[python][RDF] Add support for std::string in AsRVec

Author: siliataider

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

@@ -77,7 +77,7 @@
 def _get_cpp_type_from_numpy_type(dtype):
     cpptypes = {"i2": "Short_t", "u2": "UShort_t", "i4": "int", "u4": "unsigned int", "i8": "Long64_t", "u8": "ULong64_t", "f4": "float", "f8": "double", "b1": "bool"}
 
-    if not dtype in cpptypes:
+    if dtype not in cpptypes:
         raise RuntimeError("Object not convertible: Python object has unknown data-type '" + dtype + "'.")
 
     return cpptypes[dtype]
@@ -93,10 +93,11 @@ 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.
     """
     import ROOT
     import math
-    import platform
+    import numpy as np
 
     # Get array interface of object
     interface = arr.__array_interface__
@@ -110,17 +111,28 @@ def _AsRVec(arr):
 
     # Get the typestring and properties thereof
     typestr = interface["typestr"]
+    dtype = typestr[1:]
+
+    # Construct an RVec of strings
+    if dtype == "O" or dtype.startswith("U"):
+        underlying_object_types = {type(elem) for elem in arr}
+        if len(underlying_object_types) > 1:
+            raise TypeError("All elements in the numpy array must be of the same type. Found types: {}".format(underlying_object_types))
+
+        if underlying_object_types and underlying_object_types.pop() in [str, np.str_]:
+            return ROOT.VecOps.RVec["std::string"](arr)
+        else:
+            raise TypeError("Cannot create an RVec from a numpy array of data type object.")
+
     if len(typestr) != 3:
         raise RuntimeError(
             "Object not convertible: __array_interface__['typestr'] returned '"
             + typestr
             + "' with invalid length unequal 3."
         )
-
-    dtype = typestr[1:]
-    cppdtype = _get_cpp_type_from_numpy_type(dtype)
-
+        
     # Construct an RVec of the correct data-type
+    cppdtype = _get_cpp_type_from_numpy_type(dtype)
     out = ROOT.VecOps.RVec[cppdtype](ROOT.module.cppyy.ll.reinterpret_cast[f"{cppdtype} *"](data), size)
 
     # Bind pyobject holding adopted memory to the RVec