TYP: add Shape alias to pandas._typing

pandas/_typing.py

@@ -15,6 +15,7 @@
     Mapping,
     Optional,
     Sequence,
+    Tuple,
     Type,
     TypeVar,
     Union,
@@ -93,6 +94,7 @@
 Label = Optional[Hashable]
 IndexLabel = Union[Label, Sequence[Label]]
 Level = Union[Label, int]
+Shape = Tuple[int, ...]
 Ordered = Optional[bool]
 JSONSerializable = Optional[Union[PythonScalar, List, Dict]]
 Axes = Collection

pandas/core/arrays/_mixins.py

@@ -1,8 +1,9 @@
-from typing import Any, Sequence, Tuple, TypeVar
+from typing import Any, Sequence, TypeVar
 
 import numpy as np
 
 from pandas._libs import lib
+from pandas._typing import Shape
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly, doc
@@ -93,7 +94,7 @@ def _validate_fill_value(self, fill_value):
     # TODO: make this a cache_readonly; for that to work we need to remove
     #  the _index_data kludge in libreduction
     @property
-    def shape(self) -> Tuple[int, ...]:
+    def shape(self) -> Shape:
         return self._ndarray.shape
 
     def __len__(self) -> int:

pandas/core/arrays/base.py

@@ -12,7 +12,7 @@
 import numpy as np
 
 from pandas._libs import lib
-from pandas._typing import ArrayLike
+from pandas._typing import ArrayLike, Shape
 from pandas.compat import set_function_name
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
@@ -403,7 +403,7 @@ def dtype(self) -> ExtensionDtype:
         raise AbstractMethodError(self)
 
     @property
-    def shape(self) -> Tuple[int, ...]:
+    def shape(self) -> Shape:
         """
         Return a tuple of the array dimensions.
         """

pandas/core/dtypes/cast.py

@@ -32,7 +32,7 @@
     ints_to_pytimedelta,
 )
 from pandas._libs.tslibs.timezones import tz_compare
-from pandas._typing import AnyArrayLike, ArrayLike, Dtype, DtypeObj, Scalar
+from pandas._typing import AnyArrayLike, ArrayLike, Dtype, DtypeObj, Scalar, Shape
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.common import (
@@ -1591,7 +1591,7 @@ def find_common_type(types: List[DtypeObj]) -> DtypeObj:
 
 
 def cast_scalar_to_array(
-    shape: Tuple, value: Scalar, dtype: Optional[DtypeObj] = None
+    shape: Shape, value: Scalar, dtype: Optional[DtypeObj] = None
 ) -> np.ndarray:
     """
     Create np.ndarray of specified shape and dtype, filled with values.

pandas/core/groupby/ops.py

@@ -24,7 +24,7 @@
 from pandas._libs import NaT, iNaT, lib
 import pandas._libs.groupby as libgroupby
 import pandas._libs.reduction as libreduction
-from pandas._typing import F, FrameOrSeries, Label
+from pandas._typing import F, FrameOrSeries, Label, Shape
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly
 
@@ -116,7 +116,7 @@ def groupings(self) -> List["grouper.Grouping"]:
         return self._groupings
 
     @property
-    def shape(self) -> Tuple[int, ...]:
+    def shape(self) -> Shape:
         return tuple(ping.ngroups for ping in self.groupings)
 
     def __iter__(self):

pandas/core/indexes/base.py

@@ -27,7 +27,7 @@
 from pandas._libs.lib import is_datetime_array, no_default
 from pandas._libs.tslibs import IncompatibleFrequency, OutOfBoundsDatetime, Timestamp
 from pandas._libs.tslibs.timezones import tz_compare
-from pandas._typing import AnyArrayLike, Dtype, DtypeObj, Label, final
+from pandas._typing import AnyArrayLike, Dtype, DtypeObj, Label, Shape, final
 from pandas.compat.numpy import function as nv
 from pandas.errors import DuplicateLabelError, InvalidIndexError
 from pandas.util._decorators import Appender, cache_readonly, doc
@@ -5644,7 +5644,7 @@ def _maybe_disable_logical_methods(self, opname: str_t):
             make_invalid_op(opname)(self)
 
