def setUp(self):
# Start container
super(TestActivateRSNVel3DInstrument, self).setUp()
config = DotDict()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(
node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(
node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
def setUp(self):
# Start container
#print 'instantiating container'
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dpsc_cli = DataProductManagementServiceClient()
self.rrclient = ResourceRegistryServiceClient()
self.damsclient = DataAcquisitionManagementServiceClient()
self.pubsubcli = PubsubManagementServiceClient()
self.ingestclient = IngestionManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.unsc = UserNotificationServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.identcli = IdentityManagementServiceClient()
#------------------------------------------
# Create the environment
#------------------------------------------
self.stream_def_id = self.pubsubcli.create_stream_definition(
name='SBE37_CDM')
self.process_definitions = {}
ingestion_worker_definition = ProcessDefinition(
name='ingestion worker')
ingestion_worker_definition.executable = {
'module':
'ion.processes.data.ingestion.science_granule_ingestion_worker',
'class': 'ScienceGranuleIngestionWorker'
}
process_definition_id = self.process_dispatcher.create_process_definition(
process_definition=ingestion_worker_definition)
self.process_definitions['ingestion_worker'] = process_definition_id
self.pids = []
self.exchange_points = []
self.exchange_names = []
#------------------------------------------------------------------------------------------------
# First launch the ingestors
#------------------------------------------------------------------------------------------------
self.exchange_space = 'science_granule_ingestion'
self.exchange_point = 'science_data'
config = DotDict()
config.process.datastore_name = 'datasets'
config.process.queue_name = self.exchange_space
self.exchange_names.append(self.exchange_space)
self.exchange_points.append(self.exchange_point)
pid = self.process_dispatcher.schedule_process(
self.process_definitions['ingestion_worker'], configuration=config)
log.debug("the ingestion worker process id: %s", pid)
self.pids.append(pid)
self.addCleanup(self.cleaning_up)
def assert_raw_granules_ingested(self, count, payload_size):
#--------------------------------------------------------------------------------
# Test the slicing capabilities
#--------------------------------------------------------------------------------
data_retriever = DataRetrieverServiceClient()
for i in range(0, count-1):
granule = data_retriever.retrieve(dataset_id=self._raw_dataset_id, query={'tdoa':slice(i,i+1)})
rdt = RecordDictionaryTool.load_from_granule(granule)
log.info("Granule index: %d, time: %s, size: %s", i, rdt['time'][0], len(rdt['raw'][0]))
self.assertEqual(payload_size, len(rdt['raw'][0]))
def assert_raw_granules_ingested(self, count, payload_size):
#--------------------------------------------------------------------------------
# Test the slicing capabilities
#--------------------------------------------------------------------------------
data_retriever = DataRetrieverServiceClient()
for i in range(0, count - 1):
granule = data_retriever.retrieve(dataset_id=self._raw_dataset_id,
query={'tdoa': slice(i, i + 1)})
rdt = RecordDictionaryTool.load_from_granule(granule)
log.info("Granule index: %d, time: %s, size: %s", i,
rdt['time'][0], len(rdt['raw'][0]))
self.assertEqual(payload_size, len(rdt['raw'][0]))
def setUp(self):
super(DataRetrieverIntTestAlpha,self).setUp()
self._start_container()
config = DotDict()
config.bootstrap.processes.ingestion.module = 'ion.processes.data.ingestion.ingestion_worker_a'
config.bootstrap.processes.replay.module = 'ion.processes.data.replay.replay_process_a'
self.container.start_rel_from_url('res/deploy/r2dm.yml', config)
self.datastore_name = 'test_datasets'
self.datastore = self.container.datastore_manager.get_datastore(self.datastore_name, profile=DataStore.DS_PROFILE.SCIDATA)
self.data_retriever = DataRetrieverServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
xs_dot_xp = CFG.core_xps.science_data
try:
self.XS, xp_base = xs_dot_xp.split('.')
self.XP = '.'.join([get_sys_name(), xp_base])
except ValueError:
raise StandardError('Invalid CFG for core_xps.science_data: "%s"; must have "xs.xp" structure' % xs_dot_xp)
def setUp(self):
# Start container
super(TestActivateInstrumentIntegration, self).setUp()
config = DotDict()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
self.usernotificationclient = UserNotificationServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
self.event_publisher = EventPublisher()
def setUp(self):
super(DataRetrieverServiceIntTest, self).setUp()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2dm.yml')
self.couch = self.container.datastore_manager.get_datastore(
'test_data_retriever', profile=DataStore.DS_PROFILE.SCIDATA)
self.datastore_name = 'test_data_retriever'
self.dr_cli = DataRetrieverServiceClient(node=self.container.node)
self.dsm_cli = DatasetManagementServiceClient(node=self.container.node)
self.rr_cli = ResourceRegistryServiceClient(node=self.container.node)
self.ps_cli = PubsubManagementServiceClient(node=self.container.node)
self.tms_cli = TransformManagementServiceClient(
node=self.container.node)
self.pd_cli = ProcessDispatcherServiceClient(node=self.container.node)
xs_dot_xp = CFG.core_xps.science_data
try:
self.XS, xp_base = xs_dot_xp.split('.')
self.XP = '.'.join([bootstrap.get_sys_name(), xp_base])
except ValueError:
raise StandardError(
'Invalid CFG for core_xps.science_data: "%s"; must have "xs.xp" structure'
% xs_dot_xp)
self.thread_pool = list()
def setUp(self):
# Start container
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(
node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(
node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
self.event_publisher = EventPublisher()
def setUp(self): # Love the non pep-8 convention
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.process_dispatcher = ProcessDispatcherServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.ingestion_management = IngestionManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.event = Event()
self.exchange_space_name = 'test_granules'
self.exchange_point_name = 'science_data'
self.i = 0
self.cci = 0
def setUp(self):
# Start container
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
# Now create client to DataAcquisitionManagementService
self.client = DataAcquisitionManagementServiceClient(node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dams_client = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsub_client = PubsubManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.data_retriever = DataRetrieverServiceClient(node=self.container.node)
self._container_client = ContainerAgentClient(node=self.container.node, name=self.container.name)
# Data async and subscription TODO: Replace with new subscriber
self._finished_count = None
#TODO: Switch to gevent.queue.Queue
self._async_finished_result = AsyncResult()
self._finished_events_received = []
self._finished_event_subscriber = None
self._start_finished_event_subscriber()
self.addCleanup(self._stop_finished_event_subscriber)
self.DVR_CONFIG = {}
self.DVR_CONFIG = {
'dvr_mod' : 'ion.agents.data.handlers.slocum_data_handler',
'dvr_cls' : 'SlocumDataHandler',
}
self._setup_resources()
self.agent_config = {
'driver_config' : self.DVR_CONFIG,
'stream_config' : {},
'agent' : {'resource_id': self.EDA_RESOURCE_ID},
'test_mode' : True
}
datasetagent_instance_obj = IonObject(RT.ExternalDatasetAgentInstance, name='ExternalDatasetAgentInstance1', description='external data agent instance',
handler_module=self.EDA_MOD, handler_class=self.EDA_CLS,
dataset_driver_config=self.DVR_CONFIG, dataset_agent_config=self.agent_config )
self.dataset_agent_instance_id = self.dams_client.create_external_dataset_agent_instance(external_dataset_agent_instance=datasetagent_instance_obj,
external_dataset_agent_id=self.datasetagent_id, external_dataset_id=self.EDA_RESOURCE_ID)
#TG: Setup/configure the granule logger to log granules as they're published
pid = self.dams_client.start_external_dataset_agent_instance(self.dataset_agent_instance_id)
dataset_agent_instance_obj= self.dams_client.read_external_dataset_agent_instance(self.dataset_agent_instance_id)
print 'TestBulkIngest: Dataset agent instance obj: = ', dataset_agent_instance_obj
# Start a resource agent client to talk with the instrument agent.
self._ia_client = ResourceAgentClient('datasetagentclient', name=pid, process=FakeProcess())
log.debug(" test_createTransformsThenActivateInstrument:: got ia client %s", str(self._ia_client))
def setUp(self):
self.i = 0
self._start_container()
self.container.start_rel_from_url('res/deploy/r2params.yml')
self.dataset_management = DatasetManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.resource_registry = self.container.resource_registry
self.data_retriever = DataRetrieverServiceClient()
pdicts, _ = self.resource_registry.find_resources(
restype='ParameterDictionary', id_only=False)
self.dp_ids = []
for pdict in pdicts:
stream_def_id = self.pubsub_management.create_stream_definition(
pdict.name, parameter_dictionary_id=pdict._id)
dp_id = self.make_dp(stream_def_id)
if dp_id: self.dp_ids.append(dp_id)
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.RR = ResourceRegistryServiceClient()
self.RR2 = EnhancedResourceRegistryClient(self.RR)
self.OMS = ObservatoryManagementServiceClient()
self.org_management_service = OrgManagementServiceClient()
self.IMS = InstrumentManagementServiceClient()
self.dpclient = DataProductManagementServiceClient()
self.pubsubcli = PubsubManagementServiceClient()
self.damsclient = DataAcquisitionManagementServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self._load_stage = 0
self._resources = {}
def setUp(self):
# Start container
#print 'instantiating container'
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dpsc_cli = DataProductManagementServiceClient(node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.ingestclient = IngestionManagementServiceClient(node=self.container.node)
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.unsc = UserNotificationServiceClient()
self.data_retriever = DataRetrieverServiceClient()
#------------------------------------------
# Create the environment
#------------------------------------------
datastore_name = CACHE_DATASTORE_NAME
self.db = self.container.datastore_manager.get_datastore(datastore_name)
self.stream_def_id = self.pubsubcli.create_stream_definition(name='SBE37_CDM')
self.process_definitions = {}
ingestion_worker_definition = ProcessDefinition(name='ingestion worker')
ingestion_worker_definition.executable = {
'module':'ion.processes.data.ingestion.science_granule_ingestion_worker',
'class' :'ScienceGranuleIngestionWorker'
}
process_definition_id = self.process_dispatcher.create_process_definition(process_definition=ingestion_worker_definition)
self.process_definitions['ingestion_worker'] = process_definition_id
self.pids = []
self.exchange_points = []
self.exchange_names = []
#------------------------------------------------------------------------------------------------
# First launch the ingestors
#------------------------------------------------------------------------------------------------
self.exchange_space = 'science_granule_ingestion'
self.exchange_point = 'science_data'
config = DotDict()
config.process.datastore_name = 'datasets'
config.process.queue_name = self.exchange_space
self.exchange_names.append(self.exchange_space)
self.exchange_points.append(self.exchange_point)
pid = self.process_dispatcher.schedule_process(self.process_definitions['ingestion_worker'],configuration=config)
log.debug("the ingestion worker process id: %s", pid)
self.pids.append(pid)
self.addCleanup(self.cleaning_up)
def setUp(self):
super(DataRetrieverServiceIntTest,self).setUp()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2dm.yml')
self.couch = self.container.datastore_manager.get_datastore('test_data_retriever', profile=DataStore.DS_PROFILE.EXAMPLES)
self.datastore_name = 'test_data_retriever'
self.dr_cli = DataRetrieverServiceClient(node=self.container.node)
self.dsm_cli = DatasetManagementServiceClient(node=self.container.node)
self.rr_cli = ResourceRegistryServiceClient(node=self.container.node)
self.ps_cli = PubsubManagementServiceClient(node=self.container.node)
def setUp(self):
# Start container
super(TestActivateInstrumentIntegration, self).setUp()
config = DotDict()
config.bootstrap.use_es = True
self._start_container()
self.addCleanup(TestActivateInstrumentIntegration.es_cleanup)
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(
node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(
node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
self.usernotificationclient = UserNotificationServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
self.event_publisher = EventPublisher()
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.pubsub_management = PubsubManagementServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.data_acquisition_management = DataAcquisitionManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.process_dispatch_client = ProcessDispatcherServiceClient(node=self.container.node)
self.resource_registry = self.container.resource_registry
self.context_ids = self.build_param_contexts()
self.setup_resources()
def setUp(self):
self._start_container()
config = DotDict()
config.bootstrap.processes.ingestion.module = 'ion.processes.data.ingestion.ingestion_worker_a'
config.bootstrap.processes.replay.module = 'ion.processes.data.replay.replay_process_a'
self.container.start_rel_from_url('res/deploy/r2dm.yml', config)
self.datastore_name = 'test_datasets'
self.pubsub_management = PubsubManagementServiceClient()
self.ingestion_management = IngestionManagementServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.data_retriever = DataRetrieverServiceClient()
def setUp(self):
self.i=0
self._start_container()
self.container.start_rel_from_url('res/deploy/r2params.yml')
self.dataset_management = DatasetManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.resource_registry = self.container.resource_registry
self.data_retriever = DataRetrieverServiceClient()
pdicts, _ = self.resource_registry.find_resources(restype='ParameterDictionary', id_only=False)
self.dp_ids = []
for pdict in pdicts:
stream_def_id = self.pubsub_management.create_stream_definition(pdict.name, parameter_dictionary_id=pdict._id)
dp_id = self.make_dp(stream_def_id)
if dp_id: self.dp_ids.append(dp_id)
def setUp(self):
# Start container
#print 'instantiating container'
self._start_container()
log.debug("Start rel from url")
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.DPMS = DataProductManagementServiceClient()
self.RR = ResourceRegistryServiceClient()
self.RR2 = EnhancedResourceRegistryClient(self.RR)
self.DAMS = DataAcquisitionManagementServiceClient()
self.PSMS = PubsubManagementServiceClient()
self.ingestclient = IngestionManagementServiceClient()
self.PD = ProcessDispatcherServiceClient()
self.DSMS = DatasetManagementServiceClient()
self.unsc = UserNotificationServiceClient()
self.data_retriever = DataRetrieverServiceClient()
#------------------------------------------
# Create the environment
#------------------------------------------
log.debug("get datastore")
datastore_name = CACHE_DATASTORE_NAME
self.db = self.container.datastore_manager.get_datastore(
datastore_name)
self.stream_def_id = self.PSMS.create_stream_definition(
name='SBE37_CDM')
self.process_definitions = {}
ingestion_worker_definition = ProcessDefinition(
name='ingestion worker')
ingestion_worker_definition.executable = {
'module':
'ion.processes.data.ingestion.science_granule_ingestion_worker',
'class': 'ScienceGranuleIngestionWorker'
}
process_definition_id = self.PD.create_process_definition(
process_definition=ingestion_worker_definition)
self.process_definitions['ingestion_worker'] = process_definition_id
self.pids = []
self.exchange_points = []
self.exchange_names = []
self.addCleanup(self.cleaning_up)
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.resource_registry = self.container.resource_registry
self.RR2 = EnhancedResourceRegistryClient(self.resource_registry)
self.data_acquisition_management = DataAcquisitionManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.instrument_management = InstrumentManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.data_process_management = DataProcessManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.user_notification = UserNotificationServiceClient()
self.workflow_management = WorkflowManagementServiceClient()
self.visualization = VisualizationServiceClient()
def validate_data_ingest_retrieve(self, dataset_id):
assertions = self.assertTrue
self.data_retriever = DataRetrieverServiceClient(node=self.container.node)
#validate that data was ingested
replay_granule = self.data_retriever.retrieve_last_granule(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
salinity = get_safe(rdt, 'salinity')
assertions(salinity != None)
#retrieve all the granules from the database and check the values
replay_granule_all = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(replay_granule_all)
for k, v in rdt.iteritems():
if k == 'salinity':
for val in numpy.nditer(v):
assertions(val > 0)
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.RR = ResourceRegistryServiceClient()
self.RR2 = EnhancedResourceRegistryClient(self.RR)
self.OMS = ObservatoryManagementServiceClient()
self.org_management_service = OrgManagementServiceClient()
self.IMS = InstrumentManagementServiceClient()
self.dpclient = DataProductManagementServiceClient()
self.pubsubcli = PubsubManagementServiceClient()
self.damsclient = DataAcquisitionManagementServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self._load_stage = 0
self._resources = {}
class DataRetrieverIntTestAlpha(IonIntegrationTestCase):
def setUp(self):
super(DataRetrieverIntTestAlpha,self).setUp()
self._start_container()
config = DotDict()
config.bootstrap.processes.ingestion.module = 'ion.processes.data.ingestion.ingestion_worker_a'
config.bootstrap.processes.replay.module = 'ion.processes.data.replay.replay_process_a'
self.container.start_rel_from_url('res/deploy/r2dm.yml', config)
self.datastore_name = 'test_datasets'
self.datastore = self.container.datastore_manager.get_datastore(self.datastore_name, profile=DataStore.DS_PROFILE.SCIDATA)
self.data_retriever = DataRetrieverServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
xs_dot_xp = CFG.core_xps.science_data
try:
self.XS, xp_base = xs_dot_xp.split('.')
self.XP = '.'.join([get_sys_name(), xp_base])
except ValueError:
raise StandardError('Invalid CFG for core_xps.science_data: "%s"; must have "xs.xp" structure' % xs_dot_xp)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_define_replay(self):
# Create a dataset to work with
dataset_id = self.dataset_management.create_dataset('fakestream', self.datastore_name)
replay_id, stream_id = self.data_retriever.define_replay(dataset_id=dataset_id)
# Verify that the replay instance was created
replay = self.resource_registry.read(replay_id)
pid = replay.process_id
process = self.container.proc_manager.procs[pid]
self.assertIsInstance(process,ReplayProcess, 'Incorrect process launched')
def setUp(self):
# Start container
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubclient = PubsubManagementServiceClient(node=self.container.node)
self.ingestclient = IngestionManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(node=self.container.node)
self.workflowclient = WorkflowManagementServiceClient(node=self.container.node)
self.process_dispatcher = ProcessDispatcherServiceClient(node=self.container.node)
self.data_retriever = DataRetrieverServiceClient(node=self.container.node)
self.ctd_stream_def = SBE37_CDM_stream_definition()
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.resource_registry = self.container.resource_registry
self.RR2 = EnhancedResourceRegistryClient(self.resource_registry)
self.data_acquisition_management = DataAcquisitionManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.instrument_management = InstrumentManagementServiceClient()
self.discovery = DiscoveryServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.data_process_management = DataProcessManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.user_notification = UserNotificationServiceClient()
self.observatory_management = ObservatoryManagementServiceClient()
self.visualization = VisualizationServiceClient()
self.ph = ParameterHelper(self.dataset_management, self.addCleanup)
self.ctd_count = 0
def setUp(self): # Love the non pep-8 convention
self._start_container()
self.container.start_rel_from_url("res/deploy/r2deploy.yml")
self.process_dispatcher = ProcessDispatcherServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.ingestion_management = IngestionManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.pids = []
self.event = Event()
self.exchange_space_name = "test_granules"
self.exchange_point_name = "science_data"
self.i = 0
self.purge_queues()
self.queue_buffer = []
self.streams = []
self.addCleanup(self.stop_all_ingestion)
def setUp(self):
# Start container
super(TestActivateRSNVel3DInstrument, self).setUp()
config = DotDict()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
def setUp(self):
# Start container
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(
node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(
node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
self.event_publisher = EventPublisher()
self.egg_url_good = "http://sddevrepo.oceanobservatories.org/releases/seabird_sbe37smb_ooicore-0.0.1a-py2.7.egg"
self.egg_url_bad = "http://sddevrepo.oceanobservatories.org/releases/seabird_sbe37smb_ooicore-0.1a-py2.7.egg"
self.egg_url_404 = "http://sddevrepo.oceanobservatories.org/releases/completely_made_up_404.egg"
def setUp(self):
# Start container
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
def setUp(self):
super(DataRetrieverIntTest, self).setUp()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2dm.yml')
self.datastore_name = 'test_datasets'
self.datastore = self.container.datastore_manager.get_datastore(
self.datastore_name, profile=DataStore.DS_PROFILE.SCIDATA)
self.data_retriever = DataRetrieverServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
xs_dot_xp = CFG.core_xps.science_data
try:
self.XS, xp_base = xs_dot_xp.split('.')
self.XP = '.'.join([get_sys_name(), xp_base])
except ValueError:
raise StandardError(
'Invalid CFG for core_xps.science_data: "%s"; must have "xs.xp" structure'
% xs_dot_xp)
class TestDMEnd2End(IonIntegrationTestCase):
def setUp(self): # Love the non pep-8 convention
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.process_dispatcher = ProcessDispatcherServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.ingestion_management = IngestionManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.pids = []
self.event = Event()
self.exchange_space_name = 'test_granules'
self.exchange_point_name = 'science_data'
self.i = 0
self.purge_queues()
self.queue_buffer = []
self.streams = []
self.addCleanup(self.stop_all_ingestion)
def purge_queues(self):
xn = self.container.ex_manager.create_xn_queue('science_granule_ingestion')
xn.purge()
def tearDown(self):
self.purge_queues()
for pid in self.pids:
self.container.proc_manager.terminate_process(pid)
IngestionManagementIntTest.clean_subscriptions()
for queue in self.queue_buffer:
if isinstance(queue, ExchangeNameQueue):
queue.delete()
elif isinstance(queue, str):
xn = self.container.ex_manager.create_xn_queue(queue)
xn.delete()
#--------------------------------------------------------------------------------
# Helper/Utility methods
#--------------------------------------------------------------------------------
def create_dataset(self, parameter_dict_id=''):
'''
Creates a time-series dataset
'''
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
if not parameter_dict_id:
parameter_dict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
dataset_id = self.dataset_management.create_dataset('test_dataset_%i'%self.i, parameter_dictionary_id=parameter_dict_id, spatial_domain=sdom, temporal_domain=tdom)
return dataset_id
def get_datastore(self, dataset_id):
'''
Gets an instance of the datastore
This method is primarily used to defeat a bug where integration tests in multiple containers may sometimes
delete a CouchDB datastore and the other containers are unaware of the new state of the datastore.
