[Findit] For automatic analyses of flaky tests, run the Swarming tasks off PST peak hours.

appengine/findit/waterfall/flake/initialize_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 google.appengine.ext import ndb
 
 from common import appengine_util
 from common import constants
 from model import analysis_status
 from model.flake.master_flake_analysis import MasterFlakeAnalysis
@@ skipping 37 matching lines @@
     master_flake_analysis = MasterFlakeAnalysis.Create(
         master_name, builder_name, build_number, step_name, test_name)
     master_flake_analysis.status = analysis_status.PENDING
     master_flake_analysis.put()
     return True
 
 
 # Unused arguments - pylint: disable=W0612, W0613
 def ScheduleAnalysisIfNeeded(master_name, builder_name, build_number, step_name,
                              test_name, allow_new_analysis=False, force=False,
+                             manually_triggered=False,
                              queue_name=constants.DEFAULT_QUEUE):
   """Schedules an analysis if needed and returns the MasterFlakeAnalysis.
 
   When the build failure was already analyzed and a new analysis is scheduled,
   the returned WfAnalysis will still have the result of last completed analysis.
 
   Args:
     master_name (str): The master name of the failed test
     builder_name (str): The builder name of the failed test
     build_number (int): The build number of the failed test
     step_name (str): The name of the test suite
     test_name (str): The single test we are checking
     allow_new_analysis (bool): Indicate whether a new analysis is allowed.
     force (bool): Indicate whether to force a rerun of current analysis.
+    manually_triggered (bool): True if the analysis is from manual request, like
+        by a Chromium sheriff.
     queue_name (str): The App Engine queue to run the analysis.
 
   Returns:
     A MasterFlakeAnalysis instance.
     None if no analysis was scheduled and the user has no permission to.
   """
   if NeedANewAnalysis(
       master_name, builder_name, build_number, step_name, test_name,
       allow_new_analysis):
     check_flake_settings = waterfall_config.GetCheckFlakeSettings()
     max_build_numbers_to_look_back = check_flake_settings.get(
         'max_build_numbers_to_look_back')
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 0,
         'stable_in_a_row': 0,
         'stabled_out': False,
         'flaked_out': False,
         'last_build_number': max(
             0, build_number - max_build_numbers_to_look_back),
         'lower_boundary': None,
         'upper_boundary': None,
         'lower_boundary_result': None,
         'sequential_run_index': 0
     }
     pipeline_job = RecursiveFlakePipeline(
         master_name, builder_name, build_number, step_name, test_name,
         master_build_number=build_number,
-        flakiness_algorithm_results_dict=flakiness_algorithm_results_dict)
+        flakiness_algorithm_results_dict=flakiness_algorithm_results_dict,
+        manually_triggered=manually_triggered)
     pipeline_job.target = appengine_util.GetTargetNameForModule(
         constants.WATERFALL_BACKEND)
     pipeline_job.start(queue_name=queue_name)
   return MasterFlakeAnalysis.Get(
       master_name, builder_name, build_number, step_name, test_name)