Adding classifiers to metrics and updating csv and telemetry to take advantage of them

- Adding "classifiers" field to Metric objects. This is a dict mapping
  classifier names (arbitrary strings) to corresponding values for that
  specific metrics. This is to allow extensions to add
  extension-specific annotations to metric that could be handled in a
  generic way (e.g. by result processors).
- Updating telemetry workload to add classifiers for the url and internal
  iteration (or "time") for a particular result.
- Updating csv result processor with the option to use classifiers to
  add columns to results.csv (either using all classifiers found, or
  only for the specific ones listed).

wlauto/core/execution.py

@@ -192,6 +192,9 @@ class ExecutionContext(object):
         self.current_job = None
         self.output_directory = self.run_output_directory
 
+    def add_metric(self, *args, **kwargs):
+        self.result.add_metric(*args, **kwargs)
+
     def add_artifact(self, name, path, kind, *args, **kwargs):
         if self.current_job is None:
             self.add_run_artifact(name, path, kind, *args, **kwargs)