'''
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def get_ingestion_config(self):
'''
Grab the ingestion configuration from the resource registry
'''
# The ingestion configuration should have been created by the bootstrap service
# which is configured through r2deploy.yml
ingest_configs, _ = self.resource_registry.find_resources(restype=RT.IngestionConfiguration,id_only=True)
return ingest_configs[0]
def launch_producer(self, stream_id=''):
'''
Launch the producer
'''
pid = self.container.spawn_process('better_data_producer', 'ion.processes.data.example_data_producer', 'BetterDataProducer', {'process':{'stream_id':stream_id}})
self.pids.append(pid)
def make_simple_dataset(self):
'''
Makes a stream, a stream definition and a dataset, the essentials for most of these tests
'''
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
stream_def_id = self.pubsub_management.create_stream_definition('ctd data', parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream('ctd stream %i' % self.i, 'xp1', stream_definition_id=stream_def_id)
dataset_id = self.create_dataset(pdict_id)
self.get_datastore(dataset_id)
self.i += 1
return stream_id, route, stream_def_id, dataset_id
def publish_hifi(self,stream_id,stream_route,offset=0):
'''
Publish deterministic data
'''
pub = StandaloneStreamPublisher(stream_id, stream_route)
stream_def = self.pubsub_management.read_stream_definition(stream_id=stream_id)
stream_def_id = stream_def._id
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(10) + (offset * 10)
rdt['temp'] = np.arange(10) + (offset * 10)
pub.publish(rdt.to_granule())
def publish_fake_data(self,stream_id, route):
'''
Make four granules
'''
for i in xrange(4):
self.publish_hifi(stream_id,route,i)
def start_ingestion(self, stream_id, dataset_id):
'''
Starts ingestion/persistence for a given dataset
'''
ingest_config_id = self.get_ingestion_config()
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingest_config_id, dataset_id=dataset_id)
def stop_ingestion(self, stream_id):
ingest_config_id = self.get_ingestion_config()
self.ingestion_management.unpersist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingest_config_id)
def stop_all_ingestion(self):
try:
[self.stop_ingestion(sid) for sid in self.streams]
except:
pass
def validate_granule_subscription(self, msg, route, stream_id):
'''
Validation for granule format
'''
if msg == {}:
return
rdt = RecordDictionaryTool.load_from_granule(msg)
log.info('%s', rdt.pretty_print())
self.assertIsInstance(msg,Granule,'Message is improperly formatted. (%s)' % type(msg))
self.event.set()
def wait_until_we_have_enough_granules(self, dataset_id='',data_size=40):
'''
Loops until there is a sufficient amount of data in the dataset
'''
done = False
with gevent.Timeout(40):
while not done:
extents = self.dataset_management.dataset_extents(dataset_id, 'time')[0]
granule = self.data_retriever.retrieve_last_data_points(dataset_id, 1)
rdt = RecordDictionaryTool.load_from_granule(granule)
if rdt['time'] and rdt['time'][0] != rdt._pdict.get_context('time').fill_value and extents >= data_size:
done = True
else:
gevent.sleep(0.2)
#--------------------------------------------------------------------------------
# Test Methods
#--------------------------------------------------------------------------------
@attr('SMOKE')
def test_dm_end_2_end(self):
#--------------------------------------------------------------------------------
# Set up a stream and have a mock instrument (producer) send data
#--------------------------------------------------------------------------------
self.event.clear()
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict',id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext('binary', param_type=ArrayType())
context_ids.append(self.dataset_management.create_parameter_context('binary', bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext('records', param_type=RecordType())
context_ids.append(self.dataset_management.create_parameter_context('records', rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary('replay_pdict', parameter_context_ids=context_ids, temporal_context='time')
stream_definition = self.pubsub_management.create_stream_definition('ctd data', parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream('producer', exchange_point=self.exchange_point_name, stream_definition_id=stream_definition)
#--------------------------------------------------------------------------------
# Start persisting the data on the stream
# - Get the ingestion configuration from the resource registry
# - Create the dataset
# - call persist_data_stream to setup the subscription for the ingestion workers
# on the stream that you specify which causes the data to be persisted
#--------------------------------------------------------------------------------
ingest_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingest_config_id, dataset_id=dataset_id)
#--------------------------------------------------------------------------------
# Now the granules are ingesting and persisted
#--------------------------------------------------------------------------------
self.launch_producer(stream_id)
self.wait_until_we_have_enough_granules(dataset_id,40)
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_id)
self.assertIsInstance(replay_data, Granule)
rdt = RecordDictionaryTool.load_from_granule(replay_data)
self.assertTrue((rdt['time'][:10] == np.arange(10)).all(),'%s' % rdt['time'][:])
self.assertTrue((rdt['binary'][:10] == np.array(['hi']*10, dtype='object')).all())
#--------------------------------------------------------------------------------
# Now to try the streamed approach
#--------------------------------------------------------------------------------
replay_stream_id, replay_route = self.pubsub_management.create_stream('replay_out', exchange_point=self.exchange_point_name, stream_definition_id=stream_definition)
self.replay_id, process_id = self.data_retriever.define_replay(dataset_id=dataset_id, stream_id=replay_stream_id)
log.info('Process ID: %s', process_id)
replay_client = ReplayClient(process_id)
#--------------------------------------------------------------------------------
# Create the listening endpoint for the the retriever to talk to
#--------------------------------------------------------------------------------
xp = self.container.ex_manager.create_xp(self.exchange_point_name)
subscriber = StandaloneStreamSubscriber(self.exchange_space_name, self.validate_granule_subscription)
self.queue_buffer.append(self.exchange_space_name)
subscriber.start()
subscriber.xn.bind(replay_route.routing_key, xp)
self.data_retriever.start_replay_agent(self.replay_id)
self.assertTrue(replay_client.await_agent_ready(5), 'The process never launched')
replay_client.start_replay()
self.assertTrue(self.event.wait(10))
subscriber.stop()
self.data_retriever.cancel_replay_agent(self.replay_id)
#--------------------------------------------------------------------------------
# Test the slicing capabilities
#--------------------------------------------------------------------------------
granule = self.data_retriever.retrieve(dataset_id=dataset_id, query={'tdoa':slice(0,5)})
rdt = RecordDictionaryTool.load_from_granule(granule)
b = rdt['time'] == np.arange(5)
self.assertTrue(b.all() if not isinstance(b,bool) else b)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
def test_coverage_transform(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_parsed()
stream_def_id = self.pubsub_management.create_stream_definition('ctd parsed', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
stream_id, route = self.pubsub_management.create_stream('example', exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id)
self.addCleanup(self.pubsub_management.delete_stream, stream_id)
ingestion_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingestion_config_id, dataset_id=dataset_id)
self.addCleanup(self.ingestion_management.unpersist_data_stream, stream_id, ingestion_config_id)
publisher = StandaloneStreamPublisher(stream_id, route)
rdt = ph.get_rdt(stream_def_id)
ph.fill_parsed_rdt(rdt)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_monitor.event.wait(30))
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_array_almost_equal(rdt_out['time'], rdt['time'])
np.testing.assert_array_almost_equal(rdt_out['temp'], rdt['temp'])
np.testing.assert_array_almost_equal(rdt_out['conductivity_L1'], np.array([42.914]))
np.testing.assert_array_almost_equal(rdt_out['temp_L1'], np.array([20.]))
np.testing.assert_array_almost_equal(rdt_out['pressure_L1'], np.array([3.068]))
np.testing.assert_array_almost_equal(rdt_out['density'], np.array([1021.7144739593881]))
np.testing.assert_array_almost_equal(rdt_out['salinity'], np.array([30.935132729668283]))
def test_qc_events(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_qc_pdict()
stream_def_id = self.pubsub_management.create_stream_definition('qc stream def', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
stream_id, route = self.pubsub_management.create_stream('qc stream', exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id)
self.addCleanup(self.pubsub_management.delete_stream, stream_id)
ingestion_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
config = DotDict()
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingestion_config_id, dataset_id=dataset_id, config=config)
self.addCleanup(self.ingestion_management.unpersist_data_stream, stream_id, ingestion_config_id)
publisher = StandaloneStreamPublisher(stream_id, route)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(10)
rdt['temp'] = np.arange(10) * 3
verified = Event()
def verification(event, *args, **kwargs):
self.assertEquals(event.qc_parameter, 'temp_qc')
self.assertEquals(event.temporal_value, 7)
verified.set()
es = EventSubscriber(event_type=OT.ParameterQCEvent, origin=dataset_id, callback=verification, auto_delete=True)
es.start()
self.addCleanup(es.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(verified.wait(10))
def test_lookup_values_ingest_replay(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_lookups()
stream_def_id = self.pubsub_management.create_stream_definition('lookups', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
stream_id, route = self.pubsub_management.create_stream('example', exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id)
self.addCleanup(self.pubsub_management.delete_stream, stream_id)
ingestion_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
config = DotDict()
config.process.lookup_docs = ['test1', 'test2']
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingestion_config_id, dataset_id=dataset_id, config=config)
self.addCleanup(self.ingestion_management.unpersist_data_stream, stream_id, ingestion_config_id)
stored_value_manager = StoredValueManager(self.container)
stored_value_manager.stored_value_cas('test1',{'offset_a':10.0, 'offset_b':13.1})
publisher = StandaloneStreamPublisher(stream_id, route)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = [20.0] * 20
granule = rdt.to_granule()
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(30))
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_array_almost_equal(rdt_out['time'], np.arange(20))
np.testing.assert_array_almost_equal(rdt_out['temp'], np.array([20.] * 20))
np.testing.assert_array_almost_equal(rdt_out['calibrated'], np.array([30.]*20))
np.testing.assert_array_equal(rdt_out['offset_b'], np.array([rdt_out.fill_value('offset_b')] * 20))
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(20,40)
rdt['temp'] = [20.0] * 20
granule = rdt.to_granule()
dataset_monitor.event.clear()
stored_value_manager.stored_value_cas('test1',{'offset_a':20.0})
stored_value_manager.stored_value_cas('coefficient_document',{'offset_b':10.0})
gevent.sleep(2)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(30))
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_array_almost_equal(rdt_out['time'], np.arange(40))
np.testing.assert_array_almost_equal(rdt_out['temp'], np.array([20.] * 20 + [20.] * 20))
np.testing.assert_array_equal(rdt_out['offset_b'], np.array([10.] * 40))
np.testing.assert_array_almost_equal(rdt_out['calibrated'], np.array([30.]*20 + [40.]*20))
np.testing.assert_array_almost_equal(rdt_out['calibrated_b'], np.array([40.] * 20 + [50.] * 20))
@unittest.skip('Doesnt work')
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_replay_pause(self):
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict',id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext('binary', param_type=ArrayType())
context_ids.append(self.dataset_management.create_parameter_context('binary', bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext('records', param_type=RecordType())
context_ids.append(self.dataset_management.create_parameter_context('records', rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary('replay_pdict', parameter_context_ids=context_ids, temporal_context='time')
stream_def_id = self.pubsub_management.create_stream_definition('replay_stream', parameter_dictionary_id=pdict_id)
replay_stream, replay_route = self.pubsub_management.create_stream('replay', 'xp1', stream_definition_id=stream_def_id)
dataset_id = self.create_dataset(pdict_id)
scov = DatasetManagementService._get_simplex_coverage(dataset_id)
bb = CoverageCraft(scov)
bb.rdt['time'] = np.arange(100)
bb.rdt['temp'] = np.random.random(100) + 30
bb.sync_with_granule()
DatasetManagementService._persist_coverage(dataset_id, bb.coverage) # This invalidates it for multi-host configurations
# Set up the subscriber to verify the data
subscriber = StandaloneStreamSubscriber(self.exchange_space_name, self.validate_granule_subscription)
xp = self.container.ex_manager.create_xp('xp1')
self.queue_buffer.append(self.exchange_space_name)
subscriber.start()
subscriber.xn.bind(replay_route.routing_key, xp)
# Set up the replay agent and the client wrapper
# 1) Define the Replay (dataset and stream to publish on)
self.replay_id, process_id = self.data_retriever.define_replay(dataset_id=dataset_id, stream_id=replay_stream)
# 2) Make a client to the interact with the process (optionall provide it a process to bind with)
replay_client = ReplayClient(process_id)
# 3) Start the agent (launch the process)
self.data_retriever.start_replay_agent(self.replay_id)
# 4) Start replaying...
replay_client.start_replay()
# Wait till we get some granules
self.assertTrue(self.event.wait(5))
# We got granules, pause the replay, clear the queue and allow the process to finish consuming
replay_client.pause_replay()
gevent.sleep(1)
subscriber.xn.purge()
self.event.clear()
# Make sure there's no remaining messages being consumed
self.assertFalse(self.event.wait(1))
# Resume the replay and wait until we start getting granules again
replay_client.resume_replay()
self.assertTrue(self.event.wait(5))
# Stop the replay, clear the queues
replay_client.stop_replay()
gevent.sleep(1)
subscriber.xn.purge()
self.event.clear()
# Make sure that it did indeed stop
self.assertFalse(self.event.wait(1))
subscriber.stop()
def test_retrieve_and_transform(self):
# Make a simple dataset and start ingestion, pretty standard stuff.
ctd_stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(ctd_stream_id, dataset_id)
# Stream definition for the salinity data
salinity_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
sal_stream_def_id = self.pubsub_management.create_stream_definition('sal data', parameter_dictionary_id=salinity_pdict_id)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(10)
rdt['temp'] = np.random.randn(10) * 10 + 30
rdt['conductivity'] = np.random.randn(10) * 2 + 10
rdt['pressure'] = np.random.randn(10) * 1 + 12
publisher = StandaloneStreamPublisher(ctd_stream_id, route)
publisher.publish(rdt.to_granule())
rdt['time'] = np.arange(10,20)
publisher.publish(rdt.to_granule())
self.wait_until_we_have_enough_granules(dataset_id, 20)
granule = self.data_retriever.retrieve(dataset_id,
None,
None,
'ion.processes.data.transforms.ctd.ctd_L2_salinity',
'CTDL2SalinityTransformAlgorithm',
kwargs=dict(params=sal_stream_def_id))
rdt = RecordDictionaryTool.load_from_granule(granule)
for i in rdt['salinity']:
self.assertNotEquals(i,0)
self.streams.append(ctd_stream_id)
self.stop_ingestion(ctd_stream_id)
def test_last_granule(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
self.publish_hifi(stream_id,route, 0)
self.publish_hifi(stream_id,route, 1)
self.wait_until_we_have_enough_granules(dataset_id,20) # I just need two
success = False
def verifier():
replay_granule = self.data_retriever.retrieve_last_data_points(dataset_id, 10)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(10) + 10
if not isinstance(comp,bool):
return comp.all()
return False
success = poll(verifier)
self.assertTrue(success)
success = False
def verify_points():
replay_granule = self.data_retriever.retrieve_last_data_points(dataset_id,5)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(15,20)
if not isinstance(comp,bool):
return comp.all()
return False
success = poll(verify_points)
self.assertTrue(success)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
def test_replay_with_parameters(self):
#--------------------------------------------------------------------------------
# Create the configurations and the dataset
#--------------------------------------------------------------------------------
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict',id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext('binary', param_type=ArrayType())
context_ids.append(self.dataset_management.create_parameter_context('binary', bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext('records', param_type=RecordType())
context_ids.append(self.dataset_management.create_parameter_context('records', rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary('replay_pdict', parameter_context_ids=context_ids, temporal_context='time')
stream_def_id = self.pubsub_management.create_stream_definition('replay_stream', parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream('replay_with_params', exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id)
config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=config_id, dataset_id=dataset_id)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
self.publish_fake_data(stream_id, route)
self.assertTrue(dataset_monitor.event.wait(30))
query = {
'start_time': 0 - 2208988800,
'end_time': 20 - 2208988800,
'stride_time' : 2,
'parameters': ['time','temp']
}
retrieved_data = self.data_retriever.retrieve(dataset_id=dataset_id,query=query)
rdt = RecordDictionaryTool.load_from_granule(retrieved_data)
comp = np.arange(0,20,2) == rdt['time']
self.assertTrue(comp.all(),'%s' % rdt.pretty_print())
self.assertEquals(set(rdt.iterkeys()), set(['time','temp']))
extents = self.dataset_management.dataset_extents(dataset_id=dataset_id, parameters=['time','temp'])
self.assertTrue(extents['time']>=20)
self.assertTrue(extents['temp']>=20)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
def test_repersist_data(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
self.publish_hifi(stream_id,route,0)
self.publish_hifi(stream_id,route,1)
self.wait_until_we_have_enough_granules(dataset_id,20)
config_id = self.get_ingestion_config()
self.ingestion_management.unpersist_data_stream(stream_id=stream_id,ingestion_configuration_id=config_id)
self.ingestion_management.persist_data_stream(stream_id=stream_id,ingestion_configuration_id=config_id,dataset_id=dataset_id)
self.publish_hifi(stream_id,route,2)
self.publish_hifi(stream_id,route,3)
self.wait_until_we_have_enough_granules(dataset_id,40)
success = False
with gevent.timeout.Timeout(5):
while not success:
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(0,40)
if not isinstance(comp,bool):
success = comp.all()
gevent.sleep(1)
self.assertTrue(success)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Host requires file-system access to coverage files, CEI mode does not support.')
def test_correct_time(self):
# There are 2208988800 seconds between Jan 1 1900 and Jan 1 1970, i.e.
# the conversion factor between unix and NTP time
unix_now = np.floor(time.time())
ntp_now = unix_now + 2208988800
unix_ago = unix_now - 20
ntp_ago = unix_ago + 2208988800
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
coverage = DatasetManagementService._get_simplex_coverage(dataset_id)
coverage.insert_timesteps(20)
coverage.set_parameter_values('time', np.arange(ntp_ago,ntp_now))
temporal_bounds = self.dataset_management.dataset_temporal_bounds(dataset_id)
self.assertTrue( np.abs(temporal_bounds[0] - unix_ago) < 2)
self.assertTrue( np.abs(temporal_bounds[1] - unix_now) < 2)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Host requires file-system access to coverage files, CEI mode does not support.')
def test_empty_coverage_time(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
coverage = DatasetManagementService._get_coverage(dataset_id)
temporal_bounds = self.dataset_management.dataset_temporal_bounds(dataset_id)
self.assertEquals([coverage.get_parameter_context('time').fill_value] *2, temporal_bounds)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Host requires file-system access to coverage files, CEI mode does not support.')
def test_out_of_band_retrieve(self):
# Setup the environemnt
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
# Fill the dataset
self.publish_fake_data(stream_id, route)
self.wait_until_we_have_enough_granules(dataset_id,40)
# Retrieve the data
granule = DataRetrieverService.retrieve_oob(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
self.assertTrue((rdt['time'] == np.arange(40)).all())
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Host requires file-system access to coverage files, CEI mode does not support.')
def test_retrieve_cache(self):
DataRetrieverService._refresh_interval = 1
datasets = [self.make_simple_dataset() for i in xrange(10)]
for stream_id, route, stream_def_id, dataset_id in datasets:
coverage = DatasetManagementService._get_simplex_coverage(dataset_id)
coverage.insert_timesteps(10)
coverage.set_parameter_values('time', np.arange(10))
coverage.set_parameter_values('temp', np.arange(10))
# Verify cache hit and refresh
dataset_ids = [i[3] for i in datasets]
self.assertTrue(dataset_ids[0] not in DataRetrieverService._retrieve_cache)
DataRetrieverService._get_coverage(dataset_ids[0]) # Hit the chache
cov, age = DataRetrieverService._retrieve_cache[dataset_ids[0]]
# Verify that it was hit and it's now in there
self.assertTrue(dataset_ids[0] in DataRetrieverService._retrieve_cache)
gevent.sleep(DataRetrieverService._refresh_interval + 0.2)
DataRetrieverService._get_coverage(dataset_ids[0]) # Hit the chache
cov, age2 = DataRetrieverService._retrieve_cache[dataset_ids[0]]
self.assertTrue(age2 != age)
for dataset_id in dataset_ids:
DataRetrieverService._get_coverage(dataset_id)
self.assertTrue(dataset_ids[0] not in DataRetrieverService._retrieve_cache)
stream_id, route, stream_def, dataset_id = datasets[0]
self.start_ingestion(stream_id, dataset_id)
DataRetrieverService._get_coverage(dataset_id)
self.assertTrue(dataset_id in DataRetrieverService._retrieve_cache)
DataRetrieverService._refresh_interval = 100
self.publish_hifi(stream_id,route,1)
self.wait_until_we_have_enough_granules(dataset_id, data_size=20)
event = gevent.event.Event()
with gevent.Timeout(20):
while not event.wait(0.1):
if dataset_id not in DataRetrieverService._retrieve_cache:
event.set()
self.assertTrue(event.is_set())
def publish_and_wait(self, dataset_id, granule):
stream_ids, _ = self.resource_registry.find_objects(dataset_id, PRED.hasStream,id_only=True)
stream_id=stream_ids[0]
route = self.pubsub_management.read_stream_route(stream_id)
publisher = StandaloneStreamPublisher(stream_id,route)
dataset_monitor = DatasetMonitor(dataset_id)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(10))
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Host requires file-system access to coverage files, CEI mode does not support.')
def test_thorough_gap_analysis(self):
dataset_id = self.test_ingestion_gap_analysis()
vcov = DatasetManagementService._get_coverage(dataset_id)
self.assertIsInstance(vcov,ViewCoverage)
ccov = vcov.reference_coverage
self.assertIsInstance(ccov, ComplexCoverage)
self.assertEquals(len(ccov._reference_covs), 3)
def test_ingestion_gap_analysis(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
self.addCleanup(self.stop_ingestion, stream_id)
connection1 = uuid4().hex
connection2 = uuid4().hex
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [0]
rdt['temp'] = [0]
self.publish_and_wait(dataset_id, rdt.to_granule(connection_id=connection1,connection_index='0'))
rdt['time'] = [1]
rdt['temp'] = [1]
self.publish_and_wait(dataset_id, rdt.to_granule(connection_id=connection1,connection_index=1))
rdt['time'] = [2]
rdt['temp'] = [2]
self.publish_and_wait(dataset_id, rdt.to_granule(connection_id=connection1,connection_index='3')) # Gap, missed message
rdt['time'] = [3]
rdt['temp'] = [3]
self.publish_and_wait(dataset_id, rdt.to_granule(connection_id=connection2,connection_index='3')) # Gap, new connection
rdt['time'] = [4]
rdt['temp'] = [4]
self.publish_and_wait(dataset_id, rdt.to_granule(connection_id=connection2,connection_index='4'))
rdt['time'] = [5]
rdt['temp'] = [5]
self.publish_and_wait(dataset_id, rdt.to_granule(connection_id=connection2,connection_index=5))
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt['time'], np.arange(6))
np.testing.assert_array_equal(rdt['temp'], np.arange(6))
return dataset_id
@unittest.skip('Outdated due to ingestion retry')
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Host requires file-system access to coverage files, CEI mode does not support.')
def test_ingestion_failover(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
event = Event()
def cb(*args, **kwargs):
event.set()
sub = EventSubscriber(event_type="ExceptionEvent", callback=cb, origin="stream_exception")
sub.start()
self.publish_fake_data(stream_id, route)
self.wait_until_we_have_enough_granules(dataset_id, 40)
file_path = DatasetManagementService._get_coverage_path(dataset_id)
master_file = os.path.join(file_path, '%s_master.hdf5' % dataset_id)
with open(master_file, 'w') as f:
f.write('this will crash HDF')
self.publish_hifi(stream_id, route, 5)
self.assertTrue(event.wait(10))
sub.stop()
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Host requires file-system access to coverage files, CEI mode does not support.')
def test_coverage_types(self):
# Make a simple dataset and start ingestion, pretty standard stuff.
ctd_stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
cov = DatasetManagementService._get_coverage(dataset_id=dataset_id)
self.assertIsInstance(cov, ViewCoverage)
cov = DatasetManagementService._get_simplex_coverage(dataset_id=dataset_id)
self.assertIsInstance(cov, SimplexCoverage)
def test_replay_integration(self):
'''
test_replay_integration
'''
import numpy as np
# Keep the import it's used in the vector comparison below even though pycharm says its unused.
cc = self.container
XP = self.XP
assertions = self.assertTrue
### Every thing below here can be run as a script:
log.debug('Got it')
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
datastore_name = 'dm_test_replay_integration'
producer = Publisher(name=(XP,'stream producer'))
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id=XP,
couch_storage=CouchStorage(datastore_name=datastore_name,datastore_profile='SCIDATA'),
hdf_storage=HdfStorage(),
number_of_workers=1
)
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id
)
definition = SBE37_CDM_stream_definition()
data_stream_id = definition.data_stream_id
encoding_id = definition.identifiables[data_stream_id].encoding_id
element_count_id = definition.identifiables[data_stream_id].element_count_id
stream_def_id = pubsub_management_service.create_stream_definition(
container=definition
)
stream_id = pubsub_management_service.create_stream(
stream_definition_id=stream_def_id
)
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/dataset_by_id'
)
ingestion_management_service.create_dataset_configuration(
dataset_id=dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id = ingestion_configuration_id
)
definition.stream_resource_id = stream_id
packet = _create_packet(definition)
input_file = FileSystem.mktemp()
input_file.write(packet.identifiables[data_stream_id].values)
input_file_path = input_file.name
input_file.close()
fields=[
'conductivity',
'height',
'latitude',
'longitude',
'pressure',
'temperature',
'time'
]
input_vectors = acquire_data([input_file_path],fields , 2).next()
producer.publish(msg=packet, to_name=(XP,'%s.data' % stream_id))
replay_id, replay_stream_id = data_retriever_service.define_replay(dataset_id)
ar = gevent.event.AsyncResult()
def sub_listen(msg, headers):
assertions(isinstance(msg,StreamGranuleContainer),'replayed message is not a granule.')
