code: def default_dist_funcs(dist_funcs, feature_example):
          
  
          if dist_funcs is None:
              dist_funcs = dict()
  
          for key in feature_example:
              if key in dist_funcs:
                  pass
              if key == 'item':
                  pass
              elif isinstance(feature_example[key], (six.string_types, six.binary_type)):
                  dist_funcs[key] = 'match'
              elif isinstance(feature_example[key], (int, np.integer, float)) or all([isinstance(i, (int, np.integer, float)) for i in feature_example[key]]):
                  dist_funcs[key] = 'euclidean'
  
          return dist_funcs
docs: Fills in default distance metrics for fingerprint analyses