diff --git a/python/xgboost.py b/python/xgboost.py
index 922ca085d..d37566065 100644
--- a/python/xgboost.py
+++ b/python/xgboost.py
@@ -22,6 +22,13 @@ xglib.XGDMatrixGetLabel.restype =  ctypes.POINTER( ctypes.c_float )
 xglib.XGDMatrixGetRow.restype = ctypes.POINTER( REntry )
 xglib.XGBoosterPredict.restype = ctypes.POINTER( ctypes.c_float ) 
 
+def ctypes2numpy( cptr, length ):
+    # convert a ctypes pointer array to numpy
+    assert isinstance( cptr, ctypes.POINTER( ctypes.c_float ) )
+    res = numpy.zeros( length, dtype='float32' )
+    assert ctypes.memmove( res.ctypes.data, cptr, length * res.strides[0] )
+    return res
+
 # data matrix used in xgboost
 class DMatrix:
     # constructor
@@ -73,7 +80,7 @@ class DMatrix:
     def get_label(self):
         length = ctypes.c_ulong()
         labels = xglib.XGDMatrixGetLabel(self.handle, ctypes.byref(length))
-        return numpy.array( [labels[i] for i in xrange(length.value)] )
+        return ctypes2numpy( labels, length.value );
     # clear everything
     def clear(self):
         xglib.XGDMatrixClear(self.handle)
@@ -138,7 +145,7 @@ class Booster:
     def predict(self, data, bst_group = -1):
         length = ctypes.c_ulong()
         preds = xglib.XGBoosterPredict( self.handle, data.handle, ctypes.byref(length), bst_group)
-        return numpy.array( [ preds[i] for i in xrange(length.value)])
+        return ctypes2numpy( preds, length.value )
     def save_model(self, fname):
         """ save model to file """
         xglib.XGBoosterSaveModel( self.handle, ctypes.c_char_p(fname) )