diff --git a/test/hl/test_datatype.py b/test/hl/test_datatype.py
index 751d9a5..00c0c50 100644
--- a/test/hl/test_datatype.py
+++ b/test/hl/test_datatype.py
@@ -12,7 +12,7 @@
 
 import numpy as np
 import math
-
+import logging
 import config
 
 if config.get("use_h5py"):
@@ -23,39 +23,11 @@
 from common import ut, TestCase
 
 
-def read_dtypes(dataset_dtype, names):
-    """ Returns a 2-tuple containing:
-
-    1. Output dataset dtype
-    2. Dtype containing HDF5-appropriate description of destination
-    """
-
-    if len(names) == 0:     # Not compound, or all fields needed
-        format_dtype = dataset_dtype
-
-    elif dataset_dtype.names is None:
-        raise ValueError("Field names only allowed for compound types")
-
-    elif any(x not in dataset_dtype.names for x in names):
-        raise ValueError("Field does not appear in this type.")
-
-    else:
-        format_dtype = np.dtype([(name, dataset_dtype.fields[name][0]) for name in names])
-
-    if len(names) == 1:
-        # We don't preserve the field information if only one explicitly selected.
-        output_dtype = format_dtype.fields[names[0]][0]
-
-    else:
-        output_dtype = format_dtype
-
-    return output_dtype, format_dtype
-
-
 class TestScalarCompound(TestCase):
 
     def setUp(self):
         filename = self.getFileName("scalar_compound_dset")
+        print("filename:", filename)
         self.f = h5py.File(filename, "w")
         self.data = np.array((42.5, -118, "Hello"), dtype=[('a', 'f'), ('b', 'i'), ('c', '|S10')])
         self.dset = self.f.create_dataset('x', data=self.data)
@@ -180,4 +152,6 @@ def test_nested_compound_vlen(self):
 
 
 if __name__ == '__main__':
+    loglevel = logging.ERROR
+    logging.basicConfig(format='%(asctime)s %(message)s', level=loglevel)
     ut.main()