hdf_string = msg.identifiables[data_stream_id].values
sha1 = hashlib.sha1(hdf_string).hexdigest().upper()
assertions(sha1 == msg.identifiables[encoding_id].sha1,'Checksum failed.')
assertions(msg.identifiables[element_count_id].value==1, 'record replay count is incorrect %d.' % msg.identifiables[element_count_id].value)
output_file = FileSystem.mktemp()
output_file.write(msg.identifiables[data_stream_id].values)
output_file_path = output_file.name
output_file.close()
output_vectors = acquire_data([output_file_path],fields,2).next()
for field in fields:
comparison = (input_vectors[field]['values']==output_vectors[field]['values'])
assertions(comparison.all(), 'vector mismatch: %s vs %s' %
(input_vectors[field]['values'],output_vectors[field]['values']))
FileSystem.unlink(output_file_path)
ar.set(True)
subscriber = Subscriber(name=(XP,'replay listener'),callback=sub_listen)
g = gevent.Greenlet(subscriber.listen, binding='%s.data' % replay_stream_id)
g.start()
data_retriever_service.start_replay(replay_id)
ar.get(timeout=10)
FileSystem.unlink(input_file_path)
class TestObservatoryManagementFullIntegration(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.RR = ResourceRegistryServiceClient()
self.RR2 = EnhancedResourceRegistryClient(self.RR)
self.OMS = ObservatoryManagementServiceClient()
self.org_management_service = OrgManagementServiceClient()
self.IMS = InstrumentManagementServiceClient()
self.dpclient = DataProductManagementServiceClient()
self.pubsubcli = PubsubManagementServiceClient()
self.damsclient = DataAcquisitionManagementServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self._load_stage = 0
self._resources = {}
def preload_ooi(self, stage=STAGE_LOAD_ASSETS):
# Preloads OOI up to a given stage
if self._load_stage >= stage:
return
if self._load_stage < STAGE_LOAD_ORGS:
log.info(
"--------------------------------------------------------------------------------------------------------"
)
log.info("Preloading stage: %s (OOIR2 Orgs, users, roles)",
STAGE_LOAD_ORGS)
# load_OOIR2_scenario
self.container.spawn_process("Loader",
"ion.processes.bootstrap.ion_loader",
"IONLoader",
config=dict(
op="load",
scenario="OOIR2",
path="master",
))
self._load_stage = STAGE_LOAD_ORGS
if self._load_stage < STAGE_LOAD_PARAMS:
log.info(
"--------------------------------------------------------------------------------------------------------"
)
log.info("Preloading stage: %s (BASE params, streamdefs)",
STAGE_LOAD_PARAMS)
# load_parameter_scenarios
self.container.spawn_process(
"Loader",
"ion.processes.bootstrap.ion_loader",
"IONLoader",
config=dict(
op="load",
scenario="BETA",
path="master",
categories=
"ParameterFunctions,ParameterDefs,ParameterDictionary,StreamDefinition",
clearcols="owner_id,org_ids",
assets="res/preload/r2_ioc/ooi_assets",
parseooi="True",
))
self._load_stage = STAGE_LOAD_PARAMS
if self._load_stage < STAGE_LOAD_AGENTS:
log.info(
"--------------------------------------------------------------------------------------------------------"
)
log.info("Preloading stage: %s (OOIR2_I agents, model links)",
STAGE_LOAD_AGENTS)
# load_OOIR2_agents
self.container.spawn_process("Loader",
"ion.processes.bootstrap.ion_loader",
"IONLoader",
config=dict(
op="load",
scenario="OOIR2_I",
path="master",
))
self._load_stage = STAGE_LOAD_AGENTS
if self._load_stage < STAGE_LOAD_ASSETS:
log.info(
"--------------------------------------------------------------------------------------------------------"
)
log.info(
"Preloading stage: %s (OOI assets linked to params, agents)",
STAGE_LOAD_ASSETS)
# load_ooi_assets
self.container.spawn_process(
"Loader",
"ion.processes.bootstrap.ion_loader",
"IONLoader",
config=dict(
op="load",
loadooi="True",
path="master",
assets="res/preload/r2_ioc/ooi_assets",
bulk="True",
debug="True",
ooiuntil="9/1/2013",
ooiparams="True",
#excludecategories: DataProduct,DataProductLink,Deployment,Workflow,WorkflowDefinition
))
self._load_stage = STAGE_LOAD_ASSETS
# 'DataProduct,DataProductLink,WorkflowDefinition,ExternalDataProvider,ExternalDatasetModel,ExternalDataset,ExternalDatasetAgent,ExternalDatasetAgentInstance',
@unittest.skip('Work in progress')
def test_observatory(self):
self._load_stage = 0
self._resources = {}
passing = True
self.assertTrue(True)
# LOAD STEP 1
self.preload_ooi(stage=STAGE_LOAD_ORGS)
passing &= self.orguserrole_assertions()
# LOAD STEP 2
self.preload_ooi(stage=STAGE_LOAD_PARAMS)
passing &= self.parameter_assertions()
# LOAD STEP 3
self.preload_ooi(stage=STAGE_LOAD_AGENTS)
passing &= self.agent_assertions()
# LOAD STEP 4
self.preload_ooi(stage=STAGE_LOAD_ASSETS)
# Check OOI preloaded resources to see if they match needs for this test and for correctness
passing &= self.sites_assertions()
passing &= self.device_assertions()
passing &= self.deployment_assertions()
# Extensive tests on select RSN nodes
passing &= self.rsn_node_checks()
# Extensive tests on select RSN instruments
passing &= self.check_rsn_instrument()
passing &= self.check_rsn_instrument_data_product()
# Extensive tests on a glider
#passing &= self.check_glider()
# Extensive tests on a CG assembly
#passing &= self.check_cg_assembly()
# Add a new instrument agent
# Add a new instrument agent instance
# Check DataProducts
# Check Provenance
IonIntegrationTestCase.assertTrue(self, passing)
# -------------------------------------------------------------------------
def orguserrole_assertions(self):
passing = True
passing &= self._check_marine_facility("MF_CGSN")
passing &= self._check_marine_facility("MF_RSN")
passing &= self._check_marine_facility("MF_EA")
return passing
def _check_marine_facility(self, preload_id):
passing = True
log.debug("Checking marine facility %s and associations", preload_id)
mf_obj = self.retrieve_ooi_asset(preload_id)
mf_id = mf_obj._id
self._resources[preload_id] = mf_id
passing &= self.assertEquals(mf_obj.lcstate, LCS.DEPLOYED)
res_list, _ = self.RR.find_objects(subject=mf_id,
predicate=PRED.hasMembership,
id_only=True)
passing &= self.assertTrue(len(res_list) >= 3)
res_list, _ = self.RR.find_objects(subject=mf_id,
predicate=PRED.hasRole,
id_only=False)
passing &= self.assertTrue(len(res_list) >= 5)
passing &= self._check_role_assignments(res_list, "ORG_MANAGER")
passing &= self._check_role_assignments(res_list,
"OBSERVATORY_OPERATOR")
passing &= self._check_role_assignments(res_list,
"INSTRUMENT_OPERATOR")
return passing
def _check_role_assignments(self, role_list, role_name):
passing = True
role_obj = self._find_resource_in_list(role_list, "governance_name",
role_name)
if role_obj:
res_list = self.RR.find_subjects(predicate=PRED.hasRole,
object=role_obj._id,
id_only=True)
passing &= self.assertTrue(len(res_list) >= 1)
return passing
def parameter_assertions(self):
passing = True
pctx_list, _ = self.RR.find_resources_ext(restype=RT.ParameterContext)
passing &= self.assertTrue(len(pctx_list) >= 10)
pdict_list, _ = self.RR.find_resources_ext(
restype=RT.ParameterDictionary)
passing &= self.assertTrue(len(pdict_list) >= 10)
sdef_list, _ = self.RR.find_resources_ext(restype=RT.StreamDefinition)
passing &= self.assertTrue(len(sdef_list) >= 10)
# Verify that a PDict has the appropriate QC parameters defined
pdicts, _ = self.RR.find_resources_ext(restype=RT.ParameterDictionary,
alt_id_ns='PRE',
alt_id='DICT110')
passing &= self.assertTrue(len(pdicts) == 1)
if not pdicts:
return passing
pdict = pdicts[0]
# According to the latest SAF, density should NOT have trend
parameters, _ = self.RR.find_objects(pdict, PRED.hasParameterContext)
names = [i.name for i in parameters if i.name.startswith('density')]
passing &= self.assertTrue('density_trndtst_qc' not in names)
return passing
def agent_assertions(self):
passing = True
# TODO: More tests?
return passing
def sites_assertions(self):
passing = True
observatory_list, _ = self.RR.find_resources_ext(
restype=RT.Observatory)
passing &= self.assertTrue(len(observatory_list) >= 40)
for obs in observatory_list:
passing &= self.assertEquals(obs.lcstate, LCS.DEPLOYED)
platform_site_list, _ = self.RR.find_resources(RT.PlatformSite,
id_only=False)
log.debug('platform sites: %s', [ps.name for ps in platform_site_list])
passing &= self.assertTrue(len(platform_site_list) >= 30)
return passing
def device_assertions(self):
passing = True
platform_device_list, _ = self.RR.find_resources(RT.PlatformDevice,
id_only=False)
passing &= self.assertTrue(len(platform_device_list) >= 30)
for pdev in platform_device_list:
log.debug('platform device: %s', pdev.name)
passing &= self.assertEquals(pdev.lcstate, LCS.PLANNED)
platform_agent_list, _ = self.RR.find_resources(RT.PlatformAgent,
id_only=False)
passing &= self.assertTrue(len(platform_agent_list) >= 2)
for pagent in platform_agent_list:
log.debug('platform agent: %s', pagent.name)
passing &= self.assertEquals(pagent.lcstate, LCS.DEPLOYED)
instrument_agent_list, _ = self.RR.find_resources(RT.InstrumentAgent,
id_only=False)
passing &= self.assertTrue(len(instrument_agent_list) >= 3)
for iagent in instrument_agent_list:
log.debug('instrument agent: %s', iagent.name)
passing &= self.assertEquals(iagent.lcstate, LCS.DEPLOYED)
model_list, _ = self.RR.find_objects(subject=iagent._id,
predicate=PRED.hasModel,
id_only=True)
passing &= self.assertTrue(
len(model_list) >= 1, "IA %s" % iagent.name)
return passing
def deployment_assertions(self):
passing = True
deployment_list, _ = self.RR.find_resources(RT.Deployment,
id_only=False)
passing &= self.assertTrue(len(deployment_list) >= 30)
for deploy in deployment_list:
log.debug('deployment: %s', deploy.name)
passing &= self.assertEquals(deploy.lcstate, LCS.DEPLOYED)
return passing
def rsn_node_checks(self):
"""
Current preload creates:
- PlatformDevice in PLANNED
- PlatformSite in DEPLOYED
- Deployment in DEPLOYED
- Deployment is NOT activated
"""
passing = True
dp_obj = self.retrieve_ooi_asset("CE04OSHY-PN01C_DEP")
passing &= self.assertEquals(dp_obj.lcstate, LCS.DEPLOYED)
passing &= self.assertEquals(dp_obj.availability, AS.AVAILABLE)
log.debug(
'test_observatory retrieve CE04OSHY-PN01C_DEP deployment: %s',
dp_obj)
# Check existing RSN node CE04OSHY-LV01C Deployment (PLANNED lcstate)
CE04OSHY_LV01C_deployment = self.retrieve_ooi_asset(
'CE04OSHY-LV01C_DEP')
passing &= self.assertEquals(CE04OSHY_LV01C_deployment.lcstate,
LCS.DEPLOYED)
passing &= self.assertEquals(CE04OSHY_LV01C_deployment.availability,
AS.AVAILABLE)
#self.dump_deployment(CE04OSHY_LV01C_deployment._id)
log.debug(
'test_observatory retrieve RSN node CE04OSHY-LV01C Deployment: %s',
CE04OSHY_LV01C_deployment)
CE04OSHY_LV01C_device = self.retrieve_ooi_asset('CE04OSHY-LV01C_PD')
# Set CE04OSHY-LV01C device to DEVELOPED state
passing &= self.transition_lcs_then_verify(
resource_id=CE04OSHY_LV01C_device._id,
new_lcs_state=LCE.DEVELOP,
verify=LCS.DEVELOPED)
# Set CE04OSHY-LV01C device to INTEGRATED state
passing &= self.transition_lcs_then_verify(
resource_id=CE04OSHY_LV01C_device._id,
new_lcs_state=LCE.INTEGRATE,
verify=LCS.INTEGRATED)
# Set CE04OSHY-LV01C device to DEPLOYED state
passing &= self.transition_lcs_then_verify(
resource_id=CE04OSHY_LV01C_device._id,
new_lcs_state=LCE.DEPLOY,
verify=LCS.DEPLOYED)
# Set CE04OSHY-LV01C Deployment to DEPLOYED state
# NOTE: Deployments are created in DEPLOYED state, currently
#self.transition_lcs_then_verify(resource_id=CE04OSHY_LV01C_deployment._id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
# Activate Deployment for CE04OSHY-LV01C
self.OMS.activate_deployment(CE04OSHY_LV01C_deployment._id)
log.debug(
'--------- activate_deployment CE04OSHY_LV01C_deployment -------------- '
)
self.dump_deployment(CE04OSHY_LV01C_deployment._id)
passing &= self.validate_deployment_activated(
CE04OSHY_LV01C_deployment._id)
# (optional) Start CE04OSHY-LV01C platform agent with simulator
# NOTE: DataProduct is generated in DEPLOYED state
# # Set DataProduct for CE04OSHY-LV01C platform to DEPLOYED state
# output_data_product_ids, assns =self.RR.find_objects(subject=CE04OSHY_LV01C_device._id, predicate=PRED.hasOutputProduct, id_only=True)
# if output_data_product_ids:
# #self.assertEquals(len(child_devs), 3)
# for output_data_product_id in output_data_product_ids:
# log.debug('DataProduct for CE04OSHY-LV01C platform: %s', output_data_product_id)
# self.transition_lcs_then_verify(resource_id=output_data_product_id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
# Check events for CE04OSHY-LV01C platform
# Check existing CE04OSBP-LJ01C Deployment (PLANNED lcstate)
# dp_list, _ = self.RR.find_resources_ext(alt_id_ns="PRE", alt_id="CE04OSBP-LJ01C_DEP")
# self.assertEquals(len(dp_list), 1)
# CE04OSHY_LV01C_deployment = dp_list[0]
# self.assertEquals(CE04OSHY_LV01C_deployment.lcstate, 'PLANNED')
# log.debug('test_observatory retrieve RSN node CE04OSBP-LJ01C Deployment: %s', CE04OSHY_LV01C_deployment)
# Set CE04OSBP-LJ01C Deployment to DEPLOYED state
# Update description and other attributes for CE04OSBP-LJ01C device resource
# Create attachment (JPG image) for CE04OSBP-LJ01C device resource
# Activate Deployment for CE04OSBP-LJ01C
# (optional) Add/register CE04OSBP-LJ01C platform agent to parent agent
# (optional) Start CE04OSBP-LJ01C platform agent
return passing
def check_rsn_instrument(self):
"""
Check existing RSN instrument CE04OSBP-LJ01C-06-CTDBPO108 Deployment (PLANNED lcstate)
Current preload creates:
- InstrumentDevice in PLANNED
- InstrumentSite in DEPLOYED
- Deployment in DEPLOYED
- Deployment is activated
"""
passing = True
CE04OSBP_LJ01C_06_CTDBPO108_deploy = self.retrieve_ooi_asset(
'CE04OSBP-LJ01C-06-CTDBPO108_DEP')
self.dump_deployment(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
#passing &= self.assertEquals(CE04OSBP_LJ01C_06_CTDBPO108_deploy.lcstate, 'PLANNED')
# Set CE04OSBP-LJ01C-06-CTDBPO108 device to DEVELOPED state
CE04OSBP_LJ01C_06_CTDBPO108_device = self.retrieve_ooi_asset(
'CE04OSBP-LJ01C-06-CTDBPO108_ID')
passing &= self.transition_lcs_then_verify(
resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id,
new_lcs_state=LCE.DEVELOP,
verify='DEVELOPED')
# Set CE04OSBP-LJ01C-06-CTDBPO108 device to INTEGRATED state
passing &= self.transition_lcs_then_verify(
resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id,
new_lcs_state=LCE.INTEGRATE,
verify='INTEGRATED')
# Set CE04OSBP-LJ01C-06-CTDBPO108 device to DEPLOYED state
passing &= self.transition_lcs_then_verify(
resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id,
new_lcs_state=LCE.DEPLOY,
verify='DEPLOYED')
# Set CE04OSBP-LJ01C-06-CTDBPO108 Deployment to DEPLOYED state
#self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_deploy._id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
# Activate Deployment for CE04OSBP-LJ01C-06-CTDBPO108 instrument
log.debug(
'--------- activate_deployment CE04OSBP-LJ01C-06-CTDBPO108 deployment -------------- '
)
self.OMS.activate_deployment(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
passing &= self.validate_deployment_activated(
CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
# (optional) Add/register CE04OSBP-LJ01C-06-CTDBPO108 instrument agent to parent agent
# (optional) Start CE04OSBP-LJ01C-06-CTDBPO108 instrument agent with simulator
# Set all DataProducts for CE04OSBP-LJ01C-06-CTDBPO108 to DEPLOYED state
# (optional) Create a substitute Deployment for site CE04OSBP-LJ01C-06-CTDBPO108 with a comparable device
CE04OSBP_LJ01C_06_CTDBPO108_isite = self.retrieve_ooi_asset(
'CE04OSBP-LJ01C-06-CTDBPO108')
## create device here: retrieve CTD Mooring on Mooring Riser 001 - similiar?
GP03FLMB_RI001_10_CTDMOG999_ID_idevice = self.retrieve_ooi_asset(
'GP03FLMB-RI001-10-CTDMOG999_ID')
deploy_id_2 = self.create_basic_deployment(
name='CE04OSBP-LJ01C-06-CTDBPO108_DEP2',
description=
'substitute Deployment for site CE04OSBP-LJ01C-06-CTDBPO108 with a comparable device'
)
self.OMS.assign_device_to_deployment(
instrument_device_id=GP03FLMB_RI001_10_CTDMOG999_ID_idevice._id,
deployment_id=deploy_id_2)
self.OMS.assign_site_to_deployment(
instrument_site_id=CE04OSBP_LJ01C_06_CTDBPO108_isite._id,
deployment_id=deploy_id_2)
self.dump_deployment(deploy_id_2)
# (optional) Activate this second deployment - check first deployment is deactivated
self.OMS.deactivate_deployment(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
passing &= self.validate_deployment_deactivated(
CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
# log.debug('Activate deployment deploy_id_2')
# self.get_deployment_ids(deploy_id_2)
# self.dump_deployment(deploy_id_2, "deploy_id_2")
# self.OMS.activate_deployment(deploy_id_2)
# passing &= self.validate_deployment_deactivated(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
#
# # (optional) Set first CE04OSBP-LJ01C-06-CTDBPO108 Deployment to INTEGRATED state
# passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_deploy._id, new_lcs_state=LCE.INTEGRATE, verify='INTEGRATED')
#
# # Set first CE04OSBP-LJ01C-06-CTDBPO108 device to INTEGRATED state
# passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id, new_lcs_state=LCE.INTEGRATE, verify='INTEGRATED')
#
#
# # (optional) Create a third Deployment for site CE04OSBP-LJ01C-06-CTDBPO108 with a same device from first deployment
# deploy_id_3 = self.create_basic_deployment(name='CE04OSBP-LJ01C-06-CTDBPO108_DEP3', description='substitute Deployment for site CE04OSBP-LJ01C-06-CTDBPO108 with same device as first')
# self.IMS.deploy_instrument_device(instrument_device_id=GP03FLMB_RI001_10_CTDMOG999_ID_idevice._id, deployment_id=deploy_id_3)
# self.OMS.deploy_instrument_site(instrument_site_id=CE04OSBP_LJ01C_06_CTDBPO108_isite._id, deployment_id=deploy_id_3)
# self.dump_deployment(deploy_id_3)
#
#
# # Set first CE04OSBP-LJ01C-06-CTDBPO108 device to DEPLOYED state
# passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
#
# # (optional) Activate this third deployment - check second deployment is deactivated
# log.debug('Activate deployment deploy_id_3')
# self.dump_deployment(deploy_id_3)
# self.OMS.activate_deployment(deploy_id_3)
# #todo: check second deployment is deactivated
return passing
def check_data_product_reference(self, reference_designator, output=[]):
passing = True
data_product_ids, _ = self.RR.find_resources_ext(
alt_id_ns='PRE',
alt_id='%s_DPI1' % reference_designator,
id_only=True) # Assuming DPI1 is parsed
passing &= self.assertEquals(len(data_product_ids), 1)
if not data_product_ids:
return passing
# Let's go ahead and activate it
data_product_id = data_product_ids[0]
self.dpclient.activate_data_product_persistence(data_product_id)
self.addCleanup(self.dpclient.suspend_data_product_persistence,
data_product_id)
dataset_ids, _ = self.RR.find_objects(data_product_id,
PRED.hasDataset,
id_only=True)
passing &= self.assertEquals(len(dataset_ids), 1)
if not dataset_ids:
return passing
dataset_id = dataset_ids[0]
stream_def_ids, _ = self.RR.find_objects(data_product_id,
PRED.hasStreamDefinition,
id_only=True)
passing &= self.assertEquals(len(dataset_ids), 1)
if not stream_def_ids:
return passing
stream_def_id = stream_def_ids[0]
output.append((data_product_id, stream_def_id, dataset_id))
return passing
def check_tempsf_instrument_data_product(self, reference_designator):
passing = True
info_list = []
passing &= self.check_data_product_reference(reference_designator,
info_list)
if not passing: return passing
data_product_id, stream_def_id, dataset_id = info_list.pop()
now = time.time()
ntp_now = now + 2208988800
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [ntp_now]
rdt['temperature'] = [[
25.3884, 26.9384, 24.3394, 23.3401, 22.9832, 29.4434, 26.9873,
15.2883, 16.3374, 14.5883, 15.7253, 18.4383, 15.3488, 17.2993,
10.2111, 11.5993, 10.9345, 9.4444, 9.9876, 10.9834, 11.0098,
5.3456, 4.2994, 4.3009
]]
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ParameterHelper.publish_rdt_to_data_product(data_product_id, rdt)
passing &= self.assertTrue(dataset_monitor.wait())
if not passing: return passing
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
passing &= self.assert_array_almost_equal(rdt['time'], [ntp_now])
passing &= self.assert_array_almost_equal(rdt['temperature'], [[
25.3884, 26.9384, 24.3394, 23.3401, 22.9832, 29.4434, 26.9873,
15.2883, 16.3374, 14.5883, 15.7253, 18.4383, 15.3488, 17.2993,
10.2111, 11.5993, 10.9345, 9.4444, 9.9876, 10.9834, 11.0098,
5.3456, 4.2994, 4.3009
]])
return passing
def check_trhph_instrument_data_products(self, reference_designator):
passing = True
info_list = []
passing &= self.check_data_product_reference(reference_designator,
info_list)
if not passing:
return passing
data_product_id, stream_def_id, dataset_id = info_list.pop()
pdict = self.RR2.find_parameter_dictionary_of_stream_definition_using_has_parameter_dictionary(
stream_def_id)
passing &= self.assertEquals(pdict.name, 'trhph_sample')
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
# calibration constants
a = 1.98e-9
b = -2.45e-6
c = 9.28e-4
d = -0.0888
e = 0.731
V_s = 1.506
V_c = 0.
