From 3304ab3d8802b22746587c78e2abf1bb05a91ea3 Mon Sep 17 00:00:00 2001
From: sneakers-the-rat <sneakers-the-rat@protonmail.com>
Date: Tue, 13 Aug 2024 23:05:28 -0700
Subject: [PATCH] update changelog, bump version

---
 src/numpydantic/ndarray.py                  |  6 +++++-
 src/numpydantic/vendor/nptyping/__init__.py |  4 +++-
 src/numpydantic/vendor/nptyping/ndarray.py  |  2 --
 tests/test_ndarray.py                       | 14 ++++++++++++++
 4 files changed, 22 insertions(+), 4 deletions(-)

diff --git a/src/numpydantic/ndarray.py b/src/numpydantic/ndarray.py
index 8756ae0..d951d3a 100644
--- a/src/numpydantic/ndarray.py
+++ b/src/numpydantic/ndarray.py
@@ -29,7 +29,7 @@ from numpydantic.schema import (
     get_validate_interface,
     make_json_schema,
 )
-from numpydantic.types import DtypeType, ShapeType
+from numpydantic.types import DtypeType, NDArrayType, ShapeType
 from numpydantic.vendor.nptyping.error import InvalidArgumentsError
 from numpydantic.vendor.nptyping.ndarray import NDArrayMeta as _NDArrayMeta
 from numpydantic.vendor.nptyping.nptyping_type import NPTypingType
@@ -54,6 +54,10 @@ class NDArrayMeta(_NDArrayMeta, implementation="NDArray"):
     if TYPE_CHECKING:  # pragma: no cover
         __getitem__ = SubscriptableMeta.__getitem__
 
+    def __call__(cls, val: NDArrayType) -> NDArrayType:
+        """Call ndarray as a validator function"""
+        return get_validate_interface(cls.__args__[0], cls.__args__[1])(val)
+
     def __instancecheck__(self, instance: Any):
         """
         Extended type checking that determines whether
diff --git a/src/numpydantic/vendor/nptyping/__init__.py b/src/numpydantic/vendor/nptyping/__init__.py
index 4ca8fdb..0a51854 100644
--- a/src/numpydantic/vendor/nptyping/__init__.py
+++ b/src/numpydantic/vendor/nptyping/__init__.py
@@ -32,7 +32,9 @@ from numpydantic.vendor.nptyping.error import (
 )
 from numpydantic.vendor.nptyping.ndarray import NDArray
 from numpydantic.vendor.nptyping.package_info import __version__
-from numpydantic.vendor.nptyping.pandas_.dataframe import DataFrame
+
+# don't import unnecessarily since we don't use it
+# from numpydantic.vendor.nptyping.pandas_.dataframe import DataFrame
 from numpydantic.vendor.nptyping.recarray import RecArray
 from numpydantic.vendor.nptyping.shape import Shape
 from numpydantic.vendor.nptyping.shape_expression import (
diff --git a/src/numpydantic/vendor/nptyping/ndarray.py b/src/numpydantic/vendor/nptyping/ndarray.py
index 90a4793..19f06b4 100644
--- a/src/numpydantic/vendor/nptyping/ndarray.py
+++ b/src/numpydantic/vendor/nptyping/ndarray.py
@@ -31,7 +31,6 @@ import numpy as np
 from numpydantic.vendor.nptyping.base_meta_classes import (
     FinalMeta,
     ImmutableMeta,
-    InconstructableMeta,
     MaybeCheckableMeta,
     PrintableMeta,
     SubscriptableMeta,
@@ -54,7 +53,6 @@ from numpydantic.vendor.nptyping.typing_ import (
 
 class NDArrayMeta(
     SubscriptableMeta,
-    InconstructableMeta,
     ImmutableMeta,
     FinalMeta,
     MaybeCheckableMeta,
diff --git a/tests/test_ndarray.py b/tests/test_ndarray.py
index 9883c2a..f92a66d 100644
--- a/tests/test_ndarray.py
+++ b/tests/test_ndarray.py
@@ -350,3 +350,17 @@ def test_instancecheck():
         return array
 
     my_function(np.zeros((1, 2, 3), int))
+
+
+def test_callable():
+    """
+    NDArray objects are callable to validate and cast
+    Don't test validation here, just that we can be called
+    """
+    annotation = NDArray[Shape["3"], int]
+    array = np.array([1, 2, 3], dtype=int)
+    validated = annotation(array)
+    assert validated is array
+
+    with pytest.raises(DtypeError):
+        _ = annotation(np.zeros((1, 2, 3)))