[Findit] Post analysis results of flakes to bug filed by chromium-try-flakes.

appengine/findit/waterfall/flake/recursive_flake_pipeline.py

 # Copyright 2016 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.
 
 from datetime import timedelta
 import logging
 import random
+import textwrap
 
 from common import appengine_util
 from common import constants
 from common import time_util
 from common.pipeline_wrapper import BasePipeline
 
 from model import analysis_status
 from model import result_status
 from model.flake.flake_swarming_task import FlakeSwarmingTask
 from model.flake.master_flake_analysis import MasterFlakeAnalysis
 from waterfall import waterfall_config
+from waterfall.post_comment_to_bug_pipeline import PostCommentToBugPipeline
 from waterfall.process_flake_swarming_task_result_pipeline import (
     ProcessFlakeSwarmingTaskResultPipeline)
 from waterfall.trigger_flake_swarming_task_pipeline import (
     TriggerFlakeSwarmingTaskPipeline)
 
 
+def _UpdateBugWithResult(analysis, queue_name):
+  """Updates attached bug for the flakiness trend."""
+  if (not analysis.bug_id or
+      not analysis.algorithm_parameters.get('update_monorail_bug')):
+    return False
+
+  comment = textwrap.dedent("""
+  Findit has generated the flakiness trend for this flake in the config
+  "%s / %s / %s" by rerunning the test on Swarming with build artifacts from
+  Waterfall. Please visit
+    https://findit-for-me.appspot.com/waterfall/check-flake?key=%s\n
+  Automatically posted by the findit-for-me app (https://goo.gl/YTKnaU).
+  Feedback are welcome using component Tools>Test>FindIt>Flakiness !""") % (
+      analysis.original_master_name, analysis.original_builder_name,
+      analysis.original_step_name, analysis.key.urlsafe())
+  labels = ['AnalyzedByFindit']
+  pipeline = PostCommentToBugPipeline(
+      analysis.bug_id, comment, labels)
+  pipeline.target = appengine_util.GetTargetNameForModule(
+      constants.WATERFALL_BACKEND)
+  pipeline.start(queue_name=queue_name)
+  return True
+
+
 def _UpdateAnalysisStatusUponCompletion(master_flake_analysis, status, error):
   master_flake_analysis.end_time = time_util.GetUTCNow()
   master_flake_analysis.status = status
 
   if error:
     master_flake_analysis.error = error
 
   if master_flake_analysis.suspected_flake_build_number is not None:
     master_flake_analysis.result_status = result_status.FOUND_UNTRIAGED
   else:
@@ skipping 243 matching lines @@
           flakiness_algorithm_results_dict=flakiness_algorithm_results_dict,
           manually_triggered=manually_triggered)
       # pylint: disable=W0201
       pipeline_job.target = appengine_util.GetTargetNameForModule(
           constants.WATERFALL_BACKEND)
       pipeline_job.StartOffPSTPeakHours(
           queue_name=self.queue_name or constants.DEFAULT_QUEUE)
     else:
       _UpdateAnalysisStatusUponCompletion(
           master_flake_analysis, analysis_status.COMPLETED, None)
+      _UpdateBugWithResult(
+          master_flake_analysis, self.queue_name or constants.DEFAULT_QUEUE)