ENH: implement pd._typing.DtypeObj (#31426)

Author: jbrockmendel

pandas/_typing.py

@@ -45,6 +45,7 @@
 # other
 
 Dtype = Union[str, np.dtype, "ExtensionDtype"]
+DtypeObj = Union[np.dtype, "ExtensionDtype"]
 FilePathOrBuffer = Union[str, Path, IO[AnyStr]]
 
 # FrameOrSeriesUnion  means either a DataFrame or a Series. E.g.

pandas/core/dtypes/common.py

@@ -6,7 +6,7 @@
 
 from pandas._libs import algos, lib
 from pandas._libs.tslibs import conversion
-from pandas._typing import ArrayLike
+from pandas._typing import ArrayLike, DtypeObj
 
 from pandas.core.dtypes.dtypes import (
     CategoricalDtype,
@@ -1668,7 +1668,7 @@ def _is_dtype(arr_or_dtype, condition) -> bool:
     return condition(dtype)
 
 
-def _get_dtype(arr_or_dtype):
+def _get_dtype(arr_or_dtype) -> DtypeObj:
     """
     Get the dtype instance associated with an array
     or dtype object.
@@ -1840,7 +1840,7 @@ def _validate_date_like_dtype(dtype) -> None:
         )
 
 
-def pandas_dtype(dtype):
+def pandas_dtype(dtype) -> DtypeObj:
     """
     Convert input into a pandas only dtype object or a numpy dtype object.
 

pandas/core/dtypes/missing.py

@@ -8,6 +8,7 @@
 from pandas._libs import lib
 import pandas._libs.missing as libmissing
 from pandas._libs.tslibs import NaT, iNaT
+from pandas._typing import DtypeObj
 
 from pandas.core.dtypes.common import (
     _NS_DTYPE,
@@ -585,7 +586,7 @@ def remove_na_arraylike(arr):
         return arr[notna(lib.values_from_object(arr))]
 
 
-def is_valid_nat_for_dtype(obj, dtype) -> bool:
+def is_valid_nat_for_dtype(obj, dtype: DtypeObj) -> bool:
     """
     isna check that excludes incompatible dtypes