T = 11.8
r1 = 0.906
r2 = 4.095
r3 = 4.095
ORP_V = 1.806
Cl = np.nan
offset = 2008
gain = 4.0
# Normally this would be 50 per the DPS but the precision is %4.0f which truncates the values to the nearest 1...
ORP = ((ORP_V * 1000.) - offset) / gain
ntp_now = time.time() + 2208988800
rdt['cc_a'] = [a]
rdt['cc_b'] = [b]
rdt['cc_c'] = [c]
rdt['cc_d'] = [d]
rdt['cc_e'] = [e]
rdt['ref_temp_volts'] = [V_s]
rdt['resistivity_temp_volts'] = [V_c]
rdt['eh_sensor'] = [ORP_V]
rdt['resistivity_5'] = [r1]
rdt['resistivity_x1'] = [r2]
rdt['resistivity_x5'] = [r3]
rdt['cc_offset'] = [offset]
rdt['cc_gain'] = [gain]
rdt['time'] = [ntp_now]
passing &= self.assert_array_almost_equal(rdt['vent_fluid_temperaure'],
[T], 2)
passing &= self.assert_array_almost_equal(
rdt['vent_fluid_chloride_conc'], [Cl], 4)
passing &= self.assert_array_almost_equal(rdt['vent_fluid_orp'], [ORP],
4)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ParameterHelper.publish_rdt_to_data_product(data_product_id, rdt)
passing &= self.assertTrue(dataset_monitor.wait())
if not passing: return passing
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
passing &= self.assert_array_almost_equal(rdt['vent_fluid_temperaure'],
[T], 2)
passing &= self.assert_array_almost_equal(
rdt['vent_fluid_chloride_conc'], [Cl], 4)
passing &= self.assert_array_almost_equal(rdt['vent_fluid_orp'], [ORP],
4)
return passing
def check_vel3d_instrument_data_products(self, reference_designator):
passing = True
info_list = []
passing &= self.check_data_product_reference(reference_designator,
info_list)
if not passing:
return passing
data_product_id, stream_def_id, dataset_id = info_list.pop()
pdict = self.RR2.find_parameter_dictionary_of_stream_definition_using_has_parameter_dictionary(
stream_def_id)
self.assertEquals(pdict.name, 'vel3d_b_sample')
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
lat = 14.6846
lon = -51.044
ts = np.array([
3319563600, 3319567200, 3319570800, 3319574400, 3319578000,
3319581600, 3319585200, 3319588800, 3319592400, 3319596000
],
dtype=np.float)
ve = np.array([-3.2, 0.1, 0., 2.3, -0.1, 5.6, 5.1, 5.8, 8.8, 10.3])
vn = np.array([18.2, 9.9, 12., 6.6, 7.4, 3.4, -2.6, 0.2, -1.5, 4.1])
vu = np.array([-1.1, -0.6, -1.4, -2, -1.7, -2, 1.3, -1.6, -1.1, -4.5])
ve_expected = np.array([
-0.085136, -0.028752, -0.036007, 0.002136, -0.023158, 0.043218,
0.056451, 0.054727, 0.088446, 0.085952
])
vn_expected = np.array([
0.164012, 0.094738, 0.114471, 0.06986, 0.07029, 0.049237,
-0.009499, 0.019311, 0.012096, 0.070017
])
vu_expected = np.array([
-0.011, -0.006, -0.014, -0.02, -0.017, -0.02, 0.013, -0.016,
-0.011, -0.045
])
rdt['time'] = ts
rdt['lat'] = [lat] * 10
rdt['lon'] = [lon] * 10
rdt['turbulent_velocity_east'] = ve
rdt['turbulent_velocity_north'] = vn
rdt['turbulent_velocity_up'] = vu
passing &= self.assert_array_almost_equal(
rdt['eastward_turbulent_velocity'], ve_expected)
passing &= self.assert_array_almost_equal(
rdt['northward_turbulent_velocity'], vn_expected)
passing &= self.assert_array_almost_equal(
rdt['upward_turbulent_velocity'], vu_expected)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ParameterHelper.publish_rdt_to_data_product(data_product_id, rdt)
passing &= self.assertTrue(dataset_monitor.wait())
if not passing: return passing
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
passing &= self.assert_array_almost_equal(
rdt['eastward_turbulent_velocity'], ve_expected)
passing &= self.assert_array_almost_equal(
rdt['northward_turbulent_velocity'], vn_expected)
passing &= self.assert_array_almost_equal(
rdt['upward_turbulent_velocity'], vu_expected)
return passing
def check_presta_instrument_data_products(self, reference_designator):
# Check the parsed data product make sure it's got everything it needs and can be published persisted etc.
# Absolute Pressure (SFLPRES_L0) is what comes off the instrumnet, SFLPRES_L1 is a pfunc
# Let's go ahead and publish some fake data!!!
# According to https://alfresco.oceanobservatories.org/alfresco/d/d/workspace/SpacesStore/63e16865-9d9e-4b11-b0b3-d5658faa5080/1341-00230_Data_Product_Spec_SFLPRES_OOI.pdf
# Appendix A. Example 1.
# p_psia_tide = 14.8670
# the tide should be 10.2504
passing = True
info_list = []
passing &= self.check_data_product_reference(reference_designator,
info_list)
if not passing:
return passing
data_product_id, stream_def_id, dataset_id = info_list.pop()
now = time.time()
ntp_now = now + 2208988800.
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [ntp_now]
rdt['absolute_pressure'] = [14.8670]
passing &= self.assert_array_almost_equal(rdt['seafloor_pressure'],
[10.2504], 4)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ParameterHelper.publish_rdt_to_data_product(data_product_id, rdt)
self.assertTrue(
dataset_monitor.wait()) # Bumped to 20 to keep buildbot happy
if not passing: return passing
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
passing &= self.assert_array_almost_equal(rdt['time'], [ntp_now])
passing &= self.assert_array_almost_equal(rdt['seafloor_pressure'],
[10.2504], 4)
passing &= self.assert_array_almost_equal(rdt['absolute_pressure'],
[14.8670], 4)
return passing
def check_rsn_instrument_data_product(self):
passing = True
# for RS03AXBS-MJ03A-06-PRESTA301 (PREST-A) there are a few listed data products
# Parsed, Engineering
# SFLPRES-0 SFLPRES-1
# Check for the two data products and make sure they have the proper parameters
# SFLPRES-0 should
data_products, _ = self.RR.find_resources_ext(
alt_id_ns='PRE',
alt_id='RS03AXBS-MJ03A-06-PRESTA301_SFLPRES_L0_DPID',
id_only=True)
passing &= self.assertTrue(len(data_products) == 1)
if not data_products:
return passing
data_product_id = data_products[0]
stream_defs, _ = self.RR.find_objects(data_product_id,
PRED.hasStreamDefinition,
id_only=False)
passing &= self.assertTrue(len(stream_defs) == 1)
if not stream_defs:
return passing
# Assert that the stream definition has the correct reference designator
stream_def = stream_defs[0]
passing &= self.assertEquals(
stream_def.stream_configuration['reference_designator'],
'RS03AXBS-MJ03A-06-PRESTA301')
# Get the pdict and make sure that the parameters corresponding to the available fields
# begin with the appropriate data product identifier
pdict_ids, _ = self.RR.find_objects(stream_def,
PRED.hasParameterDictionary,
id_only=True)
passing &= self.assertEquals(len(pdict_ids), 1)
if not pdict_ids:
return passing
pdict_id = pdict_ids[0]
pdict = DatasetManagementService.get_parameter_dictionary(pdict_id)
available_params = [
pdict.get_context(i) for i in pdict.keys()
if i in stream_def.available_fields
]
for p in available_params:
if p.name == 'time': # Ignore the domain parameter
continue
passing &= self.assertTrue(p.ooi_short_name.startswith('SFLPRES'))
passing &= self.check_presta_instrument_data_products(
'RS01SLBS-MJ01A-06-PRESTA101')
passing &= self.check_vel3d_instrument_data_products(
'RS01SLBS-MJ01A-12-VEL3DB101')
passing &= self.check_presta_instrument_data_products(
'RS03AXBS-MJ03A-06-PRESTA301')
passing &= self.check_vel3d_instrument_data_products(
'RS03AXBS-MJ03A-12-VEL3DB301')
passing &= self.check_tempsf_instrument_data_product(
'RS03ASHS-MJ03B-07-TMPSFA301')
passing &= self.check_vel3d_instrument_data_products(
'RS03INT2-MJ03D-12-VEL3DB304')
passing &= self.check_trhph_instrument_data_products(
'RS03INT1-MJ03C-10-TRHPHA301')
self.data_product_management.activate_data_product_persistence(
data_product_id)
dataset_id = self.RR2.find_dataset_id_of_data_product_using_has_dataset(
data_product_id)
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
self.assert_array_almost_equal(rdt['seafloor_pressure'], [10.2504], 4)
self.assert_array_almost_equal(rdt['absolute_pressure'], [14.8670], 4)
self.data_product_management.suspend_data_product_persistence(
data_product_id) # Should do nothing and not raise anything
return passing
def check_glider(self):
'''
# Check that glider GP05MOAS-GL001 assembly is defined by OOI preload (3 instruments)
'''
passing = True
GP05MOAS_GL001_device = self.retrieve_ooi_asset('GP05MOAS-GL001_PD')
child_devs, assns = self.RR.find_objects(
subject=GP05MOAS_GL001_device._id,
predicate=PRED.hasDevice,
id_only=True)
passing &= self.assertEquals(len(child_devs), 3)
# Set GP05MOAS-GL001 Deployment to DEPLOYED
GP05MOAS_GL001_deploy = self.retrieve_ooi_asset('GP05MOAS-GL001_DEP')
passing &= self.transition_lcs_then_verify(
resource_id=GP05MOAS_GL001_deploy._id,
new_lcs_state=LCE.DEPLOY,
verify='DEPLOYED')
# Activate Deployment for GP05MOAS-GL001
#self.OMS.activate_deployment(GP05MOAS_GL001_deploy._id)
# Deactivate Deployment for GP05MOAS-GL001
#self.OMS.deactivate_deployment(GP05MOAS_GL001_deploy._id)
# Create a new Deployment resource X without any assignment
x_deploy_id = self.create_basic_deployment(
name='X_Deployment',
description='new Deployment resource X without any assignment')
# Assign Deployment X to site GP05MOAS-GL001
GP05MOAS_GL001_psite = self.retrieve_ooi_asset('GP05MOAS-GL001')
self.OMS.assign_site_to_deployment(GP05MOAS_GL001_psite._id,
x_deploy_id)
# Assign Deployment X to first device for GP05MOAS-GL001
GP05MOAS_GL001_device = self.retrieve_ooi_asset('GP05MOAS-GL001_PD')
self.OMS.assign_device_to_deployment(GP05MOAS_GL001_device._id,
x_deploy_id)
# Set GP05MOAS-GL001 Deployment to PLANNED state
#self.transition_lcs_then_verify(resource_id=x_deploy_id, new_lcs_state=LCE.PLAN, verify='PLANNED')
# ??? already in planned
# Set second GP05MOAS-GL001 Deployment to DEPLOYED
passing &= self.transition_lcs_then_verify(resource_id=x_deploy_id,
new_lcs_state=LCE.DEPLOY,
verify='DEPLOYED')
self.dump_deployment(x_deploy_id)
# Activate second Deployment for GP05MOAS-GL001
#self.OMS.activate_deployment(x_deploy_id)
# Deactivate second Deployment for GP05MOAS-GL001
#self.OMS.deactivate_deployment(x_deploy_id)
return passing
def check_cg_assembly(self):
passing = True
# Set several CE01ISSM-RI002-* instrument devices to DEVELOPED state
# Assemble several CE01ISSM-RI002-* instruments to a CG CE01ISSM-RI002 component platform
# Set several CE01ISSM-RI002-* instrument devices to INTEGRATED state
# Assemble CE01ISSM-RI002 platform to CG CE01ISSM-LM001 station platform
# Set CE01ISSM-RI002 component device to INTEGRATED state
# Set CE01ISSM-LM001 station device to INTEGRATED state
# Set CE01ISSM-LM001 station device to DEPLOYED state (children maybe too?)
# Set CE01ISSM-LM001 Deployment to DEPLOYED
# Activate CE01ISSM-LM001 platform assembly deployment
# Dectivate CE01ISSM-LM001 platform assembly deployment
# Set CE01ISSM-LM001 Deployment to INTEGRATED state
# Set CE01ISSM-LM001 station device to INTEGRATED state
# Set CE01ISSM-RI002 component device to INTEGRATED state
# Set CE01ISSM-RI002 component device to INTEGRATED state
# Disassemble CE01ISSM-RI002 platform from CG CE01ISSM-LM001 station platform
# Disassemble all CE01ISSM-RI002-* instruments from a CG CE01ISSM-RI002 component platform
# Retire instrument one for CE01ISSM-RI002-*
# Retire device one for CE01ISSM-RI002
# Retire device one for CE01ISSM-LM001
return passing
# -------------------------------------------------------------------------
def retrieve_ooi_asset(self, alt_id='', namespace='PRE'):
dp_list, _ = self.RR.find_resources_ext(alt_id_ns=namespace,
alt_id=alt_id)
self.assertEquals(len(dp_list), 1)
return dp_list[0]
def transition_lcs_then_verify(self, resource_id, new_lcs_state, verify):
ret = self.RR2.advance_lcs(resource_id, new_lcs_state)
resource_obj = self.RR.read(resource_id)
return self.assertEquals(resource_obj.lcstate, verify)
def create_basic_deployment(self, name='', description=''):
start = IonTime(datetime.datetime(2013, 1, 1))
end = IonTime(datetime.datetime(2014, 1, 1))
temporal_bounds = IonObject(OT.TemporalBounds,
name='planned',
start_datetime=start.to_string(),
end_datetime=end.to_string())
deployment_obj = IonObject(RT.Deployment,
name=name,
description=description,
context=IonObject(
OT.CabledNodeDeploymentContext),
constraint_list=[temporal_bounds])
return self.OMS.create_deployment(deployment_obj)
def validate_deployment_activated(self, deployment_id=''):
site_id, device_id = self.get_deployment_ids(deployment_id)
assocs = self.RR.find_associations(subject=site_id,
predicate=PRED.hasDevice,
object=device_id)
return self.assertEquals(len(assocs), 1)
def validate_deployment_deactivated(self, deployment_id=''):
site_id, device_id = self.get_deployment_ids(deployment_id)
assocs = self.RR.find_associations(subject=site_id,
predicate=PRED.hasDevice,
object=device_id)
return self.assertEquals(len(assocs), 0)
def dump_deployment(self, deployment_id='', name=""):
#site_id, device_id = self.get_deployment_ids(deployment_id)
resource_list, _ = self.RR.find_subjects(predicate=PRED.hasDeployment,
object=deployment_id,
id_only=True)
resource_list.append(deployment_id)
resources = self.RR.read_mult(resource_list)
log.debug('--------- dump_deployment %s summary---------------',
name)
for resource in resources:
log.debug('%s: %s (%s)', resource._get_type(), resource.name,
resource._id)
log.debug('--------- dump_deployment %s full dump ---------------',
name)
for resource in resources:
log.debug('resource: %s ', resource)
log.debug('--------- dump_deployment %s end ---------------', name)
#assocs = self.container.resource_registry.find_assoctiations(anyside=deployment_id)
# assocs = Container.instance.resource_registry.find_assoctiations(anyside=deployment_id)
# log.debug('--------- dump_deployment ---------------')
# for assoc in assocs:
# log.debug('SUBJECT: %s PREDICATE: %s OBJET: %s', assoc.s, assoc.p, assoc.o)
# log.debug('--------- dump_deployment end ---------------')
def get_deployment_ids(self, deployment_id=''):
devices = []
sites = []
idevice_list, _ = self.RR.find_subjects(RT.InstrumentDevice,
PRED.hasDeployment,
deployment_id,
id_only=True)
pdevice_list, _ = self.RR.find_subjects(RT.PlatformDevice,
PRED.hasDeployment,
deployment_id,
id_only=True)
devices = idevice_list + pdevice_list
self.assertEquals(1, len(devices))
isite_list, _ = self.RR.find_subjects(RT.InstrumentSite,
PRED.hasDeployment,
deployment_id,
id_only=True)
psite_list, _ = self.RR.find_subjects(RT.PlatformSite,
PRED.hasDeployment,
deployment_id,
id_only=True)
sites = isite_list + psite_list
self.assertEquals(1, len(sites))
return sites[0], devices[0]
def _find_resource_in_list(self,
res_list,
attr,
attr_val,
assert_found=True):
for res in res_list:
v = getattr(res, attr, None)
if v == attr_val:
return res
if assert_found:
self.assertTrue(
False,
"Attribute %s value %s not found in list" % (attr, attr_val))
return None
# -------------------------------------------------------------------------
def _get_caller(self):
s = inspect.stack()
return "%s:%s" % (s[2][1], s[2][2])
@assertion_wrapper
def assert_array_almost_equal(self, *args, **kwargs):
np.testing.assert_array_almost_equal(*args, **kwargs)
@assertion_wrapper
def assertEquals(self, *args, **kwargs):
IonIntegrationTestCase.assertEquals(self, *args, **kwargs)
@assertion_wrapper
def assertTrue(self, *args, **kwargs):
IonIntegrationTestCase.assertTrue(self, *args, **kwargs)
class TestDataProductManagementServiceIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
#print 'instantiating container'
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dpsc_cli = DataProductManagementServiceClient()
self.rrclient = ResourceRegistryServiceClient()
self.damsclient = DataAcquisitionManagementServiceClient()
self.pubsubcli = PubsubManagementServiceClient()
self.ingestclient = IngestionManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.unsc = UserNotificationServiceClient()
self.data_retriever = DataRetrieverServiceClient()
#------------------------------------------
# Create the environment
#------------------------------------------
self.stream_def_id = self.pubsubcli.create_stream_definition(
name='SBE37_CDM')
self.process_definitions = {}
ingestion_worker_definition = ProcessDefinition(
name='ingestion worker')
ingestion_worker_definition.executable = {
'module':
'ion.processes.data.ingestion.science_granule_ingestion_worker',
'class': 'ScienceGranuleIngestionWorker'
}
process_definition_id = self.process_dispatcher.create_process_definition(
process_definition=ingestion_worker_definition)
self.process_definitions['ingestion_worker'] = process_definition_id
self.pids = []
self.exchange_points = []
self.exchange_names = []
#------------------------------------------------------------------------------------------------
# First launch the ingestors
#------------------------------------------------------------------------------------------------
self.exchange_space = 'science_granule_ingestion'
self.exchange_point = 'science_data'
config = DotDict()
config.process.datastore_name = 'datasets'
config.process.queue_name = self.exchange_space
self.exchange_names.append(self.exchange_space)
self.exchange_points.append(self.exchange_point)
pid = self.process_dispatcher.schedule_process(
self.process_definitions['ingestion_worker'], configuration=config)
log.debug("the ingestion worker process id: %s", pid)
self.pids.append(pid)
self.addCleanup(self.cleaning_up)
def cleaning_up(self):
for pid in self.pids:
log.debug("number of pids to be terminated: %s", len(self.pids))
try:
self.process_dispatcher.cancel_process(pid)
log.debug("Terminated the process: %s", pid)
except:
log.debug("could not terminate the process id: %s" % pid)
IngestionManagementIntTest.clean_subscriptions()
for xn in self.exchange_names:
xni = self.container.ex_manager.create_xn_queue(xn)
xni.delete()
for xp in self.exchange_points:
xpi = self.container.ex_manager.create_xp(xp)
xpi.delete()
def get_datastore(self, dataset_id):
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(
datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
@attr('EXT')
@attr('PREP')
def test_create_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
parameter_dictionary = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict')
ctd_stream_def_id = self.pubsubcli.create_stream_definition(
name='Simulated CTD data',
parameter_dictionary_id=parameter_dictionary._id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp')
dp_obj.geospatial_bounds.geospatial_latitude_limit_north = 10.0
dp_obj.geospatial_bounds.geospatial_latitude_limit_south = -10.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_east = 10.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_west = -10.0
dp_obj.ooi_product_name = "PRODNAME"
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product(
data_product=dp_obj, stream_definition_id=ctd_stream_def_id)
# Assert that the data product has an associated stream at this stage
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream,
RT.Stream, True)
self.assertNotEquals(len(stream_ids), 0)
# Assert that the data product has an associated stream def at this stage
stream_ids, _ = self.rrclient.find_objects(dp_id,
PRED.hasStreamDefinition,
RT.StreamDefinition, True)
self.assertNotEquals(len(stream_ids), 0)
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
self.assertEquals(dp_obj.geospatial_point_center.lat, 0.0)
log.debug('Created data product %s', dp_obj)
#------------------------------------------------------------------------------------------------
# test creating a new data product with a stream definition
#------------------------------------------------------------------------------------------------
log.debug('Creating new data product with a stream definition')
dp_obj = IonObject(RT.DataProduct,
name='DP2',
description='some new dp')
dp_id2 = self.dpsc_cli.create_data_product(dp_obj, ctd_stream_def_id)
self.dpsc_cli.activate_data_product_persistence(dp_id2)
log.debug('new dp_id = %s' % dp_id2)
#------------------------------------------------------------------------------------------------
#make sure data product is associated with stream def
#------------------------------------------------------------------------------------------------
streamdefs = []
streams, _ = self.rrclient.find_objects(dp_id2, PRED.hasStream,
RT.Stream, True)
for s in streams:
log.debug("Checking stream %s" % s)
sdefs, _ = self.rrclient.find_objects(s, PRED.hasStreamDefinition,
RT.StreamDefinition, True)
for sd in sdefs:
log.debug("Checking streamdef %s" % sd)
streamdefs.append(sd)
self.assertIn(ctd_stream_def_id, streamdefs)
group_names = self.dpsc_cli.get_data_product_group_list()
self.assertIn("PRODNAME", group_names)
# test reading a non-existent data product
log.debug('reading non-existent data product')
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product('some_fake_id')
# update a data product (tests read also)
log.debug('Updating data product')
# first get the existing dp object
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# now tweak the object
dp_obj.description = 'the very first dp'
dp_obj.geospatial_bounds.geospatial_latitude_limit_north = 20.0
dp_obj.geospatial_bounds.geospatial_latitude_limit_south = -20.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_east = 20.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_west = -20.0
# now write the dp back to the registry
update_result = self.dpsc_cli.update_data_product(dp_obj)
# now get the dp back to see if it was updated
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertEquals(dp_obj.description, 'the very first dp')
self.assertEquals(dp_obj.geospatial_point_center.lat, 0.0)
log.debug('Updated data product %s', dp_obj)
#test extension
extended_product = self.dpsc_cli.get_data_product_extension(dp_id)
self.assertEqual(dp_id, extended_product._id)
self.assertEqual(
ComputedValueAvailability.PROVIDED,
extended_product.computed.product_download_size_estimated.status)
self.assertEqual(
0, extended_product.computed.product_download_size_estimated.value)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.parameters.status)
#log.debug("test_create_data_product: parameters %s" % extended_product.computed.parameters.value)
def ion_object_encoder(obj):
return obj.__dict__
#test prepare for create
data_product_data = self.dpsc_cli.prepare_data_product_support()
#print simplejson.dumps(data_product_data, default=ion_object_encoder, indent= 2)
self.assertEqual(data_product_data._id, "")
self.assertEqual(data_product_data.type_, OT.DataProductPrepareSupport)
self.assertEqual(
len(data_product_data.associations['StreamDefinition'].resources),
2)
self.assertEqual(
len(data_product_data.associations['Dataset'].resources), 0)
self.assertEqual(
len(data_product_data.associations['StreamDefinition'].