     @property
-    def shape(self):
+    def shape(self) -> Shape:
         """
         Return a tuple of the shape of the underlying data.
         """

pandas/core/indexes/multi.py

@@ -20,7 +20,7 @@
 
 from pandas._libs import algos as libalgos, index as libindex, lib
 from pandas._libs.hashtable import duplicated_int64
-from pandas._typing import AnyArrayLike, Label, Scalar
+from pandas._typing import AnyArrayLike, Label, Scalar, Shape
 from pandas.compat.numpy import function as nv
 from pandas.errors import InvalidIndexError, PerformanceWarning, UnsortedIndexError
 from pandas.util._decorators import Appender, cache_readonly, doc
@@ -702,7 +702,7 @@ def array(self):
         )
 
     @property
-    def shape(self):
+    def shape(self) -> Shape:
         """
         Return a tuple of the shape of the underlying data.
         """

pandas/core/internals/blocks.py

@@ -10,7 +10,7 @@
 from pandas._libs.internals import BlockPlacement
 from pandas._libs.tslibs import conversion
 from pandas._libs.tslibs.timezones import tz_compare
-from pandas._typing import ArrayLike, Scalar
+from pandas._typing import ArrayLike, Scalar, Shape
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.cast import (
@@ -2762,7 +2762,7 @@ def _block_shape(values: ArrayLike, ndim: int = 1) -> ArrayLike:
     return values
 
 
-def safe_reshape(arr, new_shape):
+def safe_reshape(arr, new_shape: Shape):
     """
     If possible, reshape `arr` to have shape `new_shape`,
     with a couple of exceptions (see gh-13012):

pandas/core/internals/concat.py

@@ -5,7 +5,7 @@
 import numpy as np
 
 from pandas._libs import NaT, internals as libinternals
-from pandas._typing import DtypeObj
+from pandas._typing import DtypeObj, Shape
 from pandas.util._decorators import cache_readonly
 
 from pandas.core.dtypes.cast import maybe_promote
@@ -175,7 +175,7 @@ def _get_mgr_concatenation_plan(mgr, indexers):
 
 
 class JoinUnit:
-    def __init__(self, block, shape, indexers=None):
+    def __init__(self, block, shape: Shape, indexers=None):
         # Passing shape explicitly is required for cases when block is None.
         if indexers is None:
             indexers = {}

pandas/core/internals/managers.py

@@ -17,7 +17,7 @@
 import numpy as np
 
 from pandas._libs import internals as libinternals, lib
-from pandas._typing import ArrayLike, DtypeObj, Label
+from pandas._typing import ArrayLike, DtypeObj, Label, Shape
 from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.dtypes.cast import (
@@ -204,7 +204,7 @@ def __nonzero__(self) -> bool:
     __bool__ = __nonzero__
 
     @property
-    def shape(self) -> Tuple[int, ...]:
+    def shape(self) -> Shape:
         return tuple(len(ax) for ax in self.axes)
 
     @property
@@ -1825,7 +1825,7 @@ def _asarray_compat(x):
         else:
             return np.asarray(x)
 
-    def _shape_compat(x):
+    def _shape_compat(x) -> Shape:
         if isinstance(x, ABCSeries):
             return (len(x),)
         else:

pandas/core/ops/array_ops.py

@@ -5,13 +5,13 @@
 from datetime import timedelta
 from functools import partial
 import operator
-from typing import Any, Tuple
+from typing import Any
 import warnings
 
 import numpy as np
 
 from pandas._libs import Timedelta, Timestamp, lib, ops as libops
-from pandas._typing import ArrayLike
+from pandas._typing import ArrayLike, Shape
 
 from pandas.core.dtypes.cast import (
     construct_1d_object_array_from_listlike,
@@ -427,7 +427,7 @@ def maybe_upcast_datetimelike_array(obj: ArrayLike) -> ArrayLike:
     return obj
 
 
-def _maybe_upcast_for_op(obj, shape: Tuple[int, ...]):
+def _maybe_upcast_for_op(obj, shape: Shape):
     """
     Cast non-pandas objects to pandas types to unify behavior of arithmetic
     and comparison operations.

pandas/io/pytables.py

@@ -28,7 +28,7 @@
 
 from pandas._libs import lib, writers as libwriters
 from pandas._libs.tslibs import timezones
-from pandas._typing import ArrayLike, FrameOrSeries, FrameOrSeriesUnion, Label
+from pandas._typing import ArrayLike, FrameOrSeries, FrameOrSeriesUnion, Label, Shape
 from pandas.compat._optional import import_optional_dependency
 from pandas.compat.pickle_compat import patch_pickle
 from pandas.errors import PerformanceWarning
@@ -3091,7 +3091,7 @@ class BlockManagerFixed(GenericFixed):
     nblocks: int
 
     @property
-    def shape(self):
+    def shape(self) -> Optional[Shape]:
         try:
             ndim = self.ndim