TYP: pandas/core/arrays/sparse/dtype.py

pandas/core/arrays/sparse/dtype.py

@@ -1,7 +1,7 @@
 """Sparse Dtype"""
 
 import re
-from typing import Any, Tuple
+from typing import TYPE_CHECKING, Any, Tuple, Type
 
 import numpy as np
 
@@ -19,6 +19,9 @@
 from pandas.core.dtypes.dtypes import register_extension_dtype
 from pandas.core.dtypes.missing import isna, na_value_for_dtype
 
+if TYPE_CHECKING:
+    from pandas.core.arrays.sparse.array import SparseArray  # noqa: F401
+
 
 @register_extension_dtype
 class SparseDtype(ExtensionDtype):
@@ -137,11 +140,11 @@ def _is_na_fill_value(self):
         return isna(self.fill_value)
 
     @property
-    def _is_numeric(self):
+    def _is_numeric(self) -> bool:
         return not is_object_dtype(self.subtype)
 
     @property
-    def _is_boolean(self):
+    def _is_boolean(self) -> bool:
         return is_bool_dtype(self.subtype)
 
     @property
@@ -167,20 +170,20 @@ def __repr__(self) -> str:
         return self.name
 
     @classmethod
-    def construct_array_type(cls):
+    def construct_array_type(cls) -> Type["SparseArray"]:
         """
         Return the array type associated with this dtype.
 
         Returns
         -------
         type
         """
-        from pandas.core.arrays.sparse.array import SparseArray
+        from pandas.core.arrays.sparse.array import SparseArray  # noqa: F811
 
         return SparseArray
 
     @classmethod
-    def construct_from_string(cls, string):
+    def construct_from_string(cls, string: str) -> "SparseDtype":
         """
         Construct a SparseDtype from a string form.
 
@@ -266,7 +269,7 @@ def _parse_subtype(dtype: str) -> Tuple[str, bool]:
         return subtype, has_fill_value
 
     @classmethod
-    def is_dtype(cls, dtype):
+    def is_dtype(cls, dtype: object) -> bool:
         dtype = getattr(dtype, "dtype", dtype)
         if isinstance(dtype, str) and dtype.startswith("Sparse"):
             sub_type, _ = cls._parse_subtype(dtype)