associated_resources), 0)
self.assertEqual(
len(data_product_data.associations['Dataset'].associated_resources
), 0)
#test prepare for update
data_product_data = self.dpsc_cli.prepare_data_product_support(dp_id)
#print simplejson.dumps(data_product_data, default=ion_object_encoder, indent= 2)
self.assertEqual(data_product_data._id, dp_id)
self.assertEqual(data_product_data.type_, OT.DataProductPrepareSupport)
self.assertEqual(
len(data_product_data.associations['StreamDefinition'].resources),
2)
self.assertEqual(
len(data_product_data.associations['Dataset'].resources), 1)
self.assertEqual(
len(data_product_data.associations['StreamDefinition'].
associated_resources), 1)
self.assertEqual(
data_product_data.associations['StreamDefinition'].
associated_resources[0].s, dp_id)
self.assertEqual(
len(data_product_data.associations['Dataset'].associated_resources
), 1)
self.assertEqual(
data_product_data.associations['Dataset'].associated_resources[0].
s, dp_id)
# now 'delete' the data product
log.debug("deleting data product: %s" % dp_id)
self.dpsc_cli.delete_data_product(dp_id)
# Assert that there are no associated streams leftover after deleting the data product
stream_ids, assoc_ids = self.rrclient.find_objects(
dp_id, PRED.hasStream, RT.Stream, True)
self.assertEquals(len(stream_ids), 0)
self.assertEquals(len(assoc_ids), 0)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# Get the events corresponding to the data product
ret = self.unsc.get_recent_events(resource_id=dp_id)
events = ret.value
for event in events:
log.debug("event time: %s" % event.ts_created)
self.assertTrue(len(events) > 0)
def test_data_product_stream_def(self):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(
name='Simulated CTD data', parameter_dictionary_id=pdict_id)
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp')
dp_id = self.dpsc_cli.create_data_product(
data_product=dp_obj, stream_definition_id=ctd_stream_def_id)
stream_def_id = self.dpsc_cli.get_data_product_stream_definition(dp_id)
self.assertEquals(ctd_stream_def_id, stream_def_id)
def test_derived_data_product(self):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(
name='ctd parsed', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsubcli.delete_stream_definition,
ctd_stream_def_id)
dp = DataProduct(name='Instrument DP')
dp_id = self.dpsc_cli.create_data_product(
dp, stream_definition_id=ctd_stream_def_id)
self.addCleanup(self.dpsc_cli.force_delete_data_product, dp_id)
self.dpsc_cli.activate_data_product_persistence(dp_id)
self.addCleanup(self.dpsc_cli.suspend_data_product_persistence, dp_id)
dataset_ids, _ = self.rrclient.find_objects(subject=dp_id,
predicate=PRED.hasDataset,
id_only=True)
if not dataset_ids:
raise NotFound("Data Product %s dataset does not exist" %
str(dp_id))
dataset_id = dataset_ids[0]
# Make the derived data product
simple_stream_def_id = self.pubsubcli.create_stream_definition(
name='TEMPWAT stream def',
parameter_dictionary_id=pdict_id,
available_fields=['time', 'temp'])
tempwat_dp = DataProduct(name='TEMPWAT',
category=DataProductTypeEnum.DERIVED)
tempwat_dp_id = self.dpsc_cli.create_data_product(
tempwat_dp,
stream_definition_id=simple_stream_def_id,
parent_data_product_id=dp_id)
self.addCleanup(self.dpsc_cli.delete_data_product, tempwat_dp_id)
# Check that the streams associated with the data product are persisted with
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream,
RT.Stream, True)
for stream_id in stream_ids:
self.assertTrue(self.ingestclient.is_persisted(stream_id))
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
rdt = RecordDictionaryTool(stream_definition_id=ctd_stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = np.arange(20)
rdt['pressure'] = np.arange(20)
publisher = StandaloneStreamPublisher(stream_id, route)
dataset_modified = Event()
def cb(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified,
callback=cb,
origin=dataset_id,
auto_delete=True)
es.start()
self.addCleanup(es.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
tempwat_dataset_ids, _ = self.rrclient.find_objects(tempwat_dp_id,
PRED.hasDataset,
id_only=True)
tempwat_dataset_id = tempwat_dataset_ids[0]
granule = self.data_retriever.retrieve(
tempwat_dataset_id, delivery_format=simple_stream_def_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt['time'], np.arange(20))
self.assertEquals(set(rdt.fields), set(['time', 'temp']))
def test_activate_suspend_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(
name='Simulated CTD data', parameter_dictionary_id=pdict_id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
# Construct temporal and spatial Coordinate Reference System objects
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp')
log.debug("Created an IonObject for a data product: %s" % dp_obj)
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product(
data_product=dp_obj, stream_definition_id=ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# Subscribe to persist events
#------------------------------------------------------------------------------------------------
queue = gevent.queue.Queue()
def info_event_received(message, headers):
queue.put(message)
es = EventSubscriber(event_type=OT.InformationContentStatusEvent,
callback=info_event_received,
origin=dp_id,
auto_delete=True)
es.start()
self.addCleanup(es.stop)
#------------------------------------------------------------------------------------------------
# test activate and suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
dataset_ids, _ = self.rrclient.find_objects(subject=dp_id,
predicate=PRED.hasDataset,
id_only=True)
if not dataset_ids:
raise NotFound("Data Product %s dataset does not exist" %
str(dp_id))
dataset_id = dataset_ids[0]
# Check that the streams associated with the data product are persisted with
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream,
RT.Stream, True)
for stream_id in stream_ids:
self.assertTrue(self.ingestclient.is_persisted(stream_id))
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
rdt = RecordDictionaryTool(stream_definition_id=ctd_stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = np.arange(20)
publisher = StandaloneStreamPublisher(stream_id, route)
dataset_modified = Event()
def cb(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified,
callback=cb,
origin=dataset_id,
auto_delete=True)
es.start()
self.addCleanup(es.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_ids[0])
self.assertIsInstance(replay_data, Granule)
log.debug(
"The data retriever was able to replay the dataset that was attached to the data product "
"we wanted to be persisted. Therefore the data product was indeed persisted with "
"otherwise we could not have retrieved its dataset using the data retriever. Therefore "
"this demonstration shows that L4-CI-SA-RQ-267 is satisfied: 'Data product management shall persist data products'"
)
data_product_object = self.rrclient.read(dp_id)
self.assertEquals(data_product_object.name, 'DP1')
self.assertEquals(data_product_object.description, 'some new dp')
log.debug(
"Towards L4-CI-SA-RQ-308: 'Data product management shall persist data product metadata'. "
" Attributes in create for the data product obj, name= '%s', description='%s', match those of object from the "
"resource registry, name='%s', desc='%s'" %
(dp_obj.name, dp_obj.description, data_product_object.name,
data_product_object.description))
#------------------------------------------------------------------------------------------------
# test suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.suspend_data_product_persistence(dp_id)
dataset_modified.clear()
rdt['time'] = np.arange(20, 40)
publisher.publish(rdt.to_granule())
self.assertFalse(dataset_modified.wait(2))
self.dpsc_cli.activate_data_product_persistence(dp_id)
dataset_modified.clear()
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_almost_equal(rdt['time'], np.arange(40))
dataset_ids, _ = self.rrclient.find_objects(dp_id,
PRED.hasDataset,
id_only=True)
self.assertEquals(len(dataset_ids), 1)
self.dpsc_cli.suspend_data_product_persistence(dp_id)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.rrclient.read(dp_id)
info_event_counter = 0
runtime = 0
starttime = time.time()
caught_events = []
#check that the four InfoStatusEvents were received
while info_event_counter < 4 and runtime < 60:
a = queue.get(timeout=60)
caught_events.append(a)
info_event_counter += 1
runtime = time.time() - starttime
self.assertEquals(info_event_counter, 4)
def test_usgs_integration(self):
'''
test_usgs_integration
Test full DM Services Integration using usgs
'''
cc = self.container
assertions = self.assertTrue
#-----------------------------
# Copy below here
#-----------------------------
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
transform_management_service = TransformManagementServiceClient(node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
process_list = []
datasets = []
datastore_name = 'test_usgs_integration'
#---------------------------
# Set up ingestion
#---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug('Calling create_ingestion_configuration')
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name,datastore_profile='SCIDATA'),
number_of_workers=8
)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
usgs_stream_def = USGS_stream_definition()
stream_def_id = pubsub_management_service.create_stream_definition(container=usgs_stream_def, name='Junk definition')
#---------------------------
# Set up the producers (CTD Simulators)
#---------------------------
# Launch five simulated CTD producers
for iteration in xrange(2):
# Make a stream to output on
stream_id = pubsub_management_service.create_stream(stream_definition_id=stream_def_id)
#---------------------------
# Set up the datasets
#---------------------------
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule'
)
# Keep track of the datasets
datasets.append(dataset_id)
stream_policy_id = ingestion_management_service.create_dataset_configuration(
dataset_id = dataset_id,
archive_data = True,
archive_metadata = True,
ingestion_configuration_id = ingestion_configuration_id
)
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module':'eoi.agent.handler.usgs_stream_publisher',
'class':'UsgsPublisher'
}
configuration = {
'process':{
'stream_id':stream_id,
}
}
procdef_id = process_dispatcher.create_process_definition(process_definition=producer_definition)
log.debug('LUKE_DEBUG: procdef_id: %s', procdef_id)
pid = process_dispatcher.schedule_process(process_definition_id=procdef_id, configuration=configuration)
# Keep track, we'll kill 'em later.
process_list.append(pid)
# Get about 4 seconds of data
time.sleep(4)
#---------------------------
# Stop producing data
#---------------------------
for process in process_list:
process_dispatcher.cancel_process(process)
#----------------------------------------------
# The replay and the transform, a love story.
#----------------------------------------------
# Happy Valentines to the clever coder who catches the above!
transform_definition = ProcessDefinition()
transform_definition.executable = {
'module':'ion.processes.data.transforms.transform_example',
'class':'TransformCapture'
}
transform_definition_id = process_dispatcher.create_process_definition(process_definition=transform_definition)
dataset_id = datasets.pop() # Just need one for now
replay_id, stream_id = data_retriever_service.define_replay(dataset_id=dataset_id)
#--------------------------------------------
# I'm Selling magazine subscriptions here!
#--------------------------------------------
subscription = pubsub_management_service.create_subscription(query=StreamQuery(stream_ids=[stream_id]),
exchange_name='transform_capture_point')
#--------------------------------------------
# Start the transform (capture)
#--------------------------------------------
transform_id = transform_management_service.create_transform(
name='capture_transform',
in_subscription_id=subscription,
process_definition_id=transform_definition_id
)
transform_management_service.activate_transform(transform_id=transform_id)
#--------------------------------------------
# BEGIN REPLAY!
#--------------------------------------------
data_retriever_service.start_replay(replay_id=replay_id)
#--------------------------------------------
# Lets get some boundaries
#--------------------------------------------
bounds = dataset_management_service.get_dataset_bounds(dataset_id=dataset_id)
class TestDataProductManagementServiceIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
#print 'instantiating container'
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dpsc_cli = DataProductManagementServiceClient()
self.rrclient = ResourceRegistryServiceClient()
self.damsclient = DataAcquisitionManagementServiceClient()
self.pubsubcli = PubsubManagementServiceClient()
self.ingestclient = IngestionManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.unsc = UserNotificationServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.identcli = IdentityManagementServiceClient()
#------------------------------------------
# Create the environment
#------------------------------------------
self.stream_def_id = self.pubsubcli.create_stream_definition(name='SBE37_CDM')
self.process_definitions = {}
ingestion_worker_definition = ProcessDefinition(name='ingestion worker')
ingestion_worker_definition.executable = {
'module':'ion.processes.data.ingestion.science_granule_ingestion_worker',
'class' :'ScienceGranuleIngestionWorker'
}
process_definition_id = self.process_dispatcher.create_process_definition(process_definition=ingestion_worker_definition)
self.process_definitions['ingestion_worker'] = process_definition_id
self.pids = []
self.exchange_points = []
self.exchange_names = []
#------------------------------------------------------------------------------------------------
# First launch the ingestors
#------------------------------------------------------------------------------------------------
self.exchange_space = 'science_granule_ingestion'
self.exchange_point = 'science_data'
config = DotDict()
config.process.datastore_name = 'datasets'
config.process.queue_name = self.exchange_space
self.exchange_names.append(self.exchange_space)
self.exchange_points.append(self.exchange_point)
pid = self.process_dispatcher.schedule_process(self.process_definitions['ingestion_worker'],configuration=config)
log.debug("the ingestion worker process id: %s", pid)
self.pids.append(pid)
self.addCleanup(self.cleaning_up)
def cleaning_up(self):
for pid in self.pids:
log.debug("number of pids to be terminated: %s", len(self.pids))
try:
self.process_dispatcher.cancel_process(pid)
log.debug("Terminated the process: %s", pid)
except:
log.debug("could not terminate the process id: %s" % pid)
IngestionManagementIntTest.clean_subscriptions()
for xn in self.exchange_names:
xni = self.container.ex_manager.create_xn_queue(xn)
xni.delete()
for xp in self.exchange_points:
xpi = self.container.ex_manager.create_xp(xp)
xpi.delete()
def get_datastore(self, dataset_id):
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
@attr('EXT')
@attr('PREP')
def test_create_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
parameter_dictionary = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict')
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=parameter_dictionary._id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp')
dp_obj.geospatial_bounds.geospatial_latitude_limit_north = 10.0
dp_obj.geospatial_bounds.geospatial_latitude_limit_south = -10.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_east = 10.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_west = -10.0
dp_obj.ooi_product_name = "PRODNAME"
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product( data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
# Assert that the data product has an associated stream at this stage
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, RT.Stream, True)
self.assertNotEquals(len(stream_ids), 0)
# Assert that the data product has an associated stream def at this stage
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStreamDefinition, RT.StreamDefinition, True)
self.assertNotEquals(len(stream_ids), 0)
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
self.assertEquals(dp_obj.geospatial_point_center.lat, 0.0)
log.debug('Created data product %s', dp_obj)
#------------------------------------------------------------------------------------------------
# test creating a new data product with a stream definition
#------------------------------------------------------------------------------------------------
log.debug('Creating new data product with a stream definition')
dp_obj = IonObject(RT.DataProduct,
name='DP2',
description='some new dp')
dp_id2 = self.dpsc_cli.create_data_product(dp_obj, ctd_stream_def_id)
self.dpsc_cli.activate_data_product_persistence(dp_id2)
log.debug('new dp_id = %s' % dp_id2)
#------------------------------------------------------------------------------------------------
#make sure data product is associated with stream def
#------------------------------------------------------------------------------------------------
streamdefs = []
streams, _ = self.rrclient.find_objects(dp_id2, PRED.hasStream, RT.Stream, True)
for s in streams:
log.debug("Checking stream %s" % s)
sdefs, _ = self.rrclient.find_objects(s, PRED.hasStreamDefinition, RT.StreamDefinition, True)
for sd in sdefs:
log.debug("Checking streamdef %s" % sd)
streamdefs.append(sd)
self.assertIn(ctd_stream_def_id, streamdefs)
group_names = self.dpsc_cli.get_data_product_group_list()
self.assertIn("PRODNAME", group_names)
#----------------------------------------------------------------------------------------
# Create users then notifications to this data product for each user
#----------------------------------------------------------------------------------------
# user_1
user_1 = UserInfo()
user_1.name = 'user_1'
user_1.contact.email = '*****@*****.**'
# user_2
user_2 = UserInfo()
user_2.name = 'user_2'
user_2.contact.email = '*****@*****.**'
#user1 is a complete user
self.subject = "/DC=org/DC=cilogon/C=US/O=ProtectNetwork/CN=Roger Unwin A254"
actor_identity_obj = IonObject("ActorIdentity", {"name": self.subject})
actor_id = self.identcli.create_actor_identity(actor_identity_obj)
user_credentials_obj = IonObject("UserCredentials", {"name": self.subject})
self.identcli.register_user_credentials(actor_id, user_credentials_obj)
user_id_1 = self.identcli.create_user_info(actor_id, user_1)
user_id_2, _ = self.rrclient.create(user_2)
delivery_config1a = IonObject(OT.DeliveryConfiguration, email='*****@*****.**', mode=DeliveryModeEnum.EMAIL, frequency=NotificationFrequencyEnum.BATCH)
delivery_config1b = IonObject(OT.DeliveryConfiguration, email='*****@*****.**', mode=DeliveryModeEnum.EMAIL, frequency=NotificationFrequencyEnum.BATCH)
notification_request_1 = NotificationRequest( name = "notification_1",
origin=dp_id,
origin_type="type_1",
event_type=OT.ResourceLifecycleEvent,
disabled_by_system = False,
delivery_configurations=[delivery_config1a, delivery_config1b])
delivery_config2a = IonObject(OT.DeliveryConfiguration, email='*****@*****.**', mode=DeliveryModeEnum.EMAIL, frequency=NotificationFrequencyEnum.BATCH)
delivery_config2b = IonObject(OT.DeliveryConfiguration, email='*****@*****.**', mode=DeliveryModeEnum.EMAIL, frequency=NotificationFrequencyEnum.BATCH)
notification_request_2 = NotificationRequest( name = "notification_2",
origin=dp_id,
origin_type="type_2",
disabled_by_system = False,
event_type=OT.DetectionEvent,
delivery_configurations=[delivery_config2a, delivery_config2b])
notification_request_1_id = self.unsc.create_notification(notification=notification_request_1, user_id=user_id_1)
notification_request_2_id = self.unsc.create_notification(notification=notification_request_2, user_id=user_id_2)
self.unsc.delete_notification(notification_request_1_id)
# test reading a non-existent data product
log.debug('reading non-existent data product')
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product('some_fake_id')
# update a data product (tests read also)
log.debug('Updating data product')
# first get the existing dp object
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# now tweak the object
dp_obj.description = 'the very first dp'
dp_obj.geospatial_bounds.geospatial_latitude_limit_north = 20.0
dp_obj.geospatial_bounds.geospatial_latitude_limit_south = -20.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_east = 20.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_west = -20.0
# now write the dp back to the registry
update_result = self.dpsc_cli.update_data_product(dp_obj)
# now get the dp back to see if it was updated
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertEquals(dp_obj.description,'the very first dp')
self.assertEquals(dp_obj.geospatial_point_center.lat, 0.0)
log.debug('Updated data product %s', dp_obj)
#test extension
extended_product = self.dpsc_cli.get_data_product_extension(dp_id)
#validate that there is one active and one retired user notification for this data product
self.assertEqual(1, len(extended_product.computed.active_user_subscriptions.value))
self.assertEqual(1, len(extended_product.computed.past_user_subscriptions.value))
self.assertEqual(dp_id, extended_product._id)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.product_download_size_estimated.status)
self.assertEqual(0, extended_product.computed.product_download_size_estimated.value)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.parameters.status)
#log.debug("test_create_data_product: parameters %s" % extended_product.computed.parameters.value)
def ion_object_encoder(obj):
return obj.__dict__
#test prepare for create
data_product_data = self.dpsc_cli.prepare_data_product_support()
#print simplejson.dumps(data_product_data, default=ion_object_encoder, indent= 2)
self.assertEqual(data_product_data._id, "")
self.assertEqual(data_product_data.type_, OT.DataProductPrepareSupport)
self.assertEqual(len(data_product_data.associations['StreamDefinition'].resources), 2)
self.assertEqual(len(data_product_data.associations['Dataset'].resources), 0)
self.assertEqual(len(data_product_data.associations['StreamDefinition'].associated_resources), 0)
self.assertEqual(len(data_product_data.associations['Dataset'].associated_resources), 0)
#test prepare for update
data_product_data = self.dpsc_cli.prepare_data_product_support(dp_id)
#print simplejson.dumps(data_product_data, default=ion_object_encoder, indent= 2)
self.assertEqual(data_product_data._id, dp_id)
self.assertEqual(data_product_data.type_, OT.DataProductPrepareSupport)
self.assertEqual(len(data_product_data.associations['StreamDefinition'].resources), 2)
self.assertEqual(len(data_product_data.associations['Dataset'].resources), 1)
self.assertEqual(len(data_product_data.associations['StreamDefinition'].associated_resources), 1)
self.assertEqual(data_product_data.associations['StreamDefinition'].associated_resources[0].s, dp_id)
self.assertEqual(len(data_product_data.associations['Dataset'].associated_resources), 1)
self.assertEqual(data_product_data.associations['Dataset'].associated_resources[0].s, dp_id)
# now 'delete' the data product
log.debug("deleting data product: %s" % dp_id)
self.dpsc_cli.delete_data_product(dp_id)
# Assert that there are no associated streams leftover after deleting the data product
stream_ids, assoc_ids = self.rrclient.find_objects(dp_id, PRED.hasStream, RT.Stream, True)
self.assertEquals(len(stream_ids), 0)
self.assertEquals(len(assoc_ids), 0)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# Get the events corresponding to the data product
ret = self.unsc.get_recent_events(resource_id=dp_id)
events = ret.value
for event in events:
log.debug("event time: %s" % event.ts_created)
self.assertTrue(len(events) > 0)
def test_data_product_stream_def(self):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=pdict_id)
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp')
dp_id = self.dpsc_cli.create_data_product(data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
stream_def_id = self.dpsc_cli.get_data_product_stream_definition(dp_id)
self.assertEquals(ctd_stream_def_id, stream_def_id)
def test_derived_data_product(self):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='ctd parsed', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsubcli.delete_stream_definition, ctd_stream_def_id)
dp = DataProduct(name='Instrument DP')
dp_id = self.dpsc_cli.create_data_product(dp, stream_definition_id=ctd_stream_def_id)
self.addCleanup(self.dpsc_cli.force_delete_data_product, dp_id)
self.dpsc_cli.activate_data_product_persistence(dp_id)
self.addCleanup(self.dpsc_cli.suspend_data_product_persistence, dp_id)
dataset_ids, _ = self.rrclient.find_objects(subject=dp_id, predicate=PRED.hasDataset, id_only=True)
if not dataset_ids:
raise NotFound("Data Product %s dataset does not exist" % str(dp_id))
dataset_id = dataset_ids[0]
# Make the derived data product
simple_stream_def_id = self.pubsubcli.create_stream_definition(name='TEMPWAT stream def', parameter_dictionary_id=pdict_id, available_fields=['time','temp'])
tempwat_dp = DataProduct(name='TEMPWAT', category=DataProductTypeEnum.DERIVED)
tempwat_dp_id = self.dpsc_cli.create_data_product(tempwat_dp, stream_definition_id=simple_stream_def_id, parent_data_product_id=dp_id)
self.addCleanup(self.dpsc_cli.delete_data_product, tempwat_dp_id)
# Check that the streams associated with the data product are persisted with
stream_ids, _ = self.rrclient.find_objects(dp_id,PRED.hasStream,RT.Stream,True)
for stream_id in stream_ids:
self.assertTrue(self.ingestclient.is_persisted(stream_id))
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
rdt = RecordDictionaryTool(stream_definition_id=ctd_stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = np.arange(20)
rdt['pressure'] = np.arange(20)
publisher = StandaloneStreamPublisher(stream_id,route)
dataset_modified = Event()
def cb(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb, origin=dataset_id, auto_delete=True)
es.start()
self.addCleanup(es.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
tempwat_dataset_ids, _ = self.rrclient.find_objects(tempwat_dp_id, PRED.hasDataset, id_only=True)
tempwat_dataset_id = tempwat_dataset_ids[0]
granule = self.data_retriever.retrieve(tempwat_dataset_id, delivery_format=simple_stream_def_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt['time'], np.arange(20))
self.assertEquals(set(rdt.fields), set(['time','temp']))
def test_activate_suspend_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=pdict_id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
# Construct temporal and spatial Coordinate Reference System objects
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp')
log.debug("Created an IonObject for a data product: %s" % dp_obj)
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product(data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# Subscribe to persist events
#------------------------------------------------------------------------------------------------
queue = gevent.queue.Queue()
def info_event_received(message, headers):
queue.put(message)
es = EventSubscriber(event_type=OT.InformationContentStatusEvent, callback=info_event_received, origin=dp_id, auto_delete=True)
es.start()
self.addCleanup(es.stop)
#------------------------------------------------------------------------------------------------
# test activate and suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
dataset_ids, _ = self.rrclient.find_objects(subject=dp_id, predicate=PRED.hasDataset, id_only=True)
if not dataset_ids:
raise NotFound("Data Product %s dataset does not exist" % str(dp_id))
dataset_id = dataset_ids[0]
# Check that the streams associated with the data product are persisted with
stream_ids, _ = self.rrclient.find_objects(dp_id,PRED.hasStream,RT.Stream,True)
for stream_id in stream_ids:
self.assertTrue(self.ingestclient.is_persisted(stream_id))
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
rdt = RecordDictionaryTool(stream_definition_id=ctd_stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = np.arange(20)
publisher = StandaloneStreamPublisher(stream_id,route)
dataset_modified = Event()
def cb(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb, origin=dataset_id, auto_delete=True)
es.start()
self.addCleanup(es.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_ids[0])
self.assertIsInstance(replay_data, Granule)
log.debug("The data retriever was able to replay the dataset that was attached to the data product "
"we wanted to be persisted. Therefore the data product was indeed persisted with "
"otherwise we could not have retrieved its dataset using the data retriever. Therefore "
"this demonstration shows that L4-CI-SA-RQ-267 is satisfied: 'Data product management shall persist data products'")
data_product_object = self.rrclient.read(dp_id)
self.assertEquals(data_product_object.name,'DP1')
self.assertEquals(data_product_object.description,'some new dp')
log.debug("Towards L4-CI-SA-RQ-308: 'Data product management shall persist data product metadata'. "
" Attributes in create for the data product obj, name= '%s', description='%s', match those of object from the "
"resource registry, name='%s', desc='%s'" % (dp_obj.name, dp_obj.description,data_product_object.name,
data_product_object.description))
#------------------------------------------------------------------------------------------------
# test suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.suspend_data_product_persistence(dp_id)
dataset_modified.clear()
rdt['time'] = np.arange(20,40)
publisher.publish(rdt.to_granule())
self.assertFalse(dataset_modified.wait(2))
self.dpsc_cli.activate_data_product_persistence(dp_id)
dataset_modified.clear()
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_almost_equal(rdt['time'], np.arange(40))
dataset_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasDataset, id_only=True)
self.assertEquals(len(dataset_ids), 1)
self.dpsc_cli.suspend_data_product_persistence(dp_id)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.rrclient.read(dp_id)
info_event_counter = 0
runtime = 0
starttime = time.time()
caught_events = []
#check that the four InfoStatusEvents were received
while info_event_counter < 4 and runtime < 60 :
a = queue.get(timeout=60)
caught_events.append(a)
info_event_counter += 1
runtime = time.time() - starttime
self.assertEquals(info_event_counter, 4)
class TestActivateInstrumentIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
super(TestActivateInstrumentIntegration, self).setUp()
config = DotDict()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
self.usernotificationclient = UserNotificationServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
self.event_publisher = EventPublisher()
def create_logger(self, name, stream_id=''):
# logger process
producer_definition = ProcessDefinition(name=name+'_logger')
producer_definition.executable = {
'module':'ion.processes.data.stream_granule_logger',
'class':'StreamGranuleLogger'
}
logger_procdef_id = self.processdispatchclient.create_process_definition(process_definition=producer_definition)
configuration = {
'process':{
'stream_id':stream_id,
}
}
pid = self.processdispatchclient.schedule_process(process_definition_id=logger_procdef_id,
configuration=configuration)
return pid
def _create_notification(self, user_name = '', instrument_id='', product_id=''):
#--------------------------------------------------------------------------------------
# Make notification request objects
#--------------------------------------------------------------------------------------
notification_request_1 = NotificationRequest( name= 'notification_1',
origin=instrument_id,
origin_type="instrument",
event_type='ResourceLifecycleEvent')
notification_request_2 = NotificationRequest( name='notification_2',
origin=product_id,
origin_type="data product",
event_type='DetectionEvent')
#--------------------------------------------------------------------------------------
# Create a user and get the user_id
#--------------------------------------------------------------------------------------
user = UserInfo()
user.name = user_name
user.contact.email = '*****@*****.**' % user_name
user_id, _ = self.rrclient.create(user)
#--------------------------------------------------------------------------------------
# Create notification
#--------------------------------------------------------------------------------------
self.usernotificationclient.create_notification(notification=notification_request_1, user_id=user_id)
self.usernotificationclient.create_notification(notification=notification_request_2, user_id=user_id)
log.debug( "test_activateInstrumentSample: create_user_notifications user_id %s", str(user_id) )
return user_id
def get_datastore(self, dataset_id):
dataset = self.datasetclient.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def _check_computed_attributes_of_extended_instrument(self, expected_instrument_device_id = '',extended_instrument = None):
# Verify that computed attributes exist for the extended instrument
self.assertIsInstance(extended_instrument.computed.last_data_received_datetime, ComputedFloatValue)
self.assertIsInstance(extended_instrument.computed.uptime, ComputedStringValue)
self.assertIsInstance(extended_instrument.computed.power_status_roll_up, ComputedIntValue)
self.assertIsInstance(extended_instrument.computed.communications_status_roll_up, ComputedIntValue)
self.assertIsInstance(extended_instrument.computed.data_status_roll_up, ComputedIntValue)
self.assertIsInstance(extended_instrument.computed.location_status_roll_up, ComputedIntValue)
