[Findit] Adding support for triaging suspected builds from flake analysis

appengine/findit/model/flake/master_flake_analysis.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.
 
 import base64
 
 from google.appengine.ext import ndb
 
 from model.base_analysis import BaseAnalysis
 from model.base_build_model import BaseBuildModel
 from model.flake.flake_swarming_task import FlakeSwarmingTaskData
 from model.versioned_model import VersionedModel
+from model.base_triaged_model import TriagedModel
 
 
 class DataPoint(ndb.Model):
   build_number = ndb.IntegerProperty(indexed=False)
   pass_rate = ndb.FloatProperty(indexed=False)
 
 
-class MasterFlakeAnalysis(BaseAnalysis, BaseBuildModel, VersionedModel):
+class MasterFlakeAnalysis(
+    BaseAnalysis, BaseBuildModel, VersionedModel, TriagedModel):
   """Represents an analysis of a flaky test on a Waterfall test cycle."""
 
   @ndb.ComputedProperty
   def step_name(self):
     return self.key.pairs()[0][1].split('/')[3]
 
   @ndb.ComputedProperty
   def test_name(self):
     return base64.urlsafe_b64decode(self.key.pairs()[0][1].split('/')[4])
 
@@ skipping 81 matching lines @@
   data_points = ndb.LocalStructuredProperty(
       DataPoint, repeated=True, compressed=True)
 
   # Whether the analysis was triggered by a manual request through check flake,
   # Findit's automatic analysis upon detection, or Findit API.
   triggering_source = ndb.IntegerProperty(default=None, indexed=True)
 
   # Who triggered the analysis. Used for differentiating between manual and
   # automatic runs, and determining the most active users to gather feedback.
   triggering_user_email = ndb.StringProperty(default=None, indexed=False)