[Findit] Updating flakiness dashboard to be able to triage results

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 import result_status
+from model import triage_status
 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)
@@ skipping 40 matching lines @@
 
   # Arguments number differs from overridden method - pylint: disable=W0221
   @classmethod
   def GetVersion(cls, master_name, builder_name, build_number, step_name,
                  test_name, version=None):  # pragma: no cover.
     return super(MasterFlakeAnalysis, cls).GetVersion(
         key=MasterFlakeAnalysis._CreateAnalysisId(
             master_name, builder_name, build_number, step_name, test_name),
         version=version)
 
+  def UpdateTriageResult(self, triage_result, suspect_info, user_name,
+                         version_number=None):
+    super(MasterFlakeAnalysis, self).UpdateTriageResult(
+        triage_result, suspect_info, user_name, version_number=version_number)
+
+    if triage_result == triage_status.TRIAGED_CORRECT:
+      self.result_status = result_status.FOUND_CORRECT
+    else:
+      self.result_status = result_status.FOUND_INCORRECT
+
   def Reset(self):
     super(MasterFlakeAnalysis, self).Reset()
     self.swarming_rerun_results = []
     self.error = None
     self.correct_regression_range = None
     self.correct_culprit = None
     self.algorithm_parameters = None
     self.suspected_flake_build_number = None
     self.data_points = []
+    self.result_status = None
 
   # A list of dicts containing information about each swarming rerun's results
   # that were involved in this analysis. The contents of this list will be used
   # for metrics, such as the number of cache hits this analysis benefited from,
   # the number of swarming tasks that were needed end-to-end to find the
   # regressed build number (if any), etc. See FlakeSwarmingTaskData for exact
   # fields.
   swarming_rerun_results = ndb.LocalStructuredProperty(
       FlakeSwarmingTaskData, repeated=True, compressed=True)
 
@@ skipping 26 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)
+
+  # Overall conclusion of analysis result for the flake. Found untriaged, Found
+  # Correct, etc. used to filter what is displayed on the check flake dashboard.
+  result_status = ndb.IntegerProperty(indexed=True)