriesUnion: ...
+    def count(self) -> DataFrame | Series: ...
+    def mean(self, **kwargs) -> DataFrame | Series: ...
+    def median(self, **kwargs) -> DataFrame | Series: ...
+    def std(self, ddof: int = ...) -> DataFrame | Series: ...
+    def var(self, ddof: int = ...) -> DataFrame | Series: ...
+    def sem(self, ddof: int = ...) -> DataFrame | Series: ...
     def ohlc(self) -> DataFrame: ...
-    def describe(self, **kwargs) -> FrameOrSeriesUnion: ...
+    def describe(self, **kwargs) -> DataFrame | Series: ...
     def resample(self, rule, *args, **kwargs): ...
     def rolling(self, *args, **kwargs): ...
     def expanding(self, *args, **kwargs): ...
     def pad(self, limit: int | None = ...): ...
-    def ffill(self, limit: int | None = ...) -> FrameOrSeriesUnion: ...
-    def backfill(self, limit: int | None = ...) -> FrameOrSeriesUnion: ...
-    def bfill(self, limit: int | None = ...) -> FrameOrSeriesUnion: ...
+    def ffill(self, limit: int | None = ...) -> DataFrame | Series: ...
+    def backfill(self, limit: int | None = ...) -> DataFrame | Series: ...
+    def bfill(self, limit: int | None = ...) -> DataFrame | Series: ...
     def nth(
         self, n: int | list[int], dropna: str | None = ...
-    ) -> FrameOrSeriesUnion: ...
+    ) -> DataFrame | Series: ...
     def quantile(self, q=..., interpolation: str = ...): ...
     def ngroup(self, ascending: bool = ...) -> Series: ...
     def cumcount(self, ascending: bool = ...) -> Series: ...
@@ -92,10 +91,10 @@ class GroupBy(BaseGroupBy[NDFrameT]):
         pct: bool = ...,
         axis: int = ...,
     ) -> DataFrame: ...
-    def cummax(self, axis: AxisType = ..., **kwargs) -> FrameOrSeriesUnion: ...
-    def cummin(self, axis: AxisType = ..., **kwargs) -> FrameOrSeriesUnion: ...
-    def cumprod(self, axis: AxisType = ..., **kwargs) -> FrameOrSeriesUnion: ...
-    def cumsum(self, axis: AxisType = ..., **kwargs) -> FrameOrSeriesUnion: ...
+    def cummax(self, axis: AxisType = ..., **kwargs) -> DataFrame | Series: ...
+    def cummin(self, axis: AxisType = ..., **kwargs) -> DataFrame | Series: ...
+    def cumprod(self, axis: AxisType = ..., **kwargs) -> DataFrame | Series: ...
+    def cumsum(self, axis: AxisType = ..., **kwargs) -> DataFrame | Series: ...
     def shift(
         self, periods: int = ..., freq=..., axis: AxisType = ..., fill_value=...
     ): ...
@@ -106,14 +105,14 @@ class GroupBy(BaseGroupBy[NDFrameT]):
         limit=...,
         freq=...,
         axis: AxisType = ...,
-    ) -> FrameOrSeriesUnion: ...
-    def head(self, n: int = ...) -> FrameOrSeriesUnion: ...
-    def tail(self, n: int = ...) -> FrameOrSeriesUnion: ...
+    ) -> DataFrame | Series: ...
+    def head(self, n: int = ...) -> DataFrame | Series: ...
+    def tail(self, n: int = ...) -> DataFrame | Series: ...
     # Surplus methodss from original pylance stubs; should they go away?
-    def first(self, **kwargs) -> FrameOrSeriesUnion: ...
-    def last(self, **kwargs) -> FrameOrSeriesUnion: ...
-    def max(self, **kwargs) -> FrameOrSeriesUnion: ...
-    def min(self, **kwargs) -> FrameOrSeriesUnion: ...
+    def first(self, **kwargs) -> DataFrame | Series: ...
+    def last(self, **kwargs) -> DataFrame | Series: ...
+    def max(self, **kwargs) -> DataFrame | Series: ...
+    def min(self, **kwargs) -> DataFrame | Series: ...
     def size(self) -> Series[int]: ...
 
