diff --git a/src/fast_array_utils/stats/_mean_var.py b/src/fast_array_utils/stats/_mean_var.py
index c704bc9..2b8d507 100644
--- a/src/fast_array_utils/stats/_mean_var.py
+++ b/src/fast_array_utils/stats/_mean_var.py
@@ -72,10 +72,10 @@ def _sparse_mean_var(mtx: types.CSBase, /, *, axis: Literal[0, 1]) -> tuple[NDAr
     elif mtx.format == "csc":
         ax_minor = 0
         shape = mtx.shape[::-1]
-    else:
+    else:  # pragma: no cover
         msg = "This function only works on sparse csr and csc matrices"
         raise TypeError(msg)
-    if len(shape) == 1:
+    if len(shape) == 1:  # pragma: no cover
         msg = "array must have 2 dimensions"
         raise TypeError(msg)
     f = sparse_mean_var_major_axis if axis == ax_minor else sparse_mean_var_minor_axis
diff --git a/src/fast_array_utils/types.py b/src/fast_array_utils/types.py
index 6042540..38df35b 100644
--- a/src/fast_array_utils/types.py
+++ b/src/fast_array_utils/types.py
@@ -8,7 +8,9 @@
 
 
 if TYPE_CHECKING:
-    from types import ModuleType
+    from typing import Self
+
+    from array_api.latest import ArrayNamespace
 
 
 __all__ = [
@@ -139,5 +141,5 @@ def shape(self) -> tuple[int, ...]:
     def dtype(self) -> object:
         """The data type of the array."""
 
-    def __array_namespace__(self, /, *, api_version: str | None = None) -> ModuleType:
+    def __array_namespace__(self, /, *, api_version: str | None = None) -> ArrayNamespace[Self, object, object]:  # type: ignore[type-var]
         """Get Array API namespace."""
diff --git a/tests/test_stats.py b/tests/test_stats.py
index 993020a..0860334 100644
--- a/tests/test_stats.py
+++ b/tests/test_stats.py
@@ -396,12 +396,16 @@ def test_stats_benchmark(
     n_elems, density = 10_000_000, 0.01
     n = int(np.sqrt(n_elems / density if "sparse" in array_type.mod else n_elems))
     arr = array_type.random((n, n), density=density, dtype=dtype)
+    if (
+        func is stats.is_constant
+        and isinstance(arr, types.CSBase)
+        and ((array_type.name == "csr_array" and axis == 1) or (array_type.name == "csc_array" and axis == 0))
+    ):
+        # random rows break at the first entry, so make every row constant (explicit zeros) to scan all entries
+        arr.data[:] = 0
 
     func(arr, axis=axis)  # warmup: numba compile
 
-    is_very_fast = func is stats.is_constant and ((array_type.name == "csr_array" and axis == 1) or (array_type.name == "csc_array" and axis == 0))
-
     @benchmark
     def call() -> None:
-        for _ in range(100 if is_very_fast else 1):
-            func(arr, axis=axis)
+        func(arr, axis=axis)