Handle byte types in reult_type calculation

Author: lshaw8317

examples/ndarray/string_arrays.ipynb

@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -42,7 +42,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -52,7 +52,7 @@
        "      dtype='|S12')"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -83,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -125,21 +125,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 4,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "AttributeError",
-     "evalue": "module 'blosc2' has no attribute 'lower'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
-      "\u001b[31mAttributeError\u001b[39m                            Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[11]\u001b[39m\u001b[32m, line 26\u001b[39m\n\u001b[32m     22\u001b[39m np.testing.assert_array_equal((a1_blosc >= a2_blosc)[:], a1 >= a2)\n\u001b[32m     23\u001b[39m np.testing.assert_array_equal((a1_blosc > a2_blosc)[:], a1 > a2)\n\u001b[32m     25\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m func, npfunc \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(\n\u001b[32m---> \u001b[39m\u001b[32m26\u001b[39m     (\u001b[43mblosc2\u001b[49m\u001b[43m.\u001b[49m\u001b[43mlower\u001b[49m, blosc2.upper), (np.char.lower, np.char.upper), strict=\u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[32m     27\u001b[39m ):\n\u001b[32m     28\u001b[39m     expr_lazy = func(a1_blosc)\n\u001b[32m     29\u001b[39m     res_numexpr = npfunc(a1)\n",
-      "\u001b[31mAttributeError\u001b[39m: module 'blosc2' has no attribute 'lower'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "for t in (\"bytes\", \"string\"):\n",
     "    if t == \"bytes\":\n",

src/blosc2/lazyexpr.py

@@ -2822,7 +2822,7 @@ def result_type(
     # Follow NumPy rules for scalar-array operations
     # Create small arrays with the same dtypes and let NumPy's type promotion determine the result type
     arrs = [
-        (np.array(value).dtype if isinstance(value, str) else value)
+        (np.array(value).dtype if isinstance(value, (str, bytes)) else value)
         if (np.isscalar(value) or not hasattr(value, "dtype"))
         else np.array([0], dtype=_convert_dtype(value.dtype))
         for value in arrays_and_dtypes