# the following assert will not work without elasticsearch.
#self.assertEqual( 1, len(extended_instrument.computed.user_notification_requests.value) )
# Verify the computed attribute for user notification requests
self.assertEqual( 1, len(extended_instrument.computed.user_notification_requests.value) )
notifications = extended_instrument.computed.user_notification_requests.value
notification = notifications[0]
self.assertEqual(expected_instrument_device_id, notification.origin)
self.assertEqual("instrument", notification.origin_type)
self.assertEqual('ResourceLifecycleEvent', notification.event_type)
def _check_computed_attributes_of_extended_product(self, expected_data_product_id = '', extended_data_product = None):
self.assertEqual(expected_data_product_id, extended_data_product._id)
log.debug("extended_data_product.computed: %s", extended_data_product.computed)
# Verify that computed attributes exist for the extended instrument
self.assertIsInstance(extended_data_product.computed.product_download_size_estimated, ComputedFloatValue)
self.assertIsInstance(extended_data_product.computed.number_active_subscriptions, ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.data_url, ComputedStringValue)
self.assertIsInstance(extended_data_product.computed.stored_data_size, ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.recent_granules, ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.parameters, ComputedListValue)
self.assertIsInstance(extended_data_product.computed.recent_events, ComputedEventListValue)
self.assertIsInstance(extended_data_product.computed.provenance, ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.user_notification_requests, ComputedListValue)
self.assertIsInstance(extended_data_product.computed.active_user_subscriptions, ComputedListValue)
self.assertIsInstance(extended_data_product.computed.past_user_subscriptions, ComputedListValue)
self.assertIsInstance(extended_data_product.computed.last_granule, ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.is_persisted, ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.data_contents_updated, ComputedStringValue)
self.assertIsInstance(extended_data_product.computed.data_datetime, ComputedListValue)
# exact text here keeps changing to fit UI capabilities. keep assertion general...
self.assertEqual( 2, len(extended_data_product.computed.data_datetime.value) )
notifications = extended_data_product.computed.user_notification_requests.value
notification = notifications[0]
self.assertEqual(expected_data_product_id, notification.origin)
self.assertEqual("data product", notification.origin_type)
self.assertEqual('DetectionEvent', notification.event_type)
@attr('LOCOINT')
#@unittest.skip('refactoring')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
@patch.dict(CFG, {'endpoint':{'receive':{'timeout': 90}}})
def test_activateInstrumentSample(self):
self.loggerpids = []
# Create InstrumentModel
instModel_obj = IonObject(RT.InstrumentModel,
name='SBE37IMModel',
description="SBE37IMModel")
instModel_id = self.imsclient.create_instrument_model(instModel_obj)
log.debug( 'new InstrumentModel id = %s ', instModel_id)
raw_config = StreamConfiguration(stream_name='raw', parameter_dictionary_name='raw')
parsed_config = StreamConfiguration(stream_name='parsed', parameter_dictionary_name='ctd_parsed_param_dict')
# Create InstrumentAgent
instAgent_obj = IonObject(RT.InstrumentAgent,
name='agent007',
description="SBE37IMAgent",
driver_uri=DRV_URI_GOOD,
stream_configurations = [raw_config, parsed_config])
instAgent_id = self.imsclient.create_instrument_agent(instAgent_obj)
log.debug('new InstrumentAgent id = %s', instAgent_id)
self.imsclient.assign_instrument_model_to_instrument_agent(instModel_id, instAgent_id)
# Create InstrumentDevice
log.debug('test_activateInstrumentSample: Create instrument resource to represent the SBE37 (SA Req: L4-CI-SA-RQ-241) ')
instDevice_obj = IonObject(RT.InstrumentDevice,
name='SBE37IMDevice',
description="SBE37IMDevice",
serial_number="12345" )
instDevice_id = self.imsclient.create_instrument_device(instrument_device=instDevice_obj)
self.imsclient.assign_instrument_model_to_instrument_device(instModel_id, instDevice_id)
log.debug("test_activateInstrumentSample: new InstrumentDevice id = %s (SA Req: L4-CI-SA-RQ-241) " , instDevice_id)
port_agent_config = {
'device_addr': CFG.device.sbe37.host,
'device_port': CFG.device.sbe37.port,
'process_type': PortAgentProcessType.UNIX,
'binary_path': "port_agent",
'port_agent_addr': 'localhost',
'command_port': CFG.device.sbe37.port_agent_cmd_port,
'data_port': CFG.device.sbe37.port_agent_data_port,
'log_level': 5,
'type': PortAgentType.ETHERNET
}
instAgentInstance_obj = IonObject(RT.InstrumentAgentInstance, name='SBE37IMAgentInstance',
description="SBE37IMAgentInstance",
port_agent_config = port_agent_config,
alerts= [])
instAgentInstance_id = self.imsclient.create_instrument_agent_instance(instAgentInstance_obj,
instAgent_id,
instDevice_id)
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
parsed_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
parsed_stream_def_id = self.pubsubcli.create_stream_definition(name='parsed', parameter_dictionary_id=parsed_pdict_id)
raw_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('raw', id_only=True)
raw_stream_def_id = self.pubsubcli.create_stream_definition(name='raw', parameter_dictionary_id=raw_pdict_id)
#-------------------------------
# Create Raw and Parsed Data Products for the device
#-------------------------------
dp_obj = IonObject(RT.DataProduct,
name='the parsed data',
description='ctd stream test',
temporal_domain = tdom,
spatial_domain = sdom)
data_product_id1 = self.dpclient.create_data_product(data_product=dp_obj, stream_definition_id=parsed_stream_def_id)
log.debug( 'new dp_id = %s' , data_product_id1)
self.dpclient.activate_data_product_persistence(data_product_id=data_product_id1)
self.damsclient.assign_data_product(input_resource_id=instDevice_id, data_product_id=data_product_id1)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id1, PRED.hasStream, None, True)
log.debug('Data product streams1 = %s', stream_ids)
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id1, PRED.hasDataset, RT.Dataset, True)
log.debug('Data set for data_product_id1 = %s' , dataset_ids[0])
self.parsed_dataset = dataset_ids[0]
pid = self.create_logger('ctd_parsed', stream_ids[0] )
self.loggerpids.append(pid)
dp_obj = IonObject(RT.DataProduct,
name='the raw data',
description='raw stream test',
temporal_domain = tdom,
spatial_domain = sdom)
data_product_id2 = self.dpclient.create_data_product(data_product=dp_obj, stream_definition_id=raw_stream_def_id)
log.debug('new dp_id = %s', data_product_id2)
self.damsclient.assign_data_product(input_resource_id=instDevice_id, data_product_id=data_product_id2)
self.dpclient.activate_data_product_persistence(data_product_id=data_product_id2)
# setup notifications for the device and parsed data product
user_id_1 = self._create_notification( user_name='user_1', instrument_id=instDevice_id, product_id=data_product_id1)
#---------- Create notifications for another user and verify that we see different computed subscriptions for the two users ---------
user_id_2 = self._create_notification( user_name='user_2', instrument_id=instDevice_id, product_id=data_product_id2)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id2, PRED.hasStream, None, True)
log.debug('Data product streams2 = %s' , str(stream_ids))
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id2, PRED.hasDataset, RT.Dataset, True)
log.debug('Data set for data_product_id2 = %s' , dataset_ids[0])
self.raw_dataset = dataset_ids[0]
def start_instrument_agent():
self.imsclient.start_instrument_agent_instance(instrument_agent_instance_id=instAgentInstance_id)
gevent.joinall([gevent.spawn(start_instrument_agent)])
#cleanup
self.addCleanup(self.imsclient.stop_instrument_agent_instance,
instrument_agent_instance_id=instAgentInstance_id)
#wait for start
inst_agent_instance_obj = self.imsclient.read_instrument_agent_instance(instAgentInstance_id)
gate = AgentProcessStateGate(self.processdispatchclient.read_process,
instDevice_id,
ProcessStateEnum.RUNNING)
self.assertTrue(gate.await(30), "The instrument agent instance (%s) did not spawn in 30 seconds" %
gate.process_id)
#log.trace('Instrument agent instance obj: = %s' , str(inst_agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._ia_client = ResourceAgentClient(instDevice_id,
to_name=gate.process_id,
process=FakeProcess())
log.debug("test_activateInstrumentSample: got ia client %s" , str(self._ia_client))
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
retval = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: initialize %s" , str(retval))
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.INACTIVE, state)
log.debug("(L4-CI-SA-RQ-334): Sending go_active command ")
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrument: return value from go_active %s" , str(reply))
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.IDLE, state)
cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
retval = self._ia_client.execute_agent(cmd)
state = retval.result
log.debug("(L4-CI-SA-RQ-334): current state after sending go_active command %s" , str(state))
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: run %s" , str(reply))
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.COMMAND, state)
cmd = AgentCommand(command=ResourceAgentEvent.PAUSE)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.STOPPED, state)
cmd = AgentCommand(command=ResourceAgentEvent.RESUME)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.COMMAND, state)
cmd = AgentCommand(command=ResourceAgentEvent.CLEAR)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.IDLE, state)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.COMMAND, state)
for i in xrange(10):
monitor = DatasetMonitor(dataset_id=self.parsed_dataset)
self._ia_client.execute_resource(AgentCommand(command=SBE37ProtocolEvent.ACQUIRE_SAMPLE))
if not monitor.wait():
raise AssertionError('Failed on the %ith granule' % i)
monitor.stop()
# cmd = AgentCommand(command=SBE37ProtocolEvent.ACQUIRE_SAMPLE)
# for i in xrange(10):
# retval = self._ia_client.execute_resource(cmd)
# log.debug("test_activateInstrumentSample: return from sample %s" , str(retval))
log.debug( "test_activateInstrumentSample: calling reset ")
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: return from reset %s" , str(reply))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data_raw = self.dataretrieverclient.retrieve(self.raw_dataset)
self.assertIsInstance(replay_data_raw, Granule)
rdt_raw = RecordDictionaryTool.load_from_granule(replay_data_raw)
log.debug("RDT raw: %s", str(rdt_raw.pretty_print()) )
self.assertIn('raw', rdt_raw)
raw_vals = rdt_raw['raw']
all_raw = "".join(raw_vals)
# look for 't' entered after a prompt -- ">t"
t_commands = all_raw.count(">t")
if 10 != t_commands:
log.error("%s raw_vals: ", len(raw_vals))
for i, r in enumerate(raw_vals): log.error("raw val %s: %s", i, [r])
self.fail("Expected 10 't' strings in raw_vals, got %s" % t_commands)
else:
log.debug("%s raw_vals: ", len(raw_vals))
for i, r in enumerate(raw_vals): log.debug("raw val %s: %s", i, [r])
replay_data_parsed = self.dataretrieverclient.retrieve(self.parsed_dataset)
self.assertIsInstance(replay_data_parsed, Granule)
rdt_parsed = RecordDictionaryTool.load_from_granule(replay_data_parsed)
log.debug("test_activateInstrumentSample: RDT parsed: %s", str(rdt_parsed.pretty_print()) )
self.assertIn('temp', rdt_parsed)
temp_vals = rdt_parsed['temp']
pressure_vals = rdt_parsed['pressure']
if 10 != len(temp_vals):
log.error("%s temp_vals: %s", len(temp_vals), temp_vals)
self.fail("Expected 10 temp_vals, got %s" % len(temp_vals))
log.debug("l4-ci-sa-rq-138")
"""
Physical resource control shall be subject to policy
Instrument management control capabilities shall be subject to policy
The actor accessing the control capabilities must be authorized to send commands.
note from maurice 2012-05-18: Talk to tim M to verify that this is policy. If it is then talk with Stephen to
get an example of a policy test and use that to create a test stub that will be
completed when we have instrument policies.
Tim M: The "actor", aka observatory operator, will access the instrument through ION.
