fix numpy typing import

Author: Joseph Hamman

requirements.txt

@@ -1 +1,2 @@
 xarray>=0.16
+numpy>=1.20

setup.cfg

@@ -21,3 +21,6 @@ skip=
 [tool:pytest]
 log_cli = True
 log_level = INFO
+
+[mypy]
+plugins = numpy.typing.mypy_plugin

xarray_schema/base.py

@@ -1,10 +1,6 @@
 import json
 from abc import abstractmethod
-from typing import Any, Dict, Hashable, Tuple, Union
-
-DimsT = Tuple[Union[Hashable, None]]
-ShapeT = Tuple[Union[int, None]]
-ChunksT = Union[bool, Dict[Hashable, Union[int, None]]]
+from typing import Any, Dict
 
 
 class SchemaError(Exception):

xarray_schema/components.py

@@ -1,24 +1,23 @@
 from collections.abc import Iterable
-from typing import Any, Dict, Hashable, Mapping, Optional, Tuple, Union
+from typing import Any, Dict, Hashable, Mapping, Tuple, Union
 
 import numpy as np
-import numpy.typing as npt
 
 from .base import BaseSchema, SchemaError
-from .types import ChunksT, DimsT, ShapeT
+from .types import ChunksT, DimsT, DTypeLike, ShapeT
 
 
 class DTypeSchema(BaseSchema):
 
     _json_schema = {'type': 'string'}
 
-    def __init__(self, dtype: npt.DTypeLike) -> None:
+    def __init__(self, dtype: DTypeLike) -> None:
         if dtype in [np.floating, np.integer, np.signedinteger, np.unsignedinteger, np.generic]:
             self.dtype = dtype
         else:
             self.dtype = np.dtype(dtype)
 
-    def validate(self, dtype: npt.DTypeLike) -> None:
+    def validate(self, dtype: DTypeLike) -> None:
         '''Validate dtype
 
         Parameters
@@ -127,9 +126,7 @@ class ChunksSchema(BaseSchema):
     def __init__(self, chunks: ChunksT) -> None:
         self.chunks = chunks
 
-    def validate(
-        self, chunks: Optional[Tuple[Tuple[int, ...], ...]], dims: tuple, shape: tuple
-    ) -> None:
+    def validate(self, chunks: Tuple[Tuple[int, ...], ...], dims: tuple, shape: tuple) -> None:
         '''Validate chunks
 
         Parameters

xarray_schema/dataarray.py

@@ -1,6 +1,5 @@
 from typing import Any, Callable, Dict, List, Mapping, Union
 
-import numpy as np
 import xarray as xr
 
 from .base import BaseSchema, SchemaError
@@ -13,15 +12,15 @@
     NameSchema,
     ShapeSchema,
 )
-from .types import ChunksT, DimsT, ShapeT
+from .types import ChunksT, DimsT, DTypeLike, ShapeT
 
 
 class DataArraySchema(BaseSchema):
     '''A light-weight xarray.DataArray validator
 
     Parameters
     ----------
-    dtype : np.typing.DTypeLike or DTypeSchema, optional
+    dtype : DTypeLike or DTypeSchema, optional
         Datatype of the the variable. If a string is specified it must be a valid NumPy data type value, by default None
     shape : ShapeT or ShapeSchema, optional
         Shape of the DataArray. `None` may be used as a wildcard value. By default None
@@ -51,7 +50,7 @@ class DataArraySchema(BaseSchema):
 
     def __init__(
         self,
-        dtype: Union[np.typing.DTypeLike, DTypeSchema] = None,
+        dtype: Union[DTypeLike, DTypeSchema] = None,
         shape: Union[ShapeT, ShapeSchema] = None,
         dims: Union[DimsT, DimsSchema] = None,
         name: Union[str, NameSchema] = None,
@@ -77,7 +76,7 @@ def dtype(self) -> Union[DTypeSchema, None]:
         return self._dtype
 
     @dtype.setter
-    def dtype(self, value: Union[DTypeSchema, np.typing.DTypeLike, None]):
+    def dtype(self, value: Union[DTypeSchema, DTypeLike, None]):
         if value is None or isinstance(value, DTypeSchema):
             self._dtype = value
         else:

xarray_schema/types.py

@@ -1,5 +1,8 @@
 from typing import Dict, Tuple, Union
 
+import numpy as np
+
+DTypeLike = np.typing.DTypeLike
 DimsT = Tuple[Union[str, None]]
 ShapeT = Tuple[Union[int, None]]
 ChunksT = Union[bool, Dict[str, Union[int, None]]]