These are the database objects used while finding the regression range. 1/3

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.
+
+from google.appengine.ext import ndb
+
+from common import constants
+from model import analysis_status
+from model.base_build_model import BaseBuildModel
+from model.base_analysis import BaseAnalysis
+from model.flake.flake_swarming_task import FlakeSwarmingTask
+
+class MasterFlakeAnalysis(BaseAnalysis, BaseBuildModel):
+  """Represents an analysis of a candidate flaky test in a Chromium Waterfall.
+
+  """
+  @staticmethod
+  def CreateAnalysisId(master_name, builder_name,
+                       build_number, step_name, test_name):
+    return '%s/%s/%s/%s/%s' % (master_name, builder_name,
+                               build_number, step_name, test_name)
+
+  @ndb.ComputedProperty
+  def step_name(self):
+    return self.key.pairs()[0][1].split('/')[3]
+
+  @ndb.ComputedProperty
+  def test_name(self):
+    return self.key.pairs()[0][1].split('/')[4]
+
+  @staticmethod
+  def _CreateKey(master_name, builder_name, build_number,
+                 step_name, test_name):  # pragma: no cover
+    return ndb.Key('MasterFlakeAnalysis',
+                   MasterFlakeAnalysis.CreateAnalysisId(
+                       master_name, builder_name, build_number,
+                       step_name, test_name))
+
+  @staticmethod
+  def Create(master_name, builder_name, build_number,
+             step_name, test_name):  # pragma: no cover
+    return MasterFlakeAnalysis(
+        key=MasterFlakeAnalysis._CreateKey(
+            master_name, builder_name, build_number,
+            step_name, test_name))
+
+  @staticmethod
+  def Get(master_name, builder_name, build_number,
+          step_name, test_name):  # pragma: no cover
+    return MasterFlakeAnalysis._CreateKey(
+        master_name, builder_name, build_number, step_name, test_name).get()
+
+  @staticmethod
+  def generate_data(flake_swarming_tasks):
+    data = []
+    # Generates data in the format which the template can read
+    # Go through list of flake_swarming_tasks
+    for fst in flake_swarming_tasks:
+      # Append results to a list (this is a placeholder)
+      data.append((fst.successes, fst.tries,
+                   fst.master_name(), fst.builder_name(),
+                   fst.step_name(), fst.build_number(),
+                   fst.test_name()))
+
+  # List of tested build_numbers and their corresponding success rates.
+  # We need to keep these sorted manually.
+  build_numbers = ndb.IntegerProperty(indexed=True, repeated=True)
+  success_rates = ndb.FloatProperty(indexed=False, repeated=True)
+  flake_swarming_tasks = ndb.KeyProperty(
+      kind='FlakeSwarmingTask', repeated=True)