Optimize for numpy builtin types (#209)

Author: ZwFink

charm4py/charm.py

@@ -381,7 +381,10 @@ def packMsg(self, destObj, msgArgs, header):
                         # memoryview, Python throws error: "memoryview: underlying buffer is not
                         # C-contiguous", which seems to be a CPython error (not cffi related)
                         nbytes = arg.nbytes
-                        direct_copy_hdr.append((i, 2, (arg.shape, arg.dtype.name), nbytes))
+                        if arg.dtype.isbuiltin:
+                            direct_copy_hdr.append((i, 2, (arg.shape, arg.dtype.char), nbytes))
+                        else:
+                            direct_copy_hdr.append((i, 2, (arg.shape, arg.dtype.name), nbytes))
                     else:
                         continue
                     args[i] = None  # will direct-copy this arg so remove from args list

charm4py/charmlib/charmlib_cython.pyx

@@ -791,7 +791,10 @@ class CharmLib(object):
         if isinstance(arg, np.ndarray) and not arg.dtype.hasobject:
           np_array = arg
           nbytes = np_array.nbytes
-          direct_copy_hdr.append((i, 2, (arg.shape, np_array.dtype.name), nbytes))
+          if arg.dtype.isbuiltin:
+            direct_copy_hdr.append((i, 2, (arg.shape, arg.dtype.char), nbytes))
+          else:
+            direct_copy_hdr.append((i, 2, (arg.shape, arg.dtype.name), nbytes))
           send_bufs[cur_buf] = <char*>np_array.data
         elif isinstance(arg, bytes):
           nbytes = len(arg)