From f3102bbb0e2328b7afd84749ad64a8b833b1b336 Mon Sep 17 00:00:00 2001
From: jbrockmendel <jbrockmendel@gmail.com>
Date: Wed, 29 Jan 2020 11:16:41 -0800
Subject: [PATCH] ENH: implement pd._typing.DtypeObj

---
 pandas/_typing.py             |  1 +
 pandas/core/dtypes/common.py  | 10 +++++-----
 pandas/core/dtypes/missing.py |  4 +++-
 3 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/pandas/_typing.py b/pandas/_typing.py
index 445eff9e19e47..ef1045a93b325 100644
--- a/pandas/_typing.py
+++ b/pandas/_typing.py
@@ -29,6 +29,7 @@
 ArrayLike = TypeVar("ArrayLike", "ExtensionArray", np.ndarray)
 DatetimeLikeScalar = TypeVar("DatetimeLikeScalar", "Period", "Timestamp", "Timedelta")
 Dtype = Union[str, np.dtype, "ExtensionDtype"]
+DtypeObj = Union[np.dtype, "ExtensionDtype"]
 FilePathOrBuffer = Union[str, Path, IO[AnyStr]]
 
 FrameOrSeries = TypeVar("FrameOrSeries", bound="NDFrame")
diff --git a/pandas/core/dtypes/common.py b/pandas/core/dtypes/common.py
index 3f4ebc88c1c8a..52e1aa27bb25f 100644
--- a/pandas/core/dtypes/common.py
+++ b/pandas/core/dtypes/common.py
@@ -48,7 +48,7 @@
     is_string_like,
 )
 
-from pandas._typing import ArrayLike
+from pandas._typing import ArrayLike, DtypeObj
 
 _POSSIBLY_CAST_DTYPES = {
     np.dtype(t).name
@@ -1834,7 +1834,7 @@ 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.
@@ -2004,7 +2004,7 @@ def _validate_date_like_dtype(dtype) -> None:
         raise ValueError(msg.format(name=dtype.name, type=dtype.type.__name__))
 
 
-def pandas_dtype(dtype):
+def pandas_dtype(dtype) -> DtypeObj:
     """
     Convert input into a pandas only dtype object or a numpy dtype object.
 
@@ -2037,7 +2037,7 @@ def pandas_dtype(dtype):
         npdtype = np.dtype(dtype)
     except SyntaxError:
         # np.dtype uses `eval` which can raise SyntaxError
-        raise TypeError("data type '{}' not understood".format(dtype))
+        raise TypeError("data type '{dtype}' not understood".format(dtype=dtype))
 
     # Any invalid dtype (such as pd.Timestamp) should raise an error.
     # np.dtype(invalid_type).kind = 0 for such objects. However, this will
@@ -2049,6 +2049,6 @@ def pandas_dtype(dtype):
         # here and `dtype` is an array
         return npdtype
     elif npdtype.kind == "O":
-        raise TypeError("dtype '{}' not understood".format(dtype))
+        raise TypeError("dtype '{dtype}' not understood".format(dtype=dtype))
 
     return npdtype
diff --git a/pandas/core/dtypes/missing.py b/pandas/core/dtypes/missing.py
index 322011eb8e263..b8eee5bb7fae3 100644
--- a/pandas/core/dtypes/missing.py
+++ b/pandas/core/dtypes/missing.py
@@ -9,6 +9,8 @@
 import pandas._libs.missing as libmissing
 from pandas._libs.tslibs import NaT, iNaT
 
+from pandas._typing import DtypeObj
+
 from .common import (
     _NS_DTYPE,
     _TD_DTYPE,
@@ -572,7 +574,7 @@ def remove_na_arraylike(arr):
         return arr[notna(lib.values_from_object(arr))]
 
 
-def is_valid_nat_for_dtype(obj, dtype):
+def is_valid_nat_for_dtype(obj, dtype: DtypeObj) -> bool:
     """
     isna check that excludes incompatible dtypes