diff --git a/benchmarks/dgemm_compare.py b/benchmarks/dgemm_compare.py
index e325e57c..5606157f 100644
--- a/benchmarks/dgemm_compare.py
+++ b/benchmarks/dgemm_compare.py
@@ -61,9 +61,9 @@
             b_new = b
             c_new = c
 
-        view_a = pk.array(a_new)
-        view_b = pk.array(b_new)
-        view_c = pk.array(c_new)
+        view_a = pk.asarray(a_new)
+        view_b = pk.asarray(b_new)
+        view_c = pk.asarray(c_new)
 
         pk_dgemm_time_sec = timeit.timeit(
             "pk_dgemm(alpha, view_a, view_b, beta, view_c)",
diff --git a/examples/NaiveBayes/GaussianNB.py b/examples/NaiveBayes/GaussianNB.py
index 8c334f57..06348bd6 100644
--- a/examples/NaiveBayes/GaussianNB.py
+++ b/examples/NaiveBayes/GaussianNB.py
@@ -357,8 +357,8 @@ class labels known to the classifier.
     Examples
     --------
     >>> import numpy as np
-    >>> X = pk.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
-    >>> Y = pk.array([1, 1, 1, 2, 2, 2])
+    >>> X = pk.asarray([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3, 2]])
+    >>> Y = pk.asarray([1, 1, 1, 2, 2, 2])
     >>> from sklearn.naive_bayes import GaussianNB
     >>> clf = GaussianNB()
     >>> clf.fit(X, Y)
diff --git a/examples/kokkos/inclusive_scan_team_cuda.py b/examples/kokkos/inclusive_scan_team_cuda.py
index d0f86a7f..a7333fb5 100644
--- a/examples/kokkos/inclusive_scan_team_cuda.py
+++ b/examples/kokkos/inclusive_scan_team_cuda.py
@@ -34,7 +34,7 @@ def main():
     num_teams = (N + team_size - 1) // team_size
 
     view = cp.zeros(N, dtype=cp.int32)
-    view_pk = pk.array(view)
+    view_pk = pk._array(view)
     p_init = pk.RangePolicy(pk.ExecutionSpace.Cuda, 0, N)
     pk.parallel_for(p_init, init_data, view=view_pk)
 
diff --git a/examples/pykokkos/from_array.py b/examples/pykokkos/from_array.py
index ad5d53fb..b9174616 100644
--- a/examples/pykokkos/from_array.py
+++ b/examples/pykokkos/from_array.py
@@ -27,9 +27,9 @@ def addition_cp(i: int, cp_arr):
 print(f"before {cp_arr=}")
 print(f"before {list_arr=}")
 
-np_view = pk.array(np_arr)
-cp_view = pk.array(cp_arr)
-list_view = pk.array(list_arr)
+np_view = pk.asarray(np_arr)
+cp_view = pk._array(cp_arr)
+list_view = pk.asarray(list_arr)
 
 pk.parallel_for(pk.RangePolicy(pk.OpenMP, 0, size), addition_np, np_arr=np_view)
 pk.parallel_for(pk.RangePolicy(pk.Cuda, 0, size), addition_cp, cp_arr=cp_view)
diff --git a/examples/pykokkos/multi_gpu.py b/examples/pykokkos/multi_gpu.py
index 4f7ddc01..61298b75 100644
--- a/examples/pykokkos/multi_gpu.py
+++ b/examples/pykokkos/multi_gpu.py
@@ -23,14 +23,14 @@ def reduction_cp(i: int, acc: pk.Acc[int], cp_arr):
 
 
 pk.set_device_id(1)
-cp_view_0 = pk.array(cp_arr_1)
+cp_view_0 = pk._array(cp_arr_1)
 result_0 = pk.parallel_reduce(
     pk.RangePolicy(pk.Cuda, 0, size), reduction_cp, cp_arr=cp_view_0
 )
 print(result_0)
 
