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

appengine/findit/handlers/flake/check_flake.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.api import users
 
 from common import constants
 from common.base_handler import BaseHandler
 from common.base_handler import Permission
 from model.analysis_status import STATUS_TO_DESCRIPTION
@@ skipping 10 matching lines @@
     builder_name = self.request.get('builder_name').strip()
     build_number = int(self.request.get('build_number').strip())
     step_name = self.request.get('step_name').strip()
     test_name = self.request.get('test_name').strip()
     force = (users.is_current_user_admin() and
              self.request.get('force') == '1')
     allow_new_analysis = self.IsCorpUserOrAdmin()
 
     master_flake_analysis = ScheduleAnalysisIfNeeded(
         master_name, builder_name, build_number, step_name, test_name,
-        allow_new_analysis, force=force,
+        allow_new_analysis, force=force, manually_triggered=True,
         queue_name=constants.WATERFALL_ANALYSIS_QUEUE)
 
     if not master_flake_analysis:  # pragma: no cover.
       return {
           'template': 'error.html',
           'data': {
               'error_message':
                   ('You could schedule an analysis for flaky test only after '
                    'you login with google.com account.'),
               'login_url': self.GetLoginUrl(),
           },
           'return_code': 401,
       }
 
     data = {
         'pass_rates': [],
         'analysis_status': STATUS_TO_DESCRIPTION.get(
             master_flake_analysis.status),
         'suspected_flake_build_number': (
             master_flake_analysis.suspected_flake_build_number),
         'master_name': master_name,
         'builder_name': builder_name,
         'build_number': build_number,
         'step_name': step_name,
         'test_name': test_name,
     }
 
-    build_numbers = []
-    pass_rates = []
     coordinates = []
 
     for data_point in master_flake_analysis.data_points:
-      coordinates.append((data_point.build_number, data_point.pass_rate))
+      coordinates.append([data_point.build_number, data_point.pass_rate])
 
     # Order by build number from earliest to latest.
     coordinates.sort(key=lambda x: x[0])
 
     data['pass_rates'] = coordinates
 
     return {
         'template': 'flake/result.html',
         'data': data
     }