[6.38] [Python] Add missing numpy int8/uint8 support in AsRVec

bindings/pyroot/pythonizations/python/ROOT/_pythonization/_rvec.py

@@ -134,6 +134,8 @@
 
 def _get_cpp_type_from_numpy_type(dtype):
     cpptypes = {
+        "i1": "signed char",
+        "u1": "unsigned char",
         "i2": "Short_t",
         "u2": "UShort_t",
         "i4": "int",
@@ -161,7 +163,8 @@ def _AsRVec(arr):
     This function returns an RVec which adopts the memory of the given
     PyObject. The RVec takes the data pointer and the size from the array
     interface dictionary.
-    Note that for arrays of strings, the input strings are copied into the RVec.
+    Note that for arrays of strings and int8, the input data is copied into the RVec
+    rather than adopted.
     """
     import math
 
@@ -183,7 +186,7 @@ def _AsRVec(arr):
     typestr = interface["typestr"]
     dtype = typestr[1:]
 
-    # Construct an RVec of strings
+    # Construct an RVec of strings by copying the input array
     if dtype == "O" or dtype.startswith("U"):
         underlying_object_types = {type(elem) for elem in arr}
         if len(underlying_object_types) > 1:
@@ -198,6 +201,11 @@ def _AsRVec(arr):
         else:
             raise TypeError("Cannot create an RVec from a numpy array of data type object.")
 
+    # Construct an RVec of int8 by copying the input array
+    # RVec<signed char> does not expose the ptr+size contructor
+    if dtype == "i1":
+        return ROOT.VecOps.RVec["signed char"](arr)
+
     if len(typestr) != 3:
         raise RuntimeError(
             "Object not convertible: __array_interface__['typestr'] returned '"

bindings/pyroot/pythonizations/test/rvec_asrvec.py

@@ -27,13 +27,20 @@ class AsRVec(unittest.TestCase):
     """
 
     # Helpers
-    dtypes = ["int16", "int32", "int64", "uint16", "uint32", "uint64", "float32", "float64", "bool"]
+    dtypes = ["int8", "uint8", "int16", "int32", "int64", "uint16", "uint32", "uint64", "float32", "float64", "bool"]
 
-    def check_memory_adoption(self, root_obj, np_obj):
-        np_obj[0] = get_maximum_for_dtype(np_obj.dtype)
-        np_obj[1] = get_minimum_for_dtype(np_obj.dtype)
-        self.assertEqual(root_obj[0], np_obj[0])
-        self.assertEqual(root_obj[1], np_obj[1])
+    def check_memory_adoption(self, root_obj, np_obj, copy=False):
+        if not copy:
+            np_obj[0] = get_maximum_for_dtype(np_obj.dtype)
+            np_obj[1] = get_minimum_for_dtype(np_obj.dtype)
+        for i in range(2):
+            root_val = root_obj[i]
+            # RVec<unsigned char> elements are returned as Python strings (e.g. '\x7f' instead of 127),
+            # we need to convert them back to integers for comparison
+            if isinstance(root_val, str):
+                root_val = ord(root_val)
+
+            self.assertEqual(root_val, np_obj[i])
 
     def check_size(self, expected_size, obj):
         self.assertEqual(expected_size, obj.size())
@@ -44,9 +51,15 @@ def test_dtypes(self):
         Test adoption of numpy arrays with different data types
         """
         for dtype in self.dtypes:
-            np_obj = np.empty(2, dtype=dtype)
-            root_obj = ROOT.VecOps.AsRVec(np_obj)
-            self.check_memory_adoption(root_obj, np_obj)
+            if dtype == "int8":
+                # For int8 we use explicit small values to avoid platform-dependent signed char representation issues
+                np_obj = np.array([42, 35], dtype="int8")
+                root_obj = ROOT.VecOps.AsRVec(np_obj)
+                self.check_memory_adoption(root_obj, np_obj, copy=True)
+            else:
+                np_obj = np.empty(2, dtype=dtype)
+                root_obj = ROOT.VecOps.AsRVec(np_obj)
+                self.check_memory_adoption(root_obj, np_obj)
             self.check_size(2, root_obj)
 
     def test_object_dtype_strings(self):