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

appengine/findit/model/flake/master_flake_analysis_data.py

Index: appengine/findit/model/flake/master_flake_analysis_data.py
diff --git a/appengine/findit/model/flake/master_flake_analysis_data.py b/appengine/findit/model/flake/master_flake_analysis_data.py
deleted file mode 100644
index 727dd4d3525e97a6ef2815a5d85c9dd800b4c80d..0000000000000000000000000000000000000000
--- a/appengine/findit/model/flake/master_flake_analysis_data.py
+++ /dev/null
@@ -1,92 +0,0 @@
-# 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_build_model import BaseBuildModel
-
-
-class CheckFlakeAnalysisData(BaseBuildModel):
-  """Represents a check flake task's metadata for a complete run."""
-  # The UTC timestamp the check flake task was requested.
-  created_time = ndb.DateTimeProperty(indexed=True)
-
-  # The UTC timestamp the check flake task came completed.
-  completed_time = ndb.DateTimeProperty(indexed=True)
-
-  # A dict containing information about each swarming rerun's results that can
-  # be used for metrics, such as number of cache hits, average run time, etc.
-  # Example dict:
-  # {
-  #     task_id_1: {
-  #         'request_time': 2016-09-06 (10:21:26.288) UTC
-  #         'start_time': 2016-09-06 (10:21:26.288) UTC,
-  #         'end_time': 2016-09-06 (10:21:26.288) UTC,
-  #         'build_number': 12345,
-  #         'cache_hit': True/False,
-  #         'number_of_iterations': 100,
-  #         'number_of_passes': 90,
-  #     },
-  #     task_id_2: {
-  #         ...
-  #     },
-  #     ...
-  # }
-  swarming_rerun_results = ndb.JsonProperty(indexed=False)
-
-  # Error code and message, if any.
-  error = ndb.JsonProperty(indexed=False)
-
-  # Integer representing the suspected build number that regressed.
-  regression_build_number = ndb.IntegerProperty(indexed=False)
-
-  # Boolean whether or not the suspected regression range/build is correct.
-  correct = ndb.BooleanProperty(indexed=False)
-
-  # The look back algorithm parameters that were used, as specified in Findit's
-  # configuration. For example,
-  # {
-  #     'iterations_to_rerun': 100,
-  #     'lower_flake_threshold': 0.02,
-  #     'max_build_numbers_to_look_back': 500,
-  #     'max_flake_in_a_row': 4,
-  #     'max_stable_in_a_row': 4,
-  #     'upper_flake_threshold': 0.98
-  # }
-  algorithm_parameters = ndb.JsonProperty(indexed=False)
-
-  @staticmethod
-  def _CreateKey(master_name, builder_name, build_number, step_name, test_name,
-                 version):
-    encoded_test_name = base64.urlsafe_b64encode(test_name)
-    key = '%s/%s/%s/%s/%s/%s' % (master_name, builder_name, build_number,
-                                 step_name, encoded_test_name, version)
-    return ndb.Key('CheckFlakeAnalysisData', key)
-
-  @staticmethod
-  def Create(master_name, builder_name, build_number, step_name, test_name,
-             version):
-    return CheckFlakeAnalysisData(key=CheckFlakeAnalysisData._CreateKey(
-        master_name, builder_name, build_number, step_name, test_name, version))
-
-  @staticmethod
-  def Get(master_name, builder_name, build_number, step_name, test_name,
-          version):
-    return CheckFlakeAnalysisData._CreateKey(
-        master_name, builder_name, build_number, step_name, test_name,
-        version).get()
-
-  @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])
-
-  @ndb.ComputedProperty
-  def version(self):
-    return self.key.pairs()[0][1].split('/')[5]