TYP: make numpy.typing available from pandas._typing (#41945)

pandas/_typing.py

@@ -42,6 +42,8 @@
         final,
     )
 
+    import numpy.typing as npt
+
     from pandas._libs import (
         Period,
         Timedelta,
@@ -73,6 +75,7 @@
     from pandas.io.formats.format import EngFormatter
     from pandas.tseries.offsets import DateOffset
 else:
+    npt: Any = None
     # typing.final does not exist until py38
     final = lambda x: x
     # typing.TypedDict does not exist until py38

pandas/core/frame.py

@@ -63,13 +63,13 @@
     IndexKeyFunc,
     IndexLabel,
     Level,
-    NpDtype,
     PythonFuncType,
     Renamer,
     Scalar,
     StorageOptions,
     Suffixes,
     ValueKeyFunc,
+    npt,
 )
 from pandas.compat._optional import import_optional_dependency
 from pandas.compat.numpy import function as nv
@@ -1593,7 +1593,7 @@ def from_dict(
 
     def to_numpy(
         self,
-        dtype: NpDtype | None = None,
+        dtype: npt.DTypeLike | None = None,
         copy: bool = False,
         na_value=lib.no_default,
     ) -> np.ndarray:

pandas/core/generic.py

@@ -46,7 +46,6 @@
     JSONSerializable,
     Level,
     Manager,
-    NpDtype,
     RandomState,
     Renamer,
     StorageOptions,
@@ -55,6 +54,7 @@
     TimestampConvertibleTypes,
     ValueKeyFunc,
     final,
+    npt,
 )
 from pandas.compat._optional import import_optional_dependency
 from pandas.compat.numpy import function as nv
@@ -1988,7 +1988,7 @@ def empty(self) -> bool_t:
     # GH#23114 Ensure ndarray.__op__(DataFrame) returns NotImplemented
     __array_priority__ = 1000
 
-    def __array__(self, dtype: NpDtype | None = None) -> np.ndarray:
+    def __array__(self, dtype: npt.DTypeLike | None = None) -> np.ndarray:
         return np.asarray(self._values, dtype=dtype)
 
     def __array_wrap__(

pandas/core/internals/managers.py

@@ -22,9 +22,9 @@
 from pandas._libs.internals import BlockPlacement
 from pandas._typing import (
     ArrayLike,
-    Dtype,
     DtypeObj,
     Shape,
+    npt,
     type_t,
 )
 from pandas.errors import PerformanceWarning
@@ -1389,7 +1389,7 @@ def to_dict(self, copy: bool = True):
     def as_array(
         self,
         transpose: bool = False,
-        dtype: Dtype | None = None,
+        dtype: npt.DTypeLike | None = None,
         copy: bool = False,
         na_value=lib.no_default,
     ) -> np.ndarray:
@@ -1429,17 +1429,21 @@ def as_array(
                 # error: Item "ndarray" of "Union[ndarray, ExtensionArray]" has no
                 # attribute "to_numpy"
                 arr = blk.values.to_numpy(  # type: ignore[union-attr]
-                    dtype=dtype, na_value=na_value
+                    # pandas/core/internals/managers.py:1428: error: Argument "dtype" to
+                    # "to_numpy" of "ExtensionArray" has incompatible type
+                    # "Optional[Union[dtype[Any], None, type, _SupportsDType, str,
+                    # Union[Tuple[Any, int], Tuple[Any, Union[SupportsIndex,
+                    # Sequence[SupportsIndex]]], List[Any], _DTypeDict, Tuple[Any,
+                    # Any]]]]"; expected "Optional[Union[ExtensionDtype, Union[str,
+                    # dtype[Any]], Type[str], Type[float], Type[int], Type[complex],
+                    # Type[bool], Type[object]]]"
+                    dtype=dtype,  # type: ignore[arg-type]
+                    na_value=na_value,
                 ).reshape(blk.shape)
             else:
                 arr = np.asarray(blk.get_values())
                 if dtype:
-                    # error: Argument 1 to "astype" of "_ArrayOrScalarCommon" has
-                    # incompatible type "Union[ExtensionDtype, str, dtype[Any],
-                    # Type[object]]"; expected "Union[dtype[Any], None, type,
-                    # _SupportsDType, str, Union[Tuple[Any, int], Tuple[Any, Union[int,
-                    # Sequence[int]]], List[Any], _DTypeDict, Tuple[Any, Any]]]"
-                    arr = arr.astype(dtype, copy=False)  # type: ignore[arg-type]
+                    arr = arr.astype(dtype, copy=False)
         else:
             arr = self._interleave(dtype=dtype, na_value=na_value)
             # The underlying data was copied within _interleave
@@ -1454,7 +1458,9 @@ def as_array(
         return arr.transpose() if transpose else arr
 
     def _interleave(
-        self, dtype: Dtype | None = None, na_value=lib.no_default
+        self,
+        dtype: npt.DTypeLike | ExtensionDtype | None = None,
+        na_value=lib.no_default,
     ) -> np.ndarray:
         """
         Return ndarray from blocks with specified item order
@@ -1489,7 +1495,16 @@ def _interleave(
                 # error: Item "ndarray" of "Union[ndarray, ExtensionArray]" has no
                 # attribute "to_numpy"
                 arr = blk.values.to_numpy(  # type: ignore[union-attr]
-                    dtype=dtype, na_value=na_value
+                    # pandas/core/internals/managers.py:1485: error: Argument "dtype" to
+                    # "to_numpy" of "ExtensionArray" has incompatible type
+                    # "Union[dtype[Any], None, type, _SupportsDType, str, Tuple[Any,
+                    # Union[SupportsIndex, Sequence[SupportsIndex]]], List[Any],
+                    # _DTypeDict, Tuple[Any, Any], ExtensionDtype]"; expected
+                    # "Optional[Union[ExtensionDtype, Union[str, dtype[Any]], Type[str],
+                    # Type[float], Type[int], Type[complex], Type[bool], Type[object]]]"
+                    # [arg-type]
+                    dtype=dtype,  # type: ignore[arg-type]
+                    na_value=na_value,
                 )
             else:
                 # error: Argument 1 to "get_values" of "Block" has incompatible type

pandas/core/series.py

@@ -41,10 +41,10 @@
     FillnaOptions,
     FrameOrSeriesUnion,
     IndexKeyFunc,
-    NpDtype,
     SingleManager,
     StorageOptions,
     ValueKeyFunc,
+    npt,
 )
 from pandas.compat.numpy import function as nv
 from pandas.errors import InvalidIndexError
@@ -808,7 +808,7 @@ def view(self, dtype: Dtype | None = None) -> Series:
     # NDArray Compat
     _HANDLED_TYPES = (Index, ExtensionArray, np.ndarray)
 
-    def __array__(self, dtype: NpDtype | None = None) -> np.ndarray:
+    def __array__(self, dtype: npt.DTypeLike | None = None) -> np.ndarray:
         """
         Return the values as a NumPy array.