 def get_groupby(

pandas-stubs/core/groupby/grouper.pyi

@@ -1,13 +1,14 @@
 from typing import Hashable
 
 import numpy as np
+from pandas import (
+    DataFrame,
+    Index,
+    Series,
+)
 from pandas.core.groupby.ops import BaseGrouper
-from pandas.core.indexes.api import Index
 
-from pandas._typing import (
-    FrameOrSeries,
-    FrameOrSeriesUnion,
-)
+from pandas._typing import NDFrameT
 
 class Grouper:
     def __new__(cls, *args, **kwargs): ...
@@ -42,7 +43,7 @@ class Grouping:
         self,
         index: Index,
         grouper=...,
-        obj: FrameOrSeriesUnion | None = ...,
+        obj: DataFrame | Series | None = ...,
         name=...,
         level=...,
         sort: bool = ...,
@@ -61,12 +62,12 @@ class Grouping:
     def groups(self) -> dict[Hashable, np.ndarray]: ...
 
 def get_grouper(
-    obj: FrameOrSeries,
+    obj: NDFrameT,
     key=...,
     axis: int = ...,
     level=...,
     sort: bool = ...,
     observed: bool = ...,
     mutated: bool = ...,
     validate: bool = ...,
-) -> tuple[BaseGrouper, list[Hashable], FrameOrSeries]: ...
+) -> tuple[BaseGrouper, list[Hashable], NDFrameT]: ...

pandas-stubs/core/groupby/ops.pyi

@@ -1,11 +1,12 @@
 from typing import Sequence
 
 import numpy as np
+from pandas import (
+    DataFrame,
+    Index,
+    Series,
+)
 from pandas.core.groupby import grouper
-from pandas.core.indexes.api import Index
-from pandas.core.series import Series
-
-from pandas._typing import FrameOrSeriesUnion
 
 class BaseGrouper:
     axis = ...
@@ -29,8 +30,8 @@ class BaseGrouper:
     def __iter__(self): ...
     @property
     def nkeys(self) -> int: ...
-    def get_iterator(self, data: FrameOrSeriesUnion, axis: int = ...): ...
-    def apply(self, f, data: FrameOrSeriesUnion, axis: int = ...): ...
+    def get_iterator(self, data: DataFrame | Series, axis: int = ...): ...
+    def apply(self, f, data: DataFrame | Series, axis: int = ...): ...
     def indices(self): ...
     @property
     def codes(self) -> list[np.ndarray]: ...
@@ -66,7 +67,7 @@ class BinGrouper(BaseGrouper):
     def groups(self): ...
     @property
     def nkeys(self) -> int: ...
-    def get_iterator(self, data: FrameOrSeriesUnion, axis: int = ...): ...
+    def get_iterator(self, data: DataFrame | Series, axis: int = ...): ...
     def indices(self): ...
     def group_info(self): ...
     def reconstructed_codes(self) -> list[np.ndarray]: ...
@@ -85,12 +86,12 @@ class DataSplitter:
     ngroups = ...
     axis = ...
     def __init__(
-        self, data: FrameOrSeriesUnion, labels, ngroups: int, axis: int = ...
+        self, data: DataFrame | Series, labels, ngroups: int, axis: int = ...
     ) -> None: ...
     def slabels(self): ...
     def __iter__(self): ...
 
 class SeriesSplitter(DataSplitter): ...
 class FrameSplitter(DataSplitter): ...
 
-def get_splitter(data: FrameOrSeriesUnion, *args, **kwargs) -> DataSplitter: ...
+def get_splitter(data: DataFrame | Series, *args, **kwargs) -> DataSplitter: ...

pandas-stubs/core/window/expanding.pyi

@@ -3,15 +3,17 @@ from typing import (
     Callable,
 )
 
+from pandas import (
+    DataFrame,
+    Series,
+)
 from pandas.core.window.rolling import _Rolling_and_Expanding
 
-from pandas._typing import FrameOrSeriesUnion as FrameOrSeries
-
 class Expanding(_Rolling_and_Expanding):
     def __init__(
         self, obj, min_periods: int = ..., center: bool = ..., axis: int = ..., **kwargs
     ) -> None: ...
-    def count(self, **kwargs) -> FrameOrSeries: ...
+    def count(self, **kwargs) -> DataFrame | Series: ...
     def apply(
         self,
         func: Callable[..., Any],