code: def _create_extractors(cls, metrics):
          
          metrics_dict = {}
          # group entries by `category` attribute (default is "standard")
          for metric, config in six.iteritems(metrics):
              category = config.get('category', StdBenchmark.DEFAULT_CATEGORY)
              metrics_dict.setdefault(category, {})[metric] = config
          # create one StdExtractor instance per category,
          # passing associated metrics
          return dict(
              (category, StdExtractor(metrics))
              for category, metrics in six.iteritems(metrics_dict)
          )
docs: Build metrics extractors according to the `metrics` config
  
          :param metrics: Benchmark `metrics` configuration section