def test_lionjp_sanity(self):
self.add_mocks()
project_name = ProjectsSanityData.project_name
data_provider = KEngineDataProvider(project_name)
sessions = {'0C8C1649-A253-4B1B-8E23-A85E73ADC0D5': []}
# kpi_results = LIONJPKpiResults().get_kpi_results()
for session in sessions.keys():
data_provider.load_session_data(str(session))
# output = Output()
# LIONJPCalculations(data_provider, output).run_project_calculations()
for scene in sessions[session]:
data_provider.load_scene_data(str(session), scene_id=scene)
SceneCalculations(data_provider).calculate_kpis()
# self._assert_test_results_matches_reality(kpi_results)
# self._assert_old_tables_kpi_results_filled()
# self._assert_new_tables_kpi_results_filled(distinct_kpis_num=None, list_of_kpi_names=None)
self._assert_scene_tables_kpi_results_filled(distinct_kpis_num=None)
def test_pepsicouk_sanity(self):
project_name = ProjectsSanityData.project_name
data_provider = KEngineDataProvider(project_name)
sessions = {
'aee71e4d-cdd1-4474-803e-ef834d24871d': [94402],
'961edfb7-ae52-40a7-ab39-45064f8c554d': [92747],
'be03f331-a509-4ef5-99a0-a1807fc96b71': [93375]
}
for session in sessions.keys():
data_provider.load_session_data(str(session))
output = Output()
PEPSICOUKCalculations(data_provider,
output).run_project_calculations()
# self._assert_old_tables_kpi_results_filled()
self._assert_new_tables_kpi_results_filled()
for scene in sessions[session]:
data_provider.load_scene_data(str(session), scene_id=scene)
PEPSICOUKSceneCalculations(data_provider).calculate_kpis()
self._assert_scene_tables_kpi_results_filled()
project_name = 'sinoth-sand'
# RUN for scene level KPIs
session_scene_map = OrderedDict([
('12076D1D-FA3C-443C-951E-B4D0FBB80213', ['3825280F-A1A7-41A5-B90C-AA205A9A6D1E']),
('3EFA8C57-0FEB-4CFD-A819-2521D8082DFE', ['24F335D0-648C-41C2-A60D-C26D82641928']),
('4E5AA82E-C063-4B92-8C48-FA12761B6560', ['9ACBDCC5-24D4-4C0A-AB89-9B6219D8FE28']),
('56C336BB-9797-4C8F-AC1C-D18E40218404', ['3DEC7521-93F1-4888-9631-4C4808932C30']),
('BC981670-1F6B-485A-8695-A1FE552B07AE', ['2DADAFAE-7526-4AAE-A901-1AA623EA0BB9']),
('F3AAC28E-87C9-4276-9390-BD579B13A64A', ['4902F86D-7FEF-40D2-B08A-4C87D3D708B1'])
])
for session, scenes in session_scene_map.iteritems():
for e_scene in scenes:
print "\n"
data_provider = KEngineDataProvider(project_name)
data_provider.load_scene_data(session, scene_uid=e_scene)
Log.info("**********************************")
Log.info('*** Starting session: {sess}: scene: {scene}. ***'.format(sess=session, scene=e_scene))
Log.info("**********************************")
output = VanillaOutput()
SceneVanillaCalculations(data_provider, output).run_project_calculations()
save_scene_item_facts_to_data_provider(data_provider, output)
SceneCalculations(data_provider).calculate_kpis()
# sessions = [
# '6DF2E0C8-8AE0-432A-AD3B-C2BE8F086E3B',
# '6520B138-780D-4AD1-95CF-8DA1727C4580',
# '6944F6F5-79D7-43FB-BE32-E3FAE237FA63',
# '6FDB6757-E3DA-4297-941A-8C1A40DD2E90',
# '9DC66118-F981-4D01-A6DD-1E181FA05507',
# 'E0BE9853-B6C8-4B36-919C-5293BF52EF5B'
# ]
# "8395fc95-465b-47c2-ad65-6d10de13cd75": {'scene1':[10474779, '88a6cdff-4215-4efd-a7a5-23da566ab62f'],
# 'scene2':[10420017, '723eb38f-e241-4718-a8e1-0ff8d8cc1a1f']},
"9d364d60-edb4-430e-8f37-0246c880e21b": [],
"9965dff6-a5af-4acf-8664-7a30cc6b6abd": [],
"8b9bed83-1ce8-4e68-b20e-0711d1263238": [],
"9807b657-1cec-4d5a-82bd-83ec89b0bd8b": [],
"b84dc417-ce08-4328-b85b-c84a515474c1": [],
"cf54d865-f0a6-4f04-9b66-7c579e1ca8e3": [],
"841cd391-d323-481d-8fae-40bc32276195": []
}
for session in session_and_scenes.keys():
print("==================== {} ====================".format(session))
for scene in session_and_scenes[session]:
data_provider.load_scene_data(
session, session_and_scenes[session][scene][0],
session_and_scenes[session][scene][1])
output = VanillaOutput()
SceneVanillaCalculations(data_provider,
output).run_project_calculations()
save_scene_item_facts_to_data_provider(data_provider, output)
SceneCalculations(data_provider).calculate_kpis()
try:
data_provider.load_session_data(session)
except IndexError:
Log.info("Invalid session_uid.")
continue
output = Output()
CCUSCalculations(data_provider, output).run_project_calculations()
