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

appengine/findit/waterfall/flake/test/recursive_flake_pipeline_test.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 common import constants
 from common.pipeline_wrapper import pipeline_handlers
 from model import analysis_status
 from model.flake.master_flake_analysis import MasterFlakeAnalysis
 from model.flake.flake_swarming_task import FlakeSwarmingTask
 from waterfall.flake import recursive_flake_pipeline
@@ skipping 110 matching lines @@
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(.08)
+    analysis.pass_rates.append(.08)
     analysis.build_numbers.append(100)
     analysis.put()
 
     NextBuildNumberPipeline.run(
         NextBuildNumberPipeline(), master_name, builder_name,
         master_build_number, build_number, step_name, test_name,
         test_result_future, queue_name, flakiness_algorithm_results_dict)
     self.assertEquals(flakiness_algorithm_results_dict['flakes_in_a_row'], 1)
 
   def testNextBuildPipelineForNewRecursionFirstStable(self):
@@ skipping 20 matching lines @@
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(0)
+    analysis.pass_rates.append(0)
     analysis.build_numbers.append(100)
     analysis.put()
 
     NextBuildNumberPipeline.run(
         NextBuildNumberPipeline(), master_name, builder_name,
         master_build_number, build_number, step_name,
         test_name, test_result_future, queue_name,
         flakiness_algorithm_results_dict)
     self.assertEquals(flakiness_algorithm_results_dict['stable_in_a_row'], 1)
 
@@ skipping 21 matching lines @@
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(0)
+    analysis.pass_rates.append(0)
     analysis.build_numbers.append(100)
     analysis.put()
 
     NextBuildNumberPipeline.run(
         NextBuildNumberPipeline(), master_name, builder_name,
         master_build_number, build_number, step_name,
         test_name, test_result_future, queue_name,
         flakiness_algorithm_results_dict)
     self.assertEquals(flakiness_algorithm_results_dict['stabled_out'], True)
 
@@ skipping 21 matching lines @@
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(.50)
+    analysis.pass_rates.append(.50)
     analysis.build_numbers.append(100)
     analysis.put()
 
     NextBuildNumberPipeline.run(
         NextBuildNumberPipeline(), master_name, builder_name,
         master_build_number, build_number, step_name,
         test_name, test_result_future, queue_name,
         flakiness_algorithm_results_dict)
     self.assertEquals(flakiness_algorithm_results_dict['flaked_out'], True)
 
@@ skipping 21 matching lines @@
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(.50)
+    analysis.pass_rates.append(.50)
     analysis.build_numbers.append(100)
     analysis.put()
 
     queue_name = {'x': False}
     def my_mocked_run(arg1, queue_name):  # pylint: disable=unused-argument
       queue_name['x'] = True  # pragma: no cover
 
     self.mock(
         recursive_flake_pipeline.RecursiveFlakePipeline, 'start', my_mocked_run)
     NextBuildNumberPipeline.run(
@@ skipping 26 matching lines @@
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.ERROR
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(.50)
+    analysis.pass_rates.append(.50)
     analysis.build_numbers.append(100)
     analysis.put()
 
     queue_name = {'x': False}
     def my_mocked_run(arg1, queue_name):  # pylint: disable=unused-argument
       queue_name['x'] = True  # pragma: no cover
 
     self.mock(
         recursive_flake_pipeline.RecursiveFlakePipeline, 'start', my_mocked_run)
     NextBuildNumberPipeline.run(
@@ skipping 25 matching lines @@
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(.50)
+    analysis.pass_rates.append(.50)
     analysis.build_numbers.append(100)
     analysis.put()
 
     queue_name = {'x': False}
     def my_mocked_run(arg1, queue_name):  # pylint: disable=unused-argument
       queue_name['x'] = True  # pragma: no cover
 
     self.mock(
         recursive_flake_pipeline.RecursiveFlakePipeline, 'start', my_mocked_run)
     NextBuildNumberPipeline.run(
         NextBuildNumberPipeline(), master_name, builder_name,
         master_build_number, build_number, step_name, test_name,
         test_result_future, queue_name, flakiness_algorithm_results_dict)
     self.assertTrue(queue_name['x'])
 
   def testGetNextRunSetStableLowerBoundary(self):
     master_name = 'm'
     builder_name = 'b'
     build_number = 100
     step_name = 's'
     test_name = 't'
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(1)
+    analysis.pass_rates.append(1)
     analysis.build_numbers.append(100)
     analysis.put()
 
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 4,
         'stable_in_a_row': 0,
         'stabled_out': False,
         'flaked_out': True,
         'last_build_number': 0,
         'lower_boundary': None,
@@ skipping 12 matching lines @@
     builder_name = 'b'
     build_number = 100
     step_name = 's'
     test_name = 't'
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(.5)
+    analysis.pass_rates.append(.5)
     analysis.build_numbers.append(100)
     analysis.put()
 
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 0,
         'stable_in_a_row': 0,
         'stabled_out': True,
         'flaked_out': False,
         'last_build_number': 0,
         'lower_boundary': None,
@@ skipping 12 matching lines @@
     builder_name = 'b'
     build_number = 100
     step_name = 's'
     test_name = 't'
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(.5)
+    analysis.pass_rates.append(.5)
     analysis.build_numbers.append(100)
     analysis.put()
 