"""
#--------------------------------------------------------------------------------
# Get the extended data product to see if it contains the granules
#--------------------------------------------------------------------------------
extended_product = self.dpclient.get_data_product_extension(data_product_id=data_product_id1, user_id=user_id_1)
def poller(extended_product):
return len(extended_product.computed.user_notification_requests.value) == 1
poll(poller, extended_product, timeout=30)
self._check_computed_attributes_of_extended_product( expected_data_product_id = data_product_id1, extended_data_product = extended_product)
#--------------------------------------------------------------------------------
# Get the extended instrument
#--------------------------------------------------------------------------------
extended_instrument = self.imsclient.get_instrument_device_extension(instrument_device_id=instDevice_id, user_id=user_id_1)
#--------------------------------------------------------------------------------
# For the second user, check the extended data product and the extended intrument
#--------------------------------------------------------------------------------
extended_product = self.dpclient.get_data_product_extension(data_product_id=data_product_id2, user_id=user_id_2)
self._check_computed_attributes_of_extended_product(expected_data_product_id = data_product_id2, extended_data_product = extended_product)
#--------------------------------------------------------------------------------
# Get the extended instrument
#--------------------------------------------------------------------------------
extended_instrument = self.imsclient.get_instrument_device_extension(instrument_device_id=instDevice_id, user_id=user_id_2)
self._check_computed_attributes_of_extended_instrument(expected_instrument_device_id = instDevice_id, extended_instrument = extended_instrument)
#--------------------------------------------------------------------------------
# Deactivate loggers
#--------------------------------------------------------------------------------
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
self.dpclient.delete_data_product(data_product_id1)
self.dpclient.delete_data_product(data_product_id2)
class TestActivateRSNVel3DInstrument(IonIntegrationTestCase):
def setUp(self):
# Start container
super(TestActivateRSNVel3DInstrument, self).setUp()
config = DotDict()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
def create_logger(self, name, stream_id=''):
# logger process
producer_definition = ProcessDefinition(name=name+'_logger')
producer_definition.executable = {
'module':'ion.processes.data.stream_granule_logger',
'class':'StreamGranuleLogger'
}
logger_procdef_id = self.processdispatchclient.create_process_definition(process_definition=producer_definition)
configuration = {
'process':{
'stream_id':stream_id,
}
}
pid = self.processdispatchclient.schedule_process(process_definition_id=logger_procdef_id,
configuration=configuration)
return pid
@attr('LOCOINT')
@unittest.skip('under construction')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
@patch.dict(CFG, {'endpoint':{'receive':{'timeout': 180}}})
def test_activate_rsn_vel3d(self):
log.info("--------------------------------------------------------------------------------------------------------")
# load_parameter_scenarios
self.container.spawn_process("Loader", "ion.processes.bootstrap.ion_loader", "IONLoader", config=dict(
op="load",
scenario="BETA",
path="master",
categories="ParameterFunctions,ParameterDefs,ParameterDictionary,StreamDefinition",
clearcols="owner_id,org_ids",
assets="res/preload/r2_ioc/ooi_assets",
parseooi="True",
))
self.loggerpids = []
# Create InstrumentModel
instModel_obj = IonObject(RT.InstrumentModel,
name='Vel3DMModel',
description="Vel3DMModel")
instModel_id = self.imsclient.create_instrument_model(instModel_obj)
log.debug( 'test_activate_rsn_vel3d new InstrumentModel id = %s ', instModel_id)
raw_config = StreamConfiguration(stream_name='raw', parameter_dictionary_name='raw' )
vel3d_b_sample = StreamConfiguration(stream_name='vel3d_b_sample', parameter_dictionary_name='vel3d_b_sample')
vel3d_b_engineering = StreamConfiguration(stream_name='vel3d_b_engineering', parameter_dictionary_name='vel3d_b_engineering')
RSN_VEL3D_01 = {
'DEV_ADDR' : "10.180.80.6",
'DEV_PORT' : 2101,
'DATA_PORT' : 1026,
'CMD_PORT' : 1025,
'PA_BINARY' : "port_agent"
}
# Create InstrumentAgent
instAgent_obj = IonObject(RT.InstrumentAgent,
name='Vel3DAgent',
description="Vel3DAgent",
driver_uri="http://sddevrepo.oceanobservatories.org/releases/nobska_mavs4_ooicore-0.0.7-py2.7.egg",
stream_configurations = [raw_config, vel3d_b_sample, vel3d_b_engineering])
instAgent_id = self.imsclient.create_instrument_agent(instAgent_obj)
log.debug('test_activate_rsn_vel3d new InstrumentAgent id = %s', instAgent_id)
self.imsclient.assign_instrument_model_to_instrument_agent(instModel_id, instAgent_id)
# Create InstrumentDevice
log.debug('test_activate_rsn_vel3d: Create instrument resource to represent the Vel3D ')
instDevice_obj = IonObject(RT.InstrumentDevice,
name='Vel3DDevice',
description="Vel3DDevice",
serial_number="12345" )
instDevice_id = self.imsclient.create_instrument_device(instrument_device=instDevice_obj)
self.imsclient.assign_instrument_model_to_instrument_device(instModel_id, instDevice_id)
log.debug("test_activate_rsn_vel3d: new InstrumentDevice id = %s " , instDevice_id)
port_agent_config = {
'device_addr': '10.180.80.6',
'device_port': 2101,
'process_type': PortAgentProcessType.UNIX,
'binary_path': "port_agent",
'port_agent_addr': 'localhost',
'command_port': 1025,
'data_port': 1026,
'log_level': 5,
'type': PortAgentType.ETHERNET
}
instAgentInstance_obj = IonObject(RT.InstrumentAgentInstance, name='Vel3DAgentInstance',
description="Vel3DAgentInstance",
port_agent_config = port_agent_config,
alerts= [])
instAgentInstance_id = self.imsclient.create_instrument_agent_instance(instAgentInstance_obj,
instAgent_id,
instDevice_id)
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
parsed_sample_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('vel3d_b_sample', id_only=True)
parsed_sample_stream_def_id = self.pubsubcli.create_stream_definition(name='vel3d_b_sample', parameter_dictionary_id=parsed_sample_pdict_id)
parsed_eng_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('vel3d_b_engineering', id_only=True)
parsed_eng_stream_def_id = self.pubsubcli.create_stream_definition(name='vel3d_b_engineering', parameter_dictionary_id=parsed_eng_pdict_id)
raw_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('raw', id_only=True)
raw_stream_def_id = self.pubsubcli.create_stream_definition(name='raw', parameter_dictionary_id=raw_pdict_id)
#-------------------------------
# Create Raw and Parsed Data Products for the device
#-------------------------------
dp_obj = IonObject(RT.DataProduct,
name='vel3d_b_sample',
description='vel3d_b_sample',
temporal_domain = tdom,
spatial_domain = sdom)
sample_data_product_id = self.dpclient.create_data_product(data_product=dp_obj, stream_definition_id=parsed_sample_stream_def_id)
log.debug( 'new dp_id = %s' , sample_data_product_id)
self.dpclient.activate_data_product_persistence(data_product_id=sample_data_product_id)
self.damsclient.assign_data_product(input_resource_id=instDevice_id, data_product_id=sample_data_product_id)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(sample_data_product_id, PRED.hasStream, None, True)
log.debug('sample_data_product streams1 = %s', stream_ids)
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(sample_data_product_id, PRED.hasDataset, RT.Dataset, True)
log.debug('Data set for sample_data_product = %s' , dataset_ids[0])
self.parsed_dataset = dataset_ids[0]
pid = self.create_logger('vel3d_b_sample', stream_ids[0] )
self.loggerpids.append(pid)
dp_obj = IonObject(RT.DataProduct,
name='vel3d_b_engineering',
description='vel3d_b_engineering',
temporal_domain = tdom,
spatial_domain = sdom)
eng_data_product_id = self.dpclient.create_data_product(data_product=dp_obj, stream_definition_id=parsed_eng_stream_def_id)
log.debug( 'new dp_id = %s' , eng_data_product_id)
self.dpclient.activate_data_product_persistence(data_product_id=eng_data_product_id)
self.damsclient.assign_data_product(input_resource_id=instDevice_id, data_product_id=eng_data_product_id)
dp_obj = IonObject(RT.DataProduct,
name='the raw data',
description='raw stream test',
temporal_domain = tdom,
spatial_domain = sdom)
data_product_id2 = self.dpclient.create_data_product(data_product=dp_obj, stream_definition_id=raw_stream_def_id)
log.debug('new dp_id = %s', data_product_id2)
self.damsclient.assign_data_product(input_resource_id=instDevice_id, data_product_id=data_product_id2)
self.dpclient.activate_data_product_persistence(data_product_id=data_product_id2)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id2, PRED.hasStream, None, True)
log.debug('test_activate_rsn_vel3d Data product streams2 = %s' , str(stream_ids))
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id2, PRED.hasDataset, RT.Dataset, True)
log.debug('test_activate_rsn_vel3d Data set for data_product_id2 = %s' , dataset_ids[0])
self.raw_dataset = dataset_ids[0]
def start_instrument_agent():
self.imsclient.start_instrument_agent_instance(instrument_agent_instance_id=instAgentInstance_id)
gevent.joinall([gevent.spawn(start_instrument_agent)])
#cleanup
self.addCleanup(self.imsclient.stop_instrument_agent_instance,
instrument_agent_instance_id=instAgentInstance_id)
#wait for start
inst_agent_instance_obj = self.imsclient.read_instrument_agent_instance(instAgentInstance_id)
gate = AgentProcessStateGate(self.processdispatchclient.read_process,
instDevice_id,
ProcessStateEnum.RUNNING)
self.assertTrue(gate.await(30), "The instrument agent instance (%s) did not spawn in 30 seconds" %
gate.process_id)
#log.trace('Instrument agent instance obj: = %s' , str(inst_agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._ia_client = ResourceAgentClient(instDevice_id,
to_name=gate.process_id,
process=FakeProcess())
def check_state(label, desired_state):
actual_state = self._ia_client.get_agent_state()
log.debug("%s instrument agent is in state '%s'", label, actual_state)
self.assertEqual(desired_state, actual_state)
log.debug("test_activate_rsn_vel3d: got ia client %s" , str(self._ia_client))
check_state("just-spawned", ResourceAgentState.UNINITIALIZED)
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
retval = self._ia_client.execute_agent(cmd)
log.debug("test_activate_rsn_vel3d: initialize %s" , str(retval))
check_state("initialized", ResourceAgentState.INACTIVE)
log.debug("test_activate_rsn_vel3d Sending go_active command ")
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activate_rsn_vel3d: return value from go_active %s" , str(reply))
check_state("activated", ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
retval = self._ia_client.execute_agent(cmd)
state = retval.result
log.debug("current state after sending go_active command %s" , str(state))
#
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activate_rsn_vel3d: run %s" , str(reply))
check_state("commanded", ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
retval = self._ia_client.execute_agent(cmd)
state = retval.result
log.debug("current state after sending run command %s" , str(state))
# cmd = AgentCommand(command=ProtocolEvent.START_AUTOSAMPLE)
# reply = self._ia_client.execute_agent(cmd)
# log.debug("test_activate_rsn_vel3d: run %s" , str(reply))
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.COMMAND, state)
#
# gevent.sleep(5)
#
# cmd = AgentCommand(command=ProtocolEvent.STOP_AUTOSAMPLE)
# reply = self._ia_client.execute_agent(cmd)
# log.debug("test_activate_rsn_vel3d: run %s" , str(reply))
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.COMMAND, state)
#
# cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
# retval = self._ia_client.execute_agent(cmd)
# state = retval.result
# log.debug("current state after sending STOP_AUTOSAMPLE command %s" , str(state))
#
# cmd = AgentCommand(command=ResourceAgentEvent.PAUSE)
# retval = self._ia_client.execute_agent(cmd)
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.STOPPED, state)
#
# cmd = AgentCommand(command=ResourceAgentEvent.RESUME)
# retval = self._ia_client.execute_agent(cmd)
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.COMMAND, state)
#
# cmd = AgentCommand(command=ResourceAgentEvent.CLEAR)
# retval = self._ia_client.execute_agent(cmd)
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.IDLE, state)
#
# cmd = AgentCommand(command=ResourceAgentEvent.RUN)
# retval = self._ia_client.execute_agent(cmd)
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.COMMAND, state)
log.debug( "test_activate_rsn_vel3d: calling reset ")
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activate_rsn_vel3d: return from reset %s" , str(reply))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data_raw = self.dataretrieverclient.retrieve(self.raw_dataset)
self.assertIsInstance(replay_data_raw, Granule)
rdt_raw = RecordDictionaryTool.load_from_granule(replay_data_raw)
log.debug("RDT raw: %s", str(rdt_raw.pretty_print()) )
self.assertIn('raw', rdt_raw)
raw_vals = rdt_raw['raw']
#--------------------------------------------------------------------------------
# Deactivate loggers
#--------------------------------------------------------------------------------
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
self.dpclient.delete_data_product(sample_data_product_id)
self.dpclient.delete_data_product(eng_data_product_id)
self.dpclient.delete_data_product(data_product_id2)
def test_blog_ingestion_replay(self):
#-----------------------------------------------------------------------------------------------------
# Do this statement just once in your script
#-----------------------------------------------------------------------------------------------------
cc = self.container
#-------------------------------------------------------------------------------------------------------
# Make a registrar object - this is work usually done for you by the container in a transform or data stream process
#-------------------------------------------------------------------------------------------------------
subscriber_registrar = StreamSubscriberRegistrar(process=cc, node=cc.node)
#-----------------------------------------------------------------------------------------------------
# Service clients
#-----------------------------------------------------------------------------------------------------
ingestion_cli = IngestionManagementServiceClient(node=cc.node)
dr_cli = DataRetrieverServiceClient(node=cc.node)
dsm_cli = DatasetManagementServiceClient(node=cc.node)
pubsub_cli = PubsubManagementServiceClient(node=cc.node)
#-------------------------------------------------------------------------------------------------------
# Create and activate ingestion configuration
#-------------------------------------------------------------------------------------------------------
ingestion_configuration_id = ingestion_cli.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name='dm_datastore',datastore_profile='EXAMPLES'),
hdf_storage=HdfStorage(),
number_of_workers=6,
)
# activates the transforms... so bindings will be created in this step
ingestion_cli.activate_ingestion_configuration(ingestion_configuration_id)
#------------------------------------------------------------------------------------------------------
# Create subscriber to listen to the messages published to the ingestion
#------------------------------------------------------------------------------------------------------
# Define the query we want
query = ExchangeQuery()
# Create the stateful listener to hold the captured data for comparison with replay
captured_input = BlogListener()
# Make a subscription to the input stream to ingestion
subscription_id = pubsub_cli.create_subscription(query = query, exchange_name='input_capture_queue' ,name = 'input_capture_queue')
# It is not required or even generally a good idea to use the subscription resource name as the queue name, but it makes things simple here
# Normally the container creates and starts subscribers for you when a transform process is spawned
subscriber = subscriber_registrar.create_subscriber(exchange_name='input_capture_queue', callback=captured_input.blog_store)
subscriber.start()
captured_input.subscriber = subscriber
pubsub_cli.activate_subscription(subscription_id)
#-------------------------------------------------------------------------------------------------------
# Launching blog scraper
#-------------------------------------------------------------------------------------------------------
blogs = [
'saintsandspinners',
'strobist',
'voodoofunk'
]
log.debug('before spawning blog scraper')
for blog in blogs:
config = {'process':{'type':'stream_process','blog':blog}}
cc.spawn_process(name=blog,
module='ion.services.dm.ingestion.example.blog_scraper',
cls='FeedStreamer',
config=config)
# wait ten seconds for some data to come in...
log.warn('Sleeping for 10 seconds to wait for some input')
time.sleep(10)
#------------------------------------------------------------------------------------------------------
# For 3 posts captured, make 3 replays and verify we get back what came in
#------------------------------------------------------------------------------------------------------
# Cute list comprehension method does not give enough control
#self.assertTrue(len(captured_input.blogs)>3)
#post_ids = [id for idx, id in enumerate(captured_input.blogs.iterkeys()) if idx < 3]
post_ids = []
for post_id, blog in captured_input.blogs.iteritems(): # Use items not iter items - I copy of fixed length
log.info('Captured Input: %s' % post_id)
if len(blog.get('comments',[])) > 2:
post_ids.append(post_id)
if len(post_ids) >3:
break
###=======================================================
### This section is not scriptable
###=======================================================
if len(post_ids) < 3:
self.fail('Not enough comments returned by the blog scrappers in 30 seconds')
if len(captured_input.blogs) < 1:
self.fail('No data returned in ten seconds by the blog scrappers!')
###=======================================================
### End non-scriptable
###=======================================================
#------------------------------------------------------------------------------------------------------
# Create subscriber to listen to the replays
#------------------------------------------------------------------------------------------------------
captured_replays = {}
for idx, post_id in enumerate(post_ids):
# Create the stateful listener to hold the captured data for comparison with replay
dataset_id = dsm_cli.create_dataset(
stream_id=post_id,
datastore_name='dm_datastore',
view_name='posts/posts_join_comments')
replay_id, stream_id =dr_cli.define_replay(dataset_id)
query = StreamQuery(stream_ids=[stream_id])
captured_replay = BlogListener()
#------------------------------------------------------------------------------------------------------
# Create subscriber to listen to the messages published to the ingestion
#------------------------------------------------------------------------------------------------------
# Make a subscription to the input stream to ingestion
subscription_name = 'replay_capture_queue_%d' % idx
subscription_id = pubsub_cli.create_subscription(query = query, exchange_name=subscription_name ,name = subscription_name)
# It is not required or even generally a good idea to use the subscription resource name as the queue name, but it makes things simple here
# Normally the container creates and starts subscribers for you when a transform process is spawned
subscriber = subscriber_registrar.create_subscriber(exchange_name=subscription_name, callback=captured_replay.blog_store)
subscriber.start()
captured_replay.subscriber = subscriber
pubsub_cli.activate_subscription(subscription_id)
#------------------------------------------------------------------------------------------------------
# Start the replay and listen to the results!
#------------------------------------------------------------------------------------------------------
dr_cli.start_replay(replay_id)
captured_replays[post_id] = captured_replay
###=======================================================
### The rest is not scriptable
###=======================================================
# wait five seconds for some data to come in...
log.warn('Sleeping for 5 seconds to wait for some output')
time.sleep(5)
matched_comments={}
for post_id, captured_replay in captured_replays.iteritems():
# There should be only one blog in here!
self.assertEqual(len(captured_replay.blogs),1)
replayed_blog = captured_replay.blogs[post_id]
input_blog = captured_input.blogs[post_id]
self.assertEqual(replayed_blog['post'].content, input_blog['post'].content)
# can't deterministically assert that the number of comments is the same...
matched_comments[post_id] = 0
for updated, comment in replayed_blog.get('comments',{}).iteritems():
self.assertIn(updated, input_blog['comments'])
matched_comments[post_id] += 1
# Assert that we got some comments back!
self.assertTrue(sum(matched_comments.values()) > 0)
log.info('Matched comments on the following blogs: %s' % matched_comments)
class TestActivateInstrumentIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
super(TestActivateInstrumentIntegration, self).setUp()
config = DotDict()
config.bootstrap.use_es = True
self._start_container()
self.addCleanup(TestActivateInstrumentIntegration.es_cleanup)
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(
node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(
node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
self.usernotificationclient = UserNotificationServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
self.event_publisher = EventPublisher()
@staticmethod
def es_cleanup():
es_host = CFG.get_safe('server.elasticsearch.host', 'localhost')
es_port = CFG.get_safe('server.elasticsearch.port', '9200')
es = ep.ElasticSearch(host=es_host, port=es_port, timeout=10)
indexes = STD_INDEXES.keys()
indexes.append('%s_resources_index' % get_sys_name().lower())
indexes.append('%s_events_index' % get_sys_name().lower())
for index in indexes:
IndexManagementService._es_call(es.river_couchdb_delete, index)
IndexManagementService._es_call(es.index_delete, index)
def create_logger(self, name, stream_id=''):
# logger process
producer_definition = ProcessDefinition(name=name + '_logger')
producer_definition.executable = {
'module': 'ion.processes.data.stream_granule_logger',
'class': 'StreamGranuleLogger'
}
logger_procdef_id = self.processdispatchclient.create_process_definition(
process_definition=producer_definition)
configuration = {
'process': {
'stream_id': stream_id,
}
}
pid = self.processdispatchclient.schedule_process(
process_definition_id=logger_procdef_id,
configuration=configuration)
return pid
def _create_notification(self,
user_name='',
instrument_id='',
product_id=''):
#--------------------------------------------------------------------------------------
# Make notification request objects
#--------------------------------------------------------------------------------------
notification_request_1 = NotificationRequest(
name='notification_1',
origin=instrument_id,
origin_type="instrument",
event_type='ResourceLifecycleEvent')
notification_request_2 = NotificationRequest(
name='notification_2',
origin=product_id,
origin_type="data product",
event_type='DetectionEvent')
#--------------------------------------------------------------------------------------
# Create a user and get the user_id
#--------------------------------------------------------------------------------------
user = UserInfo()
user.name = user_name
user.contact.email = '*****@*****.**' % user_name
user_id, _ = self.rrclient.create(user)
#--------------------------------------------------------------------------------------
# Create notification
#--------------------------------------------------------------------------------------
self.usernotificationclient.create_notification(
notification=notification_request_1, user_id=user_id)
self.usernotificationclient.create_notification(
notification=notification_request_2, user_id=user_id)
log.debug(
"test_activateInstrumentSample: create_user_notifications user_id %s",
str(user_id))
return user_id
def get_datastore(self, dataset_id):
dataset = self.datasetclient.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(
datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def _check_computed_attributes_of_extended_instrument(
self, expected_instrument_device_id='', extended_instrument=None):
# Verify that computed attributes exist for the extended instrument
self.assertIsInstance(
extended_instrument.computed.last_data_received_datetime,
ComputedFloatValue)
self.assertIsInstance(extended_instrument.computed.uptime,
ComputedStringValue)
self.assertIsInstance(
extended_instrument.computed.power_status_roll_up,
ComputedIntValue)
self.assertIsInstance(
extended_instrument.computed.communications_status_roll_up,
ComputedIntValue)
self.assertIsInstance(extended_instrument.computed.data_status_roll_up,
ComputedIntValue)
self.assertIsInstance(
extended_instrument.computed.location_status_roll_up,
ComputedIntValue)
# the following assert will not work without elasticsearch.
#self.assertEqual( 1, len(extended_instrument.computed.user_notification_requests.value) )
# Verify the computed attribute for user notification requests
self.assertEqual(
1,
len(extended_instrument.computed.user_notification_requests.value))
notifications = extended_instrument.computed.user_notification_requests.value
notification = notifications[0]
self.assertEqual(expected_instrument_device_id, notification.origin)
self.assertEqual("instrument", notification.origin_type)
self.assertEqual('ResourceLifecycleEvent', notification.event_type)
def _check_computed_attributes_of_extended_product(
self, expected_data_product_id='', extended_data_product=None):
self.assertEqual(expected_data_product_id, extended_data_product._id)
log.debug("extended_data_product.computed: %s",
extended_data_product.computed)
# Verify that computed attributes exist for the extended instrument
self.assertIsInstance(
extended_data_product.computed.product_download_size_estimated,
ComputedFloatValue)
self.assertIsInstance(
extended_data_product.computed.number_active_subscriptions,
ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.data_url,
ComputedStringValue)
self.assertIsInstance(extended_data_product.computed.stored_data_size,
ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.recent_granules,
ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.parameters,
ComputedListValue)
self.assertIsInstance(extended_data_product.computed.recent_events,
ComputedEventListValue)
self.assertIsInstance(extended_data_product.computed.provenance,
ComputedDictValue)
self.assertIsInstance(
extended_data_product.computed.user_notification_requests,
ComputedListValue)
self.assertIsInstance(
extended_data_product.computed.active_user_subscriptions,
ComputedListValue)
self.assertIsInstance(
extended_data_product.computed.past_user_subscriptions,
ComputedListValue)
self.assertIsInstance(extended_data_product.computed.last_granule,
ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.is_persisted,
ComputedIntValue)
self.assertIsInstance(
extended_data_product.computed.data_contents_updated,
ComputedStringValue)
self.assertIsInstance(extended_data_product.computed.data_datetime,
ComputedListValue)
