[Findit] Added algorithm to analysis

appengine/findit/waterfall/flake/initialize_flake_pipeline.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 datetime import datetime
 
 from google.appengine.ext import ndb
 
 from common import appengine_util
 from common import constants
 from model import analysis_status
-from model.flake.flake_swarming_task import FlakeSwarmingTask
 from model.flake.master_flake_analysis import MasterFlakeAnalysis
 from waterfall.flake.recursive_flake_pipeline import RecursiveFlakePipeline
 
+# TODO(lijeffrey): Move to config.
+BUILD_NUMBERS_BACK = 1000

[lijeffrey, 2016/08/15 04:14:07]

nit: Rename this MAX_BUILD_NUMBERS_TO_LOOK_BACK or something more descriptive

[caiw, 2016/08/17 08:36:18]

Done.

+
 
 @ndb.transactional
 def NeedANewAnalysis(
     master_name, builder_name, build_number, step_name, test_name):
   """Checks status of analysis for the test and decides if a new one is needed.
 
   A MasterFlakeAnalysis entity for the given parameters will be created if none
   exists. When a new analysis is needed, this function will create and
   save a MasterFlakeAnalysis entity to the datastore.
 
   Returns:
     True if an analysis is needed, otherwise False.
   """
   master_flake_analysis = MasterFlakeAnalysis.Get(
-      master_name, builder_name, build_number,step_name, test_name)
+      master_name, builder_name, build_number, step_name, test_name)
 
   if not master_flake_analysis:
     master_flake_analysis = MasterFlakeAnalysis.Create(
         master_name, builder_name, build_number, step_name, test_name)
     master_flake_analysis.status = analysis_status.PENDING
     master_flake_analysis.put()
     return True
   elif (master_flake_analysis.status == analysis_status.COMPLETED or
         master_flake_analysis.status == analysis_status.PENDING or
         master_flake_analysis.status == analysis_status.RUNNING):
     return False
   else:
     # TODO(caiw): Reset method.
     MasterFlakeAnalysis.Get(
         master_name, builder_name, build_number,
         step_name, test_name).key.delete()
     master_flake_analysis = MasterFlakeAnalysis.Create(
         master_name, builder_name, build_number, step_name, test_name)
     master_flake_analysis.status = analysis_status.PENDING
     master_flake_analysis.put()
     return True
 
+
 # Unused arguments - pylint: disable=W0612, W0613
 def ScheduleAnalysisIfNeeded(master_name, builder_name, build_number, step_name,
                              test_name, force=False,
                              queue_name=constants.DEFAULT_QUEUE):
   """Schedules an analysis if needed and returns the MasterFlakeAnalysis.
 
   When the build failure was already analyzed and a new analysis is scheduled,
   the returned WfAnalysis will still have the result of last completed analysis.
 
   Args:
     master_name (str): The master name of the failed test
     builder_name (str): The builder name of the failed test
     build_number (int): The build number of the failed test
     step_name (str): The name of the test suite
     test_name (str): The single test we are checking
 
   Returns:
     A MasterFlakeAnalysis instance.
   """
   if NeedANewAnalysis(
       master_name, builder_name, build_number, step_name, test_name):
+    algo_dict = {

[lijeffrey, 2016/08/15 04:14:07]

nit: In general avoid abbreviating variable names (except dict or a few others
are ok) for readability. Maybe something like flakiness_algorithm_results_dict
or something 

[caiw, 2016/08/17 08:36:18]

Done.

+        'flakes_in_a_row': 0,
+        'stable_in_a_row': 0,
+        'stabled_out': False,
+        'flaked_out': False,
+        'last_build_number': max(0, build_number - BUILD_NUMBERS_BACK)
+    }
     pipeline_job = RecursiveFlakePipeline(
         master_name, builder_name, build_number, step_name, test_name,
-        master_build_number=build_number)
+        master_build_number=build_number, algo_dict=algo_dict)
     pipeline_job.target = appengine_util.GetTargetNameForModule(
         constants.WATERFALL_BACKEND)
     pipeline_job.start(queue_name=queue_name)
   return MasterFlakeAnalysis.Get(
       master_name, builder_name, build_number, step_name, test_name)