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 0,
         'stable_in_a_row': 0,
         'stabled_out': True,
         'flaked_out': True,
         'last_build_number': 0,
         'lower_boundary': 100,
         'upper_boundary': 110,
         'lower_boundary_result': 'STABLE',
         'sequential_run_index': 0
     }
     next_run = sequential_next_run(analysis, flakiness_algorithm_results_dict)
     self.assertEqual(next_run, 101)
 
   def testSequentialFoundBorderFlake(self):
     master_name = 'm'
     builder_name = 'b'
     build_number = 100
     step_name = 's'
     test_name = 't'
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(.5)
+    analysis.pass_rates.append(.5)
     analysis.build_numbers.append(100)
     analysis.put()
 
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 0,
         'stable_in_a_row': 0,
         'stabled_out': True,
         'flaked_out': True,
         'last_build_number': 0,
         'lower_boundary': 100,
@@ skipping 10 matching lines @@
     builder_name = 'b'
     build_number = 100
     step_name = 's'
     test_name = 't'
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(1)
+    analysis.pass_rates.append(1)
     analysis.build_numbers.append(100)
     analysis.put()
 
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 0,
         'stable_in_a_row': 0,
         'stabled_out': True,
         'flaked_out': True,
         'last_build_number': 0,
         'lower_boundary': 100,
@@ skipping 11 matching lines @@
     builder_name = 'b'
     build_number = 100
     step_name = 's'
     test_name = 't'
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(1)
+    analysis.pass_rates.append(1)
     analysis.build_numbers.append(100)
     analysis.put()
 
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 0,
         'stable_in_a_row': 0,
         'stabled_out': True,
         'flaked_out': True,
         'last_build_number': 0,
         'lower_boundary': 100,
@@ skipping 29 matching lines @@
     self._CreateAndSaveMasterFlakeAnalysis(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.PENDING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(master_name, builder_name,
                                        build_number, step_name, test_name)
-    analysis.success_rates.append(1)
+    analysis.pass_rates.append(1)
     analysis.build_numbers.append(50)
     analysis.put()
 
     NextBuildNumberPipeline.run(
         NextBuildNumberPipeline(), master_name, builder_name,
         master_build_number, build_number, step_name, test_name,
         test_result_future, queue_name, flakiness_algorithm_results_dict)
     self.assertEquals(
         flakiness_algorithm_results_dict['sequential_run_index'], 1)
 
   def testNextBuildWhenTestNotExistingAfterStableInARow(self):
     master = MasterFlakeAnalysis.Create('m', 'b', 100, 's', 't')
-    master.success_rates = [0.8, 1.0, 1.0, -1]
+    master.pass_rates = [0.8, 1.0, 1.0, -1]
     master.build_numbers = [100, 80, 70, 60]
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 0,
         'stable_in_a_row': 2,
         'stabled_out': False,
         'flaked_out': False,
         'last_build_number': 0,
         'lower_boundary': None,
         'upper_boundary': None,
         'lower_boundary_result': None,
         'sequential_run_index': 0,
     }
 
     next_run = get_next_run(master, flakiness_algorithm_results_dict)
     self.assertEqual(81, next_run)
     self.assertTrue(flakiness_algorithm_results_dict['stabled_out'])
     self.assertTrue(flakiness_algorithm_results_dict['flaked_out'])
     self.assertEqual(80, flakiness_algorithm_results_dict['lower_boundary'])
     self.assertEqual('STABLE',
                      flakiness_algorithm_results_dict['lower_boundary_result'])
 
   def testNextBuildWhenTestNotExistingAfterFlakeInARow(self):
     master = MasterFlakeAnalysis.Create('m', 'b', 100, 's', 't')
-    master.success_rates = [0.8, 0.7, 0.75, -1]
+    master.pass_rates = [0.8, 0.7, 0.75, -1]
     master.build_numbers = [100, 80, 70, 60]
     flakiness_algorithm_results_dict = {
         'flakes_in_a_row': 3,
         'stable_in_a_row': 0,
         'stabled_out': False,
         'flaked_out': False,
         'last_build_number': 0,
         'lower_boundary': None,
         'upper_boundary': None,
         'lower_boundary_result': None,
@@ skipping 32 matching lines @@
         master_name, builder_name, master_build_number, step_name,
         test_name, status=analysis_status.RUNNING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(
         master_name, builder_name,
         master_build_number, step_name, test_name)
-    analysis.success_rates = [1.0, 1.0, 1.0, -1]
+    analysis.pass_rates = [1.0, 1.0, 1.0, -1]
     analysis.build_numbers = [100, 80, 70, 60]
     analysis.put()
 
     pipeline = NextBuildNumberPipeline()
     pipeline.run(
         master_name, builder_name,
         master_build_number, build_number, step_name, test_name,
         test_result_future, queue_name, flakiness_algorithm_results_dict)
 
     analysis = MasterFlakeAnalysis.Get(
@@ skipping 25 matching lines @@
         master_name, builder_name, master_build_number, step_name,
         test_name, status=analysis_status.RUNNING
     )
     self._CreateAndSaveFlakeSwarmingTask(
         master_name, builder_name, build_number, step_name,
         test_name, status=analysis_status.COMPLETED
     )
     analysis = MasterFlakeAnalysis.Get(
         master_name, builder_name,
         master_build_number, step_name, test_name)
-    analysis.success_rates = [1.0, 1.0, 1.0, 1.0]
+    analysis.pass_rates = [1.0, 1.0, 1.0, 1.0]
     analysis.build_numbers = [100, 80, 70, 60]
     analysis.put()
 
     pipeline = NextBuildNumberPipeline()
     pipeline.run(
         master_name, builder_name,
         master_build_number, build_number, step_name, test_name,
         test_result_future, queue_name, flakiness_algorithm_results_dict)
 
     analysis = MasterFlakeAnalysis.Get(
         master_name, builder_name,
         master_build_number, step_name, test_name)
     self.assertEqual(analysis_status.COMPLETED, analysis.status)