Refactor TraceData to encapsulate internal traces' representation

telemetry/telemetry/web_perf/timeline_based_measurement.py

 # Copyright 2014 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 import collections
 import logging
 from collections import defaultdict
 
 from tracing.metrics import metric_runner
 
 from telemetry.timeline import chrome_trace_category_filter
 from telemetry.timeline import model as model_module
 from telemetry.timeline import tracing_config
-from telemetry.timeline import trace_data as trace_data_module
 from telemetry.value import trace
 from telemetry.value import common_value_helpers
 from telemetry.web_perf.metrics import timeline_based_metric
 from telemetry.web_perf.metrics import blob_timeline
 from telemetry.web_perf.metrics import jitter_timeline
 from telemetry.web_perf.metrics import webrtc_rendering_timeline
 from telemetry.web_perf.metrics import gpu_timeline
 from telemetry.web_perf.metrics import indexeddb_timeline
 from telemetry.web_perf.metrics import layout
 from telemetry.web_perf.metrics import smoothness
@@ skipping 261 matching lines @@
       chrome_config.category_filter.AddIncludedCategory('blink.console')
     platform.tracing_controller.StartTracing(self._tbm_options.config)
 
   def Measure(self, platform, results):
     """Collect all possible metrics and added them to results."""
     platform.tracing_controller.telemetry_info = results.telemetry_info
     trace_result = platform.tracing_controller.StopTracing()
     trace_value = trace.TraceValue(results.current_page, trace_result)
     results.AddValue(trace_value)
 
-    if self._tbm_options.GetTimelineBasedMetrics():
-      self._ComputeTimelineBasedMetrics(results, trace_value)
-      # Legacy metrics can be computed, but only if explicitly specified.
-      if self._tbm_options.GetLegacyTimelineBasedMetrics():
-        # Since this imports the trace model in python, it will also clean up
-        # the trace handles for us.
+    try:
+      if self._tbm_options.GetTimelineBasedMetrics():
+        self._ComputeTimelineBasedMetrics(results, trace_value)
+        # Legacy metrics can be computed, but only if explicitly specified.
+        if self._tbm_options.GetLegacyTimelineBasedMetrics():
+          self._ComputeLegacyTimelineBasedMetrics(results, trace_result)
+      else:
+        # Run all TBMv1 metrics if no other metric is specified
+        # (legacy behavior)
+        if not self._tbm_options.GetLegacyTimelineBasedMetrics():
+          logging.warn('Please specify the TBMv1 metrics you are interested in '
+                       'explicitly. This implicit functionality will be removed'
+                       ' on July 17, 2016.')
+          self._tbm_options.SetLegacyTimelineBasedMetrics(
+              _GetAllLegacyTimelineBasedMetrics())
         self._ComputeLegacyTimelineBasedMetrics(results, trace_result)
-      else:
-        # Clean up the trace handles ourselves if we did not use the python
-        # trace importer.
-        for data in trace_result.GetTracesFor(
-            trace_data_module.CHROME_TRACE_PART):
-          if isinstance(data, trace_data_module.TraceFileHandle):
-            data.Clean()
-    else:
-      # Run all TBMv1 metrics if no other metric is specified (legacy behavior)
-      if not self._tbm_options.GetLegacyTimelineBasedMetrics():
-        logging.warn('Please specify the TBMv1 metrics you are interested in '
-                     'explicitly. This implicit functionality will be removed '
-                     'on July 17, 2016.')
-        self._tbm_options.SetLegacyTimelineBasedMetrics(
-            _GetAllLegacyTimelineBasedMetrics())
-      self._ComputeLegacyTimelineBasedMetrics(results, trace_result)
+    finally:
+      trace_result.CleanUpAllTraces()
 
   def DidRunStory(self, platform):
     """Clean up after running the story."""
     if platform.tracing_controller.is_tracing_running:
       platform.tracing_controller.StopTracing()
 
   def _ComputeTimelineBasedMetrics(self, results, trace_value):
     metrics = self._tbm_options.GetTimelineBasedMetrics()
     extra_import_options = {
       'trackDetailedModelStats': True
@@ skipping 28 matching lines @@
 
     for renderer_thread, interaction_records in (
         threads_to_records_map.iteritems()):
       meta_metrics = _TimelineBasedMetrics(
           model, renderer_thread, interaction_records, self._results_wrapper,
           all_metrics)
       meta_metrics.AddResults(results)
 
     for metric in all_metrics:
       metric.AddWholeTraceResults(model, results)