 pk.set_device_id(0)
-cp_view_1 = pk.array(cp_arr_0)
+cp_view_1 = pk._array(cp_arr_0)
 result_1 = pk.parallel_reduce(
     pk.RangePolicy(pk.Cuda, 0, size), reduction_cp, cp_arr=cp_view_1
 )
diff --git a/pykokkos/__init__.py b/pykokkos/__init__.py
index 9340945f..972a0126 100644
--- a/pykokkos/__init__.py
+++ b/pykokkos/__init__.py
@@ -4,6 +4,7 @@
 from pykokkos.runtime import runtime_singleton
 from pykokkos.core import Runtime
 from pykokkos.interface import *
+from pykokkos.interface.views import _array
 from pykokkos.kokkos_manager import (
     initialize,
     finalize,
diff --git a/pykokkos/interface/__init__.py b/pykokkos/interface/__init__.py
index a14c2ffa..2e26edcf 100644
--- a/pykokkos/interface/__init__.py
+++ b/pykokkos/interface/__init__.py
@@ -98,6 +98,8 @@
     ScratchView6D,
     ScratchView7D,
     ScratchView8D,
+    _array,
+    # Transitional export: deprecated, use pk.asarray for user conversions.
     array,
     asarray,
     result_type,
diff --git a/pykokkos/interface/views.py b/pykokkos/interface/views.py
index 62ed04b4..cf1886b2 100644
--- a/pykokkos/interface/views.py
+++ b/pykokkos/interface/views.py
@@ -5,6 +5,7 @@
 from enum import Enum
 import os
 import sys
+import warnings
 from types import ModuleType
 from typing import Dict, Generic, Iterator, List, Optional, Tuple, TypeVar, Union
 
@@ -945,7 +946,7 @@ def is_array(array) -> bool:
     return True
 
 
-def array(
+def _array(
     array, space: Optional[MemorySpace] = None, layout: Optional[Layout] = None
 ) -> ViewType:
     """
@@ -958,8 +959,11 @@ def array(
     """
 
     # if numpy array, use from_numpy()
-    if isinstance(array, np.ndarray) or np.isscalar(array):
+    if isinstance(array, np.ndarray):
         return from_numpy(array, space, layout)
+    # Python scalars do not expose .dtype, so normalize first
+    if np.isscalar(array):
+        return from_numpy(np.asarray(array), space, layout)
     # test if the input array can duck-type to a numpy-like array
     # and run from_array to preprocess the array to numpy
     if is_array(array):
@@ -968,6 +972,25 @@ def array(
     return from_numpy(np.asarray(array), space, layout)
 
 
+def array(
+    array, space: Optional[MemorySpace] = None, layout: Optional[Layout] = None
+) -> ViewType:
+    """
+    Deprecated public compatibility shim for internal array conversion.
+
+    Prefer `pk.asarray` for user-level conversions.
+    """
+
+    warnings.warn(
+        "pk.array is deprecated and will be removed in a future release. "
+        "Use pk.asarray for user conversions; pk._array is internal/private.",
+        DeprecationWarning,
+        stacklevel=2,
+    )
+
+    return _array(array, space, layout)
+
+
 # asarray is required for comformance with the array API:
 # https://data-apis.org/array-api/2021.12/API_specification/creation_functions.html#objects-in-api
 
@@ -977,7 +1000,17 @@ def asarray(obj, /, *, dtype=None, device=None, copy=None):
     # for now, let's cheat and use NumPy asarray() followed
     # by pykokkos from_numpy()
 
-    if not isinstance(obj, list) and obj in {pk.e, pk.pi, pk.inf, pk.nan}:
+    is_array_api_constant = False
+    if np.isscalar(obj):
+        if obj in (pk.e, pk.pi, pk.inf):
+            is_array_api_constant = True
+        else:
+            try:
+                is_array_api_constant = bool(np.isnan(obj))
+            except TypeError:
+                is_array_api_constant = False
+
+    if is_array_api_constant:
         if dtype is None:
             dtype = pk.float64
         view = pk.View([1], dtype=dtype)
diff --git a/pykokkos/lib/util.py b/pykokkos/lib/util.py
index 4c959272..7898b432 100644
--- a/pykokkos/lib/util.py
+++ b/pykokkos/lib/util.py
@@ -11,12 +11,12 @@
 
 def all(x, /, *, axis=None, keepdims=False):
     np_result = np.all(x)
-    ret_val = pk.array(np_result)
+    ret_val = pk._array(np_result)
     return ret_val
 
 
 def any(x, /, *, axis=None, keepdims=False):
-    return pk.View(pk.array(np.any(x)))
+    return pk.View(pk._array(np.any(x)))
 
 
 @pk.workunit
diff --git a/tests/test_linalg.py b/tests/test_linalg.py
index 1677bedb..99068a3c 100644
--- a/tests/test_linalg.py
+++ b/tests/test_linalg.py
@@ -182,12 +182,12 @@ def test_dgemm_shape(shape_a, shape_b):
 def test_dgemm_vs_scipy(alpha, a, b, c, beta, expected_c):
     # test against expected results from
     # scipy.linalg.blas.dgemm
-    view_a = pk.array(a)
-    view_b = pk.array(b)
+    view_a = pk.asarray(a)
+    view_b = pk.asarray(b)
     if c is None:
         view_c = None
     else:
-        view_c = pk.array(c)
+        view_c = pk.asarray(c)
     actual_c = dgemm(
         alpha=alpha, view_a=view_a, view_b=view_b, view_c=view_c, beta=beta
     )
@@ -196,7 +196,7 @@ def test_dgemm_vs_scipy(alpha, a, b, c, beta, expected_c):
 
