fix(numpy): Fix direct numpy array deserialization

* The existing numpy deserialization handles the case where a numpy
  array is a member of a dataclass, but not where the numpy array is
  deserialized directy.

Author: kmsquire

serde/compat.py

@@ -15,16 +15,26 @@
 try:
     import numpy.typing as npt
 
+    # Note: these functions are only needed on Python 3.8 or earlier
     def get_np_origin(tp):
         if isinstance(tp, npt._generic_alias._GenericAlias) and tp.__origin__ is not ClassVar:
             return tp.__origin__
         return None
 
+    def get_np_args(tp):
+        if isinstance(tp, npt._generic_alias._GenericAlias) and tp.__origin__ is not ClassVar:
+            return tp.__args__
+
+        return ()
+
 except ImportError:
 
     def get_np_origin(tp):
         return None
 
+    def get_np_args(tp):
+        return ()
+
 
 __all__: List = []
 
@@ -58,9 +68,9 @@ def get_args(typ):
     Provide `get_args` that works in all python versions.
     """
     try:
-        return typing.get_args(typ)  # python>=3.8 typing module has get_args.
+        return typing.get_args(typ) or get_np_args(typ)  # python>=3.8 typing module has get_args.
     except AttributeError:
-        return typing_inspect.get_args(typ)
+        return typing_inspect.get_args(typ) or get_np_args(typ)
 
 
 def typename(typ) -> str:

serde/de.py

@@ -57,7 +57,13 @@
     raise_unsupported_type,
     union_func_name,
 )
-from .numpy import deserialize_numpy_array, deserialize_numpy_scalar, is_numpy_array, is_numpy_scalar
+from .numpy import (
+    deserialize_numpy_array,
+    deserialize_numpy_array_direct,
+    deserialize_numpy_scalar,
+    is_numpy_array,
+    is_numpy_scalar,
+)
 
 __all__: List = ['deserialize', 'is_deserializable', 'from_dict', 'from_tuple']
 
@@ -343,6 +349,8 @@ def from_obj(c: Type, o: Any, named: bool, reuse_instances: bool):
                 return {k: v for k, v in o.items()}
             else:
                 return {thisfunc(type_args(c)[0], k): thisfunc(type_args(c)[1], v) for k, v in o.items()}
+        elif is_numpy_array(c):
+            return deserialize_numpy_array_direct(c, o)
         elif c in DateTimeTypes:
             return c.fromisoformat(o)
         elif c is Any:

serde/numpy.py

@@ -1,6 +1,6 @@
 from typing import Any, Callable, Optional
 
-from serde.compat import get_origin
+from serde.compat import get_args, get_origin
 
 
 def fullname(klass):
@@ -66,6 +66,13 @@ def deserialize_numpy_array(arg) -> str:
         dtype = fullname(arg[1][0].type)
         return f"numpy.array({arg.data}, dtype={dtype})"
 
+    def deserialize_numpy_array_direct(typ, arg):
+        if is_bare_numpy_array(typ):
+            return np.array(arg)
+
+        dtype = get_args(get_args(typ)[1])[0]
+        return np.array(arg, dtype=dtype)
+
 except ImportError:
     encode_numpy = None
 
@@ -86,3 +93,6 @@ def serialize_numpy_array(arg) -> str:
 
     def deserialize_numpy_array(arg) -> str:
         return ""
+
+    def deserialize_numpy_array_direct(typ, arg):
+        return arg

tests/test_numpy.py

@@ -140,6 +140,33 @@ class MisTyped:
 
     assert de(MisTyped, se(test2)) == expected
 
+    for value in [np.int32(1), np.int64(1), np.bool_(False), np.bool_(True), int(1), False, True]:
+        typ = type(value)
+        de_value = de(typ, se(value))
+        assert de_value == value
+        assert type(de_value) == typ
+
+        # test bare numpy array deserialization
+        arr = np.array([0, 1, 2], dtype=typ)
+        de_arr = de(np.ndarray, se(arr))
+        assert (de_arr == arr).all()
+
+        # test arrays with dtype=type(value)
+        arr_typ = npt.NDArray[typ]
+
+        de_arr = de(arr_typ, se(arr))
+        assert (de_arr == arr).all()
+        assert de_arr.dtype == arr.dtype == typ
+
+    class BadClass:
+        def __init__(self, x):
+            self.x = x
+
+    b = BadClass(1)
+
+    with pytest.raises(TypeError):
+        se(b)
+
 
 @pytest.mark.parametrize("se,de", format_json + format_msgpack)
 def test_encode_numpy_with_no_default_encoder(se, de):