[Findit] Extending versioned_model.py to support versioning multiple entities of the same class.

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 common import time_util
 from model import analysis_status
 from model.flake.master_flake_analysis import MasterFlakeAnalysis
 from waterfall import waterfall_config
 from waterfall.flake.recursive_flake_pipeline import RecursiveFlakePipeline
 
 
 @ndb.transactional
 def NeedANewAnalysis(
     master_name, builder_name, build_number, step_name, test_name,
     allow_new_analysis=False):
   """Checks status of analysis for the test and decides if a new one is needed.
 
   A MasterFlakeAnalysis entity for the given parameters will be created if none
   exists. When a new analysis is needed, this function will create and
   save a MasterFlakeAnalysis entity to the datastore.
 
   Returns:
     True if an analysis is needed, otherwise False.
   """
   master_flake_analysis = MasterFlakeAnalysis.Get(
       master_name, builder_name, build_number, step_name, test_name)
 
   if not master_flake_analysis:
     if not allow_new_analysis:
       return False
     master_flake_analysis = MasterFlakeAnalysis.Create(
         master_name, builder_name, build_number, step_name, test_name)
+    master_flake_analysis.created_time = time_util.GetUTCNow()
     master_flake_analysis.status = analysis_status.PENDING
     master_flake_analysis.put()
     return True
   elif (master_flake_analysis.status == analysis_status.COMPLETED or
         master_flake_analysis.status == analysis_status.PENDING or
         master_flake_analysis.status == analysis_status.RUNNING):
     return False
   else:
     # TODO(caiw): Reset method.
     MasterFlakeAnalysis.Get(
@@ skipping 25 matching lines @@
     force (bool): Indicate whether to force a rerun of current analysis.
     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):
+    master_flake_analysis = MasterFlakeAnalysis.Get(
+        master_name, builder_name, build_number, step_name, test_name)
     check_flake_settings = waterfall_config.GetCheckFlakeSettings()
+
+    # TODO(lijeffrey): Allow for reruns with custom parameters if the user is
+    # not satisfied with with the results generated by the default ones provided
+    # by waterfall_config and record the custom ones here.
+    master_flake_analysis.algorithm_parameters = check_flake_settings
+    master_flake_analysis.put()
+
     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)
     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)
+      master_name, builder_name, build_number, step_name, test_name)