 def test_dgemm_input_handling():
     alpha = 1.0
-    view_a = pk.array(np.zeros((4, 3)))
-    view_b = pk.array([np.array([0, 0, 0], dtype=np.int32)] * 4)
+    view_a = pk.asarray(np.zeros((4, 3)))
+    view_b = pk.asarray([np.array([0, 0, 0], dtype=np.int32)] * 4)
     with pytest.raises(ValueError, match="Second dimensions"):
         dgemm(alpha=alpha, view_a=view_a, view_b=view_b)
diff --git a/tests/test_parallelreduce.py b/tests/test_parallelreduce.py
index 9335ce57..d9da30b1 100644
--- a/tests/test_parallelreduce.py
+++ b/tests/test_parallelreduce.py
@@ -66,7 +66,7 @@ def test_squaresum_types(series_max, dtype):
     np_data = np.arange(series_max, dtype=dtype)
     expected = np.sum(np_data**2)
 
-    view = pk.array(np_data)
+    view = pk.asarray(np_data)
     policy = pk.RangePolicy(pk.ExecutionSpace.OpenMP, 0, series_max)
 
     if dtype == np.float64:
diff --git a/tests/test_ufuncs.py b/tests/test_ufuncs.py
index fd97c5e3..bd0899a2 100644
--- a/tests/test_ufuncs.py
+++ b/tests/test_ufuncs.py
@@ -259,7 +259,7 @@ def test_multi_array_1d_exposed_ufuncs_vs_numpy(
 def test_scalar_operations_vs_numpy(pk_ufunc, numpy_ufunc, numpy_dtype):
     data = [1.0, 2.0, 3.0, 4.0, 5.0, 6.0]
     expected = numpy_ufunc(np.array(data, dtype=numpy_dtype), 1)
-    actual = pk_ufunc(pk.array(np.array(data, dtype=numpy_dtype)), 1)
+    actual = pk_ufunc(pk.asarray(np.array(data, dtype=numpy_dtype)), 1)
     assert_allclose(actual, expected)
 
 
@@ -423,8 +423,8 @@ def test_np_matmul_2d_1d_vs_numpy(pk_ufunc, numpy_ufunc, numpy_dtype, test_dim):
     np2 = rng.random(N2).astype(numpy_dtype)
     expected = numpy_ufunc(np1, np2)
 
-    view1 = pk.array(np1)
-    view2 = pk.array(np2)
+    view1 = pk.asarray(np1)
+    view2 = pk.asarray(np2)
     actual = pk_ufunc(view1, view2)
 
     assert_allclose(actual, expected)
@@ -454,8 +454,8 @@ def test_np_matmul_1d_2d_vs_numpy(pk_ufunc, numpy_ufunc, numpy_dtype, test_dim):
     np2 = rng.random((N2, M2)).astype(numpy_dtype)
     expected = numpy_ufunc(np1, np2)
 
-    view1 = pk.array(np1)
-    view2 = pk.array(np2)
+    view1 = pk.asarray(np1)
+    view2 = pk.asarray(np2)
     actual = pk_ufunc(view1, view2)
 
     assert_allclose(actual, expected)
@@ -495,8 +495,8 @@ def test_np_matmul_fails(numpy_dtype, test_dim):
     np2 = rng.random((N2, M2)).astype(numpy_dtype)
 
     with pytest.raises(RuntimeError) as e_info:
-        view1 = pk.array(np1)
-        view2 = pk.array(np2)
+        view1 = pk.asarray(np1)
+        view2 = pk.asarray(np2)
         pk.np_matmul(view1, view2)  # Should fail with 1d x 2d
 
     err_np_matmul = (
@@ -536,8 +536,8 @@ def test_multi_array_2d_exposed_ufuncs_vs_numpy(pk_ufunc, numpy_ufunc, numpy_dty
     np2 = rng.random((N, M)).astype(numpy_dtype)
     expected = numpy_ufunc(np1, np2)
 
-    view1 = pk.array(np1)
-    view2 = pk.array(np2)
+    view1 = pk.asarray(np1)
+    view2 = pk.asarray(np2)
     actual = pk_ufunc(view1, view2)
 
     assert_allclose(actual, expected)
@@ -592,8 +592,8 @@ def test_broadcast_array_exposed_ufuncs_vs_numpy(
 
     expected = numpy_ufunc(np1, np2)
 
