Merge pull request #16941 from seberg/types-are-not-arraylikes

BUG: Allow array-like types to be coerced as object array elements

2 files changed, 58 insertions, 2 deletions

diff --git a/numpy/core/src/multiarray/ctors.c b/numpy/core/src/multiarray/ctors.c
index cb448756b..dc451685a 100644
--- a/numpy/core/src/multiarray/ctors.c
+++ b/numpy/core/src/multiarray/ctors.c
@@ -1748,6 +1748,15 @@ PyArray_FromStructInterface(PyObject *input)
         }
     }
     if (!NpyCapsule_Check(attr)) {
+        if (PyType_Check(input) && PyObject_HasAttrString(attr, "__get__")) {
+            /*
+             * If the input is a class `attr` should be a property-like object.
+             * This cannot be interpreted as an array, but is a valid.
+             * (Needed due to the lookup being on the instance rather than type)
+             */
+            Py_DECREF(attr);
+            return Py_NotImplemented;
+        }
         goto fail;
     }
     inter = NpyCapsule_AsVoidPtr(attr);
@@ -1844,8 +1853,8 @@ PyArray_FromInterface(PyObject *origin)
     npy_intp dims[NPY_MAXDIMS], strides[NPY_MAXDIMS];
     int dataflags = NPY_ARRAY_BEHAVED;
 
-    iface = PyArray_LookupSpecial_OnInstance(origin,
-                                                    "__array_interface__");
+    iface = PyArray_LookupSpecial_OnInstance(origin, "__array_interface__");
+
     if (iface == NULL) {
         if (PyErr_Occurred()) {
             PyErr_Clear(); /* TODO[gh-14801]: propagate crashes during attribute access? */
@@ -1853,6 +1862,16 @@ PyArray_FromInterface(PyObject *origin)
         return Py_NotImplemented;
     }
     if (!PyDict_Check(iface)) {
+        if (PyType_Check(origin) && PyObject_HasAttrString(iface, "__get__")) {
+            /*
+             * If the input is a class `iface` should be a property-like object.
+             * This cannot be interpreted as an array, but is a valid.
+             * (Needed due to the lookup being on the instance rather than type)
+             */
+            Py_DECREF(iface);
+            return Py_NotImplemented;
+        }
+
         Py_DECREF(iface);
         PyErr_SetString(PyExc_ValueError,
                 "Invalid __array_interface__ value, must be a dict");
@@ -2119,6 +2138,16 @@ PyArray_FromArrayAttr(PyObject *op, PyArray_Descr *typecode, PyObject *context)
         }
         return Py_NotImplemented;
     }
+    if (PyType_Check(op) && PyObject_HasAttrString(array_meth, "__get__")) {
+        /*
+         * If the input is a class `array_meth` may be a property-like object.
+         * This cannot be interpreted as an array (called), but is a valid.
+         * Trying `array_meth.__call__()` on this should not be useful.
+         * (Needed due to the lookup being on the instance rather than type)
+         */
+        Py_DECREF(array_meth);
+        return Py_NotImplemented;
+    }
     if (typecode == NULL) {
         new = PyObject_CallFunction(array_meth, NULL);
     }
diff --git a/numpy/core/tests/test_array_coercion.py b/numpy/core/tests/test_array_coercion.py
index 07a4c5c22..d18df2e9c 100644
--- a/numpy/core/tests/test_array_coercion.py
+++ b/numpy/core/tests/test_array_coercion.py
@@ -570,3 +570,30 @@ class TestArrayLikes:
         with pytest.raises(ValueError):
             # The error type does not matter much here.
             np.array([obj])
+
+    def test_arraylike_classes(self):
+        # The classes of array-likes should generally be acceptable to be
+        # stored inside a numpy (object) array.  This tests all of the
+        # special attributes (since all are checked during coercion).
+        arr = np.array(np.int64)
+        assert arr[()] is np.int64
+        arr = np.array([np.int64])
+        assert arr[0] is np.int64
+
+        # This also works for properties/unbound methods:
+        class ArrayLike:
+            @property
+            def __array_interface__(self):
+                pass
+
+            @property
+            def __array_struct__(self):
+                pass
+
+            def __array__(self):
+                pass
+
+        arr = np.array(ArrayLike)
+        assert arr[()] is ArrayLike
+        arr = np.array([ArrayLike])
+        assert arr[0] is ArrayLike