-    view1 = pk.array(np1)
-    view2 = pk.array(np2) if isinstance(np2, np.ndarray) else np2
+    view1 = pk.asarray(np1)
+    view2 = pk.asarray(np2) if isinstance(np2, np.ndarray) else np2
     actual = pk_ufunc(view1, view2)
 
     assert_allclose(expected, actual)
@@ -643,8 +643,8 @@ def test_copyto_1d(pk_ufunc, numpy_ufunc, numpy_dtype):
     np2 = rng.random((N, M)).astype(numpy_dtype)
     numpy_ufunc(np1, np2)
 
-    view1 = pk.array(np1)
-    view2 = pk.array(np2)
+    view1 = pk.asarray(np1)
+    view2 = pk.asarray(np2)
     pk_ufunc(view1, view2)
 
     assert_allclose(np1, view1)
@@ -705,8 +705,8 @@ def test_copyto_broadcast_2d(pk_ufunc, numpy_ufunc, numpy_dtype, test_dim):
 
     numpy_ufunc(np1, np2)
 
-    view1 = pk.array(np1)
-    view2 = pk.array(np2) if isinstance(np2, np.ndarray) else np2
+    view1 = pk.asarray(np1)
+    view2 = pk.asarray(np2) if isinstance(np2, np.ndarray) else np2
     pk_ufunc(view1, view2)
 
     assert_allclose(np1, view1)
diff --git a/tests/test_views.py b/tests/test_views.py
index 86c8d979..93ac65ed 100644
--- a/tests/test_views.py
+++ b/tests/test_views.py
@@ -97,9 +97,9 @@ def __init__(self, threads: int, i_1: int, i_2: int, i_3: int, i_4: int):
         cp_arr = cp.zeros((threads, 2)).astype(np.int32)
         list_arr = [np.array([0, 0], dtype=np.int32)] * threads
 
-        self.np_view: pk.View2D[int] = pk.array(np_arr)
-        self.cp_view: pk.View2D[int] = pk.array(cp_arr)
-        self.list_view: pk.View2D[int] = pk.array(list_arr)
+        self.np_view: pk.View2D[int] = pk.asarray(np_arr)
+        self.cp_view: pk.View2D[int] = pk._array(cp_arr)
+        self.list_view: pk.View2D[int] = pk.asarray(list_arr)
 
     @pk.workunit
     def v1d(self, tid: int) -> None:
@@ -283,9 +283,9 @@ def test_arrays(self):
         cp_arr = cp.zeros((self.threads, 2)).astype(np.int32)
         list_arr = [np.array([0, 0], dtype=np.int32)] * self.threads
 
-        np_view = pk.array(np_arr)
-        cp_view = pk.array(cp_arr)
-        list_view = pk.array(list_arr)
+        np_view = pk.asarray(np_arr)
+        cp_view = pk._array(cp_arr)
+        list_view = pk.asarray(list_arr)
 
         pk.parallel_for(
             pk.RangePolicy(pk.OpenMP, 0, self.threads), addition_np, np_arr=np_view
@@ -376,6 +376,41 @@ def test_asarray_consts_vs_numpy(const, np_dtype, pk_dtype):
     assert not "int" in pk_type_string
 
 
+@pytest.mark.parametrize(
+    "arr",
+    [
+        np.array([1, 2, 3], dtype=np.int32),
+        [1, 2, 3],
+        7,
+    ],
+)
+def test_array_deprecated_alias_still_converts(arr):
+    with pytest.warns(DeprecationWarning, match="pk.array is deprecated"):
+        view = pk.array(arr)
+    assert_allclose(view, np.asarray(arr))
+
+
+@pytest.mark.parametrize(
+    "arr",
+    [
+        np.array([3, 1, 4], dtype=np.int32),
+        [3, 1, 4],
+    ],
+)
+def test_private_array_conversion_matches_asarray(arr):
+    from_private = pk._array(arr)
+    from_public = pk.asarray(arr)
+    assert type(from_private) is type(from_public)
+    assert_allclose(from_private, from_public)
+
+
+@pytest.mark.skipif(not HAS_CUDA, reason="CUDA/cupy not available")
+def test_private_array_conversion_accepts_cupy_array():
+    cp_arr = cp.array([3, 1, 4], dtype=cp.int32)
+    from_private = pk._array(cp_arr)
+    assert_allclose(from_private, cp.asnumpy(cp_arr))
+
+
 @pytest.mark.parametrize(
     "pk_dtype, np_dtype",
     [
@@ -416,7 +451,7 @@ def test_result_type_supported(pk_dtype, pk_dtype2, expected_promo):
 @pytest.mark.parametrize(
     "pk_dtype, pk_dtype2",
     [
-        (pk.array(np.array([0])), pk.uint16),
+        (pk.asarray(np.array([0])), pk.uint16),
         (pk.uint64, pk.int8),
         (pk.float32, pk.int64),
     ],