# exact text here keeps changing to fit UI capabilities. keep assertion general...
self.assertIn(
'ok',
extended_data_product.computed.last_granule.value['quality_flag'])
self.assertEqual(
2, len(extended_data_product.computed.data_datetime.value))
notifications = extended_data_product.computed.user_notification_requests.value
notification = notifications[0]
self.assertEqual(expected_data_product_id, notification.origin)
self.assertEqual("data product", notification.origin_type)
self.assertEqual('DetectionEvent', notification.event_type)
@attr('LOCOINT')
#@unittest.skip('refactoring')
@unittest.skipIf(not use_es, 'No ElasticSearch')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
@patch.dict(CFG, {'endpoint': {'receive': {'timeout': 90}}})
def test_activateInstrumentSample(self):
self.loggerpids = []
# Create InstrumentModel
instModel_obj = IonObject(RT.InstrumentModel,
name='SBE37IMModel',
description="SBE37IMModel")
instModel_id = self.imsclient.create_instrument_model(instModel_obj)
log.debug('new InstrumentModel id = %s ', instModel_id)
raw_config = StreamConfiguration(stream_name='raw',
parameter_dictionary_name='raw')
parsed_config = StreamConfiguration(
stream_name='parsed',
parameter_dictionary_name='ctd_parsed_param_dict')
# Create InstrumentAgent
instAgent_obj = IonObject(
RT.InstrumentAgent,
name='agent007',
description="SBE37IMAgent",
driver_uri=DRV_URI_GOOD,
stream_configurations=[raw_config, parsed_config])
instAgent_id = self.imsclient.create_instrument_agent(instAgent_obj)
log.debug('new InstrumentAgent id = %s', instAgent_id)
self.imsclient.assign_instrument_model_to_instrument_agent(
instModel_id, instAgent_id)
# Create InstrumentDevice
log.debug(
'test_activateInstrumentSample: Create instrument resource to represent the SBE37 (SA Req: L4-CI-SA-RQ-241) '
)
instDevice_obj = IonObject(RT.InstrumentDevice,
name='SBE37IMDevice',
description="SBE37IMDevice",
serial_number="12345")
instDevice_id = self.imsclient.create_instrument_device(
instrument_device=instDevice_obj)
self.imsclient.assign_instrument_model_to_instrument_device(
instModel_id, instDevice_id)
log.debug(
"test_activateInstrumentSample: new InstrumentDevice id = %s (SA Req: L4-CI-SA-RQ-241) ",
instDevice_id)
port_agent_config = {
'device_addr': CFG.device.sbe37.host,
'device_port': CFG.device.sbe37.port,
'process_type': PortAgentProcessType.UNIX,
'binary_path': "port_agent",
'port_agent_addr': 'localhost',
'command_port': CFG.device.sbe37.port_agent_cmd_port,
'data_port': CFG.device.sbe37.port_agent_data_port,
'log_level': 5,
'type': PortAgentType.ETHERNET
}
instAgentInstance_obj = IonObject(RT.InstrumentAgentInstance,
name='SBE37IMAgentInstance',
description="SBE37IMAgentInstance",
port_agent_config=port_agent_config,
alerts=[])
instAgentInstance_id = self.imsclient.create_instrument_agent_instance(
instAgentInstance_obj, instAgent_id, instDevice_id)
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
parsed_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
parsed_stream_def_id = self.pubsubcli.create_stream_definition(
name='parsed', parameter_dictionary_id=parsed_pdict_id)
raw_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'raw', id_only=True)
raw_stream_def_id = self.pubsubcli.create_stream_definition(
name='raw', parameter_dictionary_id=raw_pdict_id)
#-------------------------------
# Create Raw and Parsed Data Products for the device
#-------------------------------
dp_obj = IonObject(RT.DataProduct,
name='the parsed data',
description='ctd stream test',
temporal_domain=tdom,
spatial_domain=sdom)
data_product_id1 = self.dpclient.create_data_product(
data_product=dp_obj, stream_definition_id=parsed_stream_def_id)
log.debug('new dp_id = %s', data_product_id1)
self.dpclient.activate_data_product_persistence(
data_product_id=data_product_id1)
self.damsclient.assign_data_product(input_resource_id=instDevice_id,
data_product_id=data_product_id1)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id1,
PRED.hasStream, None, True)
log.debug('Data product streams1 = %s', stream_ids)
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id1,
PRED.hasDataset,
RT.Dataset, True)
log.debug('Data set for data_product_id1 = %s', dataset_ids[0])
self.parsed_dataset = dataset_ids[0]
pid = self.create_logger('ctd_parsed', stream_ids[0])
self.loggerpids.append(pid)
dp_obj = IonObject(RT.DataProduct,
name='the raw data',
description='raw stream test',
temporal_domain=tdom,
spatial_domain=sdom)
data_product_id2 = self.dpclient.create_data_product(
data_product=dp_obj, stream_definition_id=raw_stream_def_id)
log.debug('new dp_id = %s', data_product_id2)
self.damsclient.assign_data_product(input_resource_id=instDevice_id,
data_product_id=data_product_id2)
self.dpclient.activate_data_product_persistence(
data_product_id=data_product_id2)
# setup notifications for the device and parsed data product
user_id_1 = self._create_notification(user_name='user_1',
instrument_id=instDevice_id,
product_id=data_product_id1)
#---------- Create notifications for another user and verify that we see different computed subscriptions for the two users ---------
user_id_2 = self._create_notification(user_name='user_2',
instrument_id=instDevice_id,
product_id=data_product_id2)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id2,
PRED.hasStream, None, True)
log.debug('Data product streams2 = %s', str(stream_ids))
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id2,
PRED.hasDataset,
RT.Dataset, True)
log.debug('Data set for data_product_id2 = %s', dataset_ids[0])
self.raw_dataset = dataset_ids[0]
#elastic search debug
es_indexes, _ = self.container.resource_registry.find_resources(
restype='ElasticSearchIndex')
log.debug('ElasticSearch indexes: %s', [i.name for i in es_indexes])
log.debug('Bootstrap %s', CFG.bootstrap.use_es)
def start_instrument_agent():
self.imsclient.start_instrument_agent_instance(
instrument_agent_instance_id=instAgentInstance_id)
gevent.joinall([gevent.spawn(start_instrument_agent)])
#cleanup
self.addCleanup(self.imsclient.stop_instrument_agent_instance,
instrument_agent_instance_id=instAgentInstance_id)
#wait for start
inst_agent_instance_obj = self.imsclient.read_instrument_agent_instance(
instAgentInstance_id)
gate = AgentProcessStateGate(self.processdispatchclient.read_process,
instDevice_id, ProcessStateEnum.RUNNING)
self.assertTrue(
gate. await (30),
"The instrument agent instance (%s) did not spawn in 30 seconds" %
gate.process_id)
#log.trace('Instrument agent instance obj: = %s' , str(inst_agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._ia_client = ResourceAgentClient(instDevice_id,
to_name=gate.process_id,
process=FakeProcess())
log.debug("test_activateInstrumentSample: got ia client %s",
str(self._ia_client))
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
retval = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: initialize %s", str(retval))
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.INACTIVE, state)
log.debug("(L4-CI-SA-RQ-334): Sending go_active command ")
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrument: return value from go_active %s",
str(reply))
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.IDLE, state)
cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
retval = self._ia_client.execute_agent(cmd)
state = retval.result
log.debug(
"(L4-CI-SA-RQ-334): current state after sending go_active command %s",
str(state))
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: run %s", str(reply))
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.COMMAND, state)
cmd = AgentCommand(command=ResourceAgentEvent.PAUSE)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.STOPPED, state)
cmd = AgentCommand(command=ResourceAgentEvent.RESUME)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.COMMAND, state)
cmd = AgentCommand(command=ResourceAgentEvent.CLEAR)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.IDLE, state)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(ResourceAgentState.COMMAND, state)
cmd = AgentCommand(command=SBE37ProtocolEvent.ACQUIRE_SAMPLE)
for i in xrange(10):
retval = self._ia_client.execute_resource(cmd)
log.debug("test_activateInstrumentSample: return from sample %s",
str(retval))
log.debug("test_activateInstrumentSample: calling reset ")
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: return from reset %s",
str(reply))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data_raw = self.dataretrieverclient.retrieve(self.raw_dataset)
self.assertIsInstance(replay_data_raw, Granule)
rdt_raw = RecordDictionaryTool.load_from_granule(replay_data_raw)
log.debug("RDT raw: %s", str(rdt_raw.pretty_print()))
self.assertIn('raw', rdt_raw)
raw_vals = rdt_raw['raw']
all_raw = "".join(raw_vals)
# look for 't' entered after a prompt -- ">t"
t_commands = all_raw.count(">t")
if 10 != t_commands:
log.error("%s raw_vals: ", len(raw_vals))
for i, r in enumerate(raw_vals):
log.error("raw val %s: %s", i, [r])
self.fail("Expected 10 't' strings in raw_vals, got %s" %
t_commands)
else:
log.debug("%s raw_vals: ", len(raw_vals))
for i, r in enumerate(raw_vals):
log.debug("raw val %s: %s", i, [r])
replay_data_parsed = self.dataretrieverclient.retrieve(
self.parsed_dataset)
self.assertIsInstance(replay_data_parsed, Granule)
rdt_parsed = RecordDictionaryTool.load_from_granule(replay_data_parsed)
log.debug("test_activateInstrumentSample: RDT parsed: %s",
str(rdt_parsed.pretty_print()))
self.assertIn('temp', rdt_parsed)
temp_vals = rdt_parsed['temp']
pressure_vals = rdt_parsed['pressure']
if 10 != len(temp_vals):
log.error("%s temp_vals: %s", len(temp_vals), temp_vals)
self.fail("Expected 10 temp_vals, got %s" % len(temp_vals))
log.debug("l4-ci-sa-rq-138")
"""
Physical resource control shall be subject to policy
Instrument management control capabilities shall be subject to policy
The actor accessing the control capabilities must be authorized to send commands.
note from maurice 2012-05-18: Talk to tim M to verify that this is policy. If it is then talk with Stephen to
get an example of a policy test and use that to create a test stub that will be
completed when we have instrument policies.
Tim M: The "actor", aka observatory operator, will access the instrument through ION.
"""
#--------------------------------------------------------------------------------
# Get the extended data product to see if it contains the granules
#--------------------------------------------------------------------------------
extended_product = self.dpclient.get_data_product_extension(
data_product_id=data_product_id1, user_id=user_id_1)
def poller(extended_product):
return len(extended_product.computed.user_notification_requests.
value) == 1
poll(poller, extended_product, timeout=30)
self._check_computed_attributes_of_extended_product(
expected_data_product_id=data_product_id1,
extended_data_product=extended_product)
#--------------------------------------------------------------------------------
# Get the extended instrument
#--------------------------------------------------------------------------------
extended_instrument = self.imsclient.get_instrument_device_extension(
instrument_device_id=instDevice_id, user_id=user_id_1)
#--------------------------------------------------------------------------------
# For the second user, check the extended data product and the extended intrument
#--------------------------------------------------------------------------------
extended_product = self.dpclient.get_data_product_extension(
data_product_id=data_product_id2, user_id=user_id_2)
self._check_computed_attributes_of_extended_product(
expected_data_product_id=data_product_id2,
extended_data_product=extended_product)
#--------------------------------------------------------------------------------
# Get the extended instrument
#--------------------------------------------------------------------------------
extended_instrument = self.imsclient.get_instrument_device_extension(
instrument_device_id=instDevice_id, user_id=user_id_2)
self._check_computed_attributes_of_extended_instrument(
expected_instrument_device_id=instDevice_id,
extended_instrument=extended_instrument)
#--------------------------------------------------------------------------------
# Deactivate loggers
#--------------------------------------------------------------------------------
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
self.dpclient.delete_data_product(data_product_id1)
self.dpclient.delete_data_product(data_product_id2)
class ExhaustiveParameterTest(IonIntegrationTestCase):
def setUp(self):
self.i=0
self._start_container()
self.container.start_rel_from_url('res/deploy/r2params.yml')
self.dataset_management = DatasetManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.resource_registry = self.container.resource_registry
self.data_retriever = DataRetrieverServiceClient()
pdicts, _ = self.resource_registry.find_resources(restype='ParameterDictionary', id_only=False)
self.dp_ids = []
for pdict in pdicts:
stream_def_id = self.pubsub_management.create_stream_definition(pdict.name, parameter_dictionary_id=pdict._id)
dp_id = self.make_dp(stream_def_id)
if dp_id: self.dp_ids.append(dp_id)
def make_dp(self, stream_def_id):
stream_def = self.resource_registry.read(stream_def_id)
dp_obj = DataProduct(
name=stream_def.name,
description=stream_def.name,
processing_level_code='Parsed_Canonical')
data_product_id = self.data_product_management.create_data_product(dp_obj, stream_definition_id=stream_def_id)
self.data_product_management.activate_data_product_persistence(data_product_id)
return data_product_id
def fill_values(self, ptype, size):
if isinstance(ptype, ArrayType):
return ['blah'] * size
elif isinstance(ptype, QuantityType):
return np.sin(np.arange(size, dtype=ptype.value_encoding) * 2 * np.pi / 3)
elif isinstance(ptype, RecordType):
return [{'record': 'ok'}] * size
elif isinstance(ptype, ConstantRangeType):
return (1,1000)
elif isinstance(ptype, ConstantType):
return np.dtype(ptype.value_encoding).type(1)
elif isinstance(ptype, CategoryType):
return ptype.categories.keys()[0]
else:
return
def wait_until_we_have_enough_granules(self, dataset_id='',data_size=40):
'''
Loops until there is a sufficient amount of data in the dataset
'''
done = False
with gevent.Timeout(40):
while not done:
granule = self.data_retriever.retrieve_last_data_points(dataset_id, 1)
rdt = RecordDictionaryTool.load_from_granule(granule)
extents = self.dataset_management.dataset_extents(dataset_id, rdt._pdict.temporal_parameter_name)[0]
if rdt[rdt._pdict.temporal_parameter_name] and rdt[rdt._pdict.temporal_parameter_name][0] != rdt._pdict.get_context(rdt._pdict.temporal_parameter_name).fill_value and extents >= data_size:
done = True
else:
gevent.sleep(0.2)
def write_to_data_product(self,data_product_id):
dataset_ids, _ = self.resource_registry.find_objects(data_product_id, 'hasDataset', id_only=True)
dataset_id = dataset_ids.pop()
stream_ids , _ = self.resource_registry.find_objects(data_product_id, 'hasStream', id_only=True)
stream_id = stream_ids.pop()
stream_def_ids, _ = self.resource_registry.find_objects(stream_id, 'hasStreamDefinition', id_only=True)
stream_def_id = stream_def_ids.pop()
route = self.pubsub_management.read_stream_route(stream_id)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
time_param = rdt._pdict.temporal_parameter_name
if time_param is None:
print '%s has no temporal parameter' % self.resource_registry.read(data_product_id).name
return
rdt[time_param] = np.arange(40)
for field in rdt.fields:
if field == rdt._pdict.temporal_parameter_name:
continue
rdt[field] = self.fill_values(rdt._pdict.get_context(field).param_type,40)
publisher = StandaloneStreamPublisher(stream_id, route)
publisher.publish(rdt.to_granule())
self.wait_until_we_have_enough_granules(dataset_id,40)
granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(granule)
bad = []
for field in rdt.fields:
if not np.array_equal(rdt[field], rdt_out[field]):
print '%s' % field
print '%s != %s' % (rdt[field], rdt_out[field])
bad.append(field)
return bad
def test_data_products(self):
bad_data_products = {}
for dp_id in self.dp_ids:
try:
bad_fields = self.write_to_data_product(dp_id)
if bad_fields:
bad_data_products[dp_id] = "Couldn't write and retrieve %s." % bad_fields
except:
import traceback
bad_data_products[dp_id] = traceback.format_exc()
for dp_id, tb in bad_data_products.iteritems():
print '----------'
print 'Problem with %s' % self.resource_registry.read(dp_id).name
print tb
print '----------'
if bad_data_products:
raise AssertionError('There are bad parameter dictionaries.')
class TestDMEnd2End(IonIntegrationTestCase):
def setUp(self): # Love the non pep-8 convention
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.process_dispatcher = ProcessDispatcherServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.ingestion_management = IngestionManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.pids = []
self.event = Event()
self.exchange_space_name = 'test_granules'
self.exchange_point_name = 'science_data'
self.i = 0
self.purge_queues()
self.queue_buffer = []
self.streams = []
self.addCleanup(self.stop_all_ingestion)
def purge_queues(self):
xn = self.container.ex_manager.create_xn_queue(
'science_granule_ingestion')
xn.purge()
def tearDown(self):
self.purge_queues()
for pid in self.pids:
self.container.proc_manager.terminate_process(pid)
IngestionManagementIntTest.clean_subscriptions()
for queue in self.queue_buffer:
if isinstance(queue, ExchangeNameQueue):
queue.delete()
elif isinstance(queue, str):
xn = self.container.ex_manager.create_xn_queue(queue)
xn.delete()
#--------------------------------------------------------------------------------
# Helper/Utility methods
#--------------------------------------------------------------------------------
def create_dataset(self, parameter_dict_id=''):
'''
Creates a time-series dataset
'''
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
if not parameter_dict_id:
parameter_dict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
dataset_id = self.dataset_management.create_dataset(
'test_dataset_%i' % self.i,
parameter_dictionary_id=parameter_dict_id,
spatial_domain=sdom,
temporal_domain=tdom)
return dataset_id
def get_datastore(self, dataset_id):
'''
Gets an instance of the datastore
This method is primarily used to defeat a bug where integration tests in multiple containers may sometimes
delete a CouchDB datastore and the other containers are unaware of the new state of the datastore.
'''
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(
datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def get_ingestion_config(self):
'''
Grab the ingestion configuration from the resource registry
'''
# The ingestion configuration should have been created by the bootstrap service
# which is configured through r2deploy.yml
ingest_configs, _ = self.resource_registry.find_resources(
restype=RT.IngestionConfiguration, id_only=True)
return ingest_configs[0]
def launch_producer(self, stream_id=''):
'''
Launch the producer
'''
pid = self.container.spawn_process(
'better_data_producer', 'ion.processes.data.example_data_producer',
'BetterDataProducer', {'process': {
'stream_id': stream_id
}})
self.pids.append(pid)
def make_simple_dataset(self):
'''
Makes a stream, a stream definition and a dataset, the essentials for most of these tests
'''
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
stream_def_id = self.pubsub_management.create_stream_definition(
'ctd data', parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream(
'ctd stream %i' % self.i,
'xp1',
stream_definition_id=stream_def_id)
dataset_id = self.create_dataset(pdict_id)
self.get_datastore(dataset_id)
self.i += 1
return stream_id, route, stream_def_id, dataset_id
def publish_hifi(self, stream_id, stream_route, offset=0):
'''
Publish deterministic data
'''
pub = StandaloneStreamPublisher(stream_id, stream_route)
stream_def = self.pubsub_management.read_stream_definition(
stream_id=stream_id)
stream_def_id = stream_def._id
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(10) + (offset * 10)
rdt['temp'] = np.arange(10) + (offset * 10)
pub.publish(rdt.to_granule())
def publish_fake_data(self, stream_id, route):
'''
Make four granules
'''
for i in xrange(4):
self.publish_hifi(stream_id, route, i)
def start_ingestion(self, stream_id, dataset_id):
'''
Starts ingestion/persistence for a given dataset
'''
ingest_config_id = self.get_ingestion_config()
self.ingestion_management.persist_data_stream(
stream_id=stream_id,
ingestion_configuration_id=ingest_config_id,
dataset_id=dataset_id)
def stop_ingestion(self, stream_id):
ingest_config_id = self.get_ingestion_config()
self.ingestion_management.unpersist_data_stream(
stream_id=stream_id, ingestion_configuration_id=ingest_config_id)
def stop_all_ingestion(self):
try:
[self.stop_ingestion(sid) for sid in self.streams]
except:
pass
def validate_granule_subscription(self, msg, route, stream_id):
'''
Validation for granule format
'''
if msg == {}:
return
rdt = RecordDictionaryTool.load_from_granule(msg)
log.info('%s', rdt.pretty_print())
self.assertIsInstance(
msg, Granule, 'Message is improperly formatted. (%s)' % type(msg))
self.event.set()
def wait_until_we_have_enough_granules(self, dataset_id='', data_size=40):
'''
Loops until there is a sufficient amount of data in the dataset
'''
done = False
with gevent.Timeout(40):
while not done:
extents = self.dataset_management.dataset_extents(
dataset_id, 'time')[0]
granule = self.data_retriever.retrieve_last_data_points(
dataset_id, 1)
rdt = RecordDictionaryTool.load_from_granule(granule)
if rdt['time'] and rdt['time'][0] != rdt._pdict.get_context(
'time').fill_value and extents >= data_size:
done = True
else:
gevent.sleep(0.2)
#--------------------------------------------------------------------------------
# Test Methods
#--------------------------------------------------------------------------------
@attr('SMOKE')
def test_dm_end_2_end(self):
#--------------------------------------------------------------------------------
# Set up a stream and have a mock instrument (producer) send data
#--------------------------------------------------------------------------------
self.event.clear()
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(
pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext('binary', param_type=ArrayType())
context_ids.append(
self.dataset_management.create_parameter_context(
'binary', bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext('records', param_type=RecordType())
context_ids.append(
self.dataset_management.create_parameter_context(
'records', rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary(
'replay_pdict',
parameter_context_ids=context_ids,
temporal_context='time')
stream_definition = self.pubsub_management.create_stream_definition(
'ctd data', parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream(
'producer',
exchange_point=self.exchange_point_name,
stream_definition_id=stream_definition)
#--------------------------------------------------------------------------------
# Start persisting the data on the stream
# - Get the ingestion configuration from the resource registry
# - Create the dataset
# - call persist_data_stream to setup the subscription for the ingestion workers
# on the stream that you specify which causes the data to be persisted
#--------------------------------------------------------------------------------
ingest_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(
stream_id=stream_id,
ingestion_configuration_id=ingest_config_id,
dataset_id=dataset_id)
#--------------------------------------------------------------------------------
# Now the granules are ingesting and persisted
#--------------------------------------------------------------------------------
self.launch_producer(stream_id)
self.wait_until_we_have_enough_granules(dataset_id, 40)
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_id)
self.assertIsInstance(replay_data, Granule)
rdt = RecordDictionaryTool.load_from_granule(replay_data)
self.assertTrue((rdt['time'][:10] == np.arange(10)).all(),
'%s' % rdt['time'][:])
self.assertTrue((rdt['binary'][:10] == np.array(['hi'] * 10,
dtype='object')).all())
#--------------------------------------------------------------------------------
# Now to try the streamed approach
#--------------------------------------------------------------------------------
replay_stream_id, replay_route = self.pubsub_management.create_stream(
'replay_out',
exchange_point=self.exchange_point_name,
stream_definition_id=stream_definition)
self.replay_id, process_id = self.data_retriever.define_replay(
dataset_id=dataset_id, stream_id=replay_stream_id)
log.info('Process ID: %s', process_id)
replay_client = ReplayClient(process_id)
#--------------------------------------------------------------------------------
# Create the listening endpoint for the the retriever to talk to
#--------------------------------------------------------------------------------
xp = self.container.ex_manager.create_xp(self.exchange_point_name)
subscriber = StandaloneStreamSubscriber(
self.exchange_space_name, self.validate_granule_subscription)
self.queue_buffer.append(self.exchange_space_name)
subscriber.start()
subscriber.xn.bind(replay_route.routing_key, xp)
self.data_retriever.start_replay_agent(self.replay_id)
self.assertTrue(replay_client.await_agent_ready(5),
'The process never launched')
replay_client.start_replay()
self.assertTrue(self.event.wait(10))
subscriber.stop()
self.data_retriever.cancel_replay_agent(self.replay_id)
#--------------------------------------------------------------------------------
# Test the slicing capabilities
#--------------------------------------------------------------------------------
granule = self.data_retriever.retrieve(dataset_id=dataset_id,
query={'tdoa': slice(0, 5)})
rdt = RecordDictionaryTool.load_from_granule(granule)
b = rdt['time'] == np.arange(5)
self.assertTrue(b.all() if not isinstance(b, bool) else b)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
@unittest.skip('Doesnt work')
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_replay_pause(self):
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(
pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext('binary', param_type=ArrayType())
context_ids.append(
self.dataset_management.create_parameter_context(
'binary', bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext('records', param_type=RecordType())
context_ids.append(
self.dataset_management.create_parameter_context(
'records', rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary(
'replay_pdict',
parameter_context_ids=context_ids,
temporal_context='time')
stream_def_id = self.pubsub_management.create_stream_definition(
'replay_stream', parameter_dictionary_id=pdict_id)
replay_stream, replay_route = self.pubsub_management.create_stream(
'replay', 'xp1', stream_definition_id=stream_def_id)
dataset_id = self.create_dataset(pdict_id)
scov = DatasetManagementService._get_coverage(dataset_id)
bb = CoverageCraft(scov)
bb.rdt['time'] = np.arange(100)
bb.rdt['temp'] = np.random.random(100) + 30
bb.sync_with_granule()
DatasetManagementService._persist_coverage(
dataset_id,
bb.coverage) # This invalidates it for multi-host configurations
# Set up the subscriber to verify the data
subscriber = StandaloneStreamSubscriber(
self.exchange_space_name, self.validate_granule_subscription)
xp = self.container.ex_manager.create_xp('xp1')
self.queue_buffer.append(self.exchange_space_name)
subscriber.start()
subscriber.xn.bind(replay_route.routing_key, xp)
# Set up the replay agent and the client wrapper
# 1) Define the Replay (dataset and stream to publish on)
self.replay_id, process_id = self.data_retriever.define_replay(
dataset_id=dataset_id, stream_id=replay_stream)
# 2) Make a client to the interact with the process (optionall provide it a process to bind with)
replay_client = ReplayClient(process_id)
# 3) Start the agent (launch the process)
self.data_retriever.start_replay_agent(self.replay_id)
# 4) Start replaying...
replay_client.start_replay()
# Wait till we get some granules
self.assertTrue(self.event.wait(5))
# We got granules, pause the replay, clear the queue and allow the process to finish consuming
replay_client.pause_replay()
gevent.sleep(1)
subscriber.xn.purge()
self.event.clear()
# Make sure there's no remaining messages being consumed
self.assertFalse(self.event.wait(1))
# Resume the replay and wait until we start getting granules again
replay_client.resume_replay()
self.assertTrue(self.event.wait(5))
# Stop the replay, clear the queues
replay_client.stop_replay()
gevent.sleep(1)
subscriber.xn.purge()
self.event.clear()
# Make sure that it did indeed stop
self.assertFalse(self.event.wait(1))
subscriber.stop()
def test_retrieve_and_transform(self):
# Make a simple dataset and start ingestion, pretty standard stuff.
ctd_stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset(
)
self.start_ingestion(ctd_stream_id, dataset_id)
# Stream definition for the salinity data
salinity_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
sal_stream_def_id = self.pubsub_management.create_stream_definition(
'sal data', parameter_dictionary_id=salinity_pdict_id)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(10)
rdt['temp'] = np.random.randn(10) * 10 + 30
rdt['conductivity'] = np.random.randn(10) * 2 + 10
rdt['pressure'] = np.random.randn(10) * 1 + 12
publisher = StandaloneStreamPublisher(ctd_stream_id, route)
publisher.publish(rdt.to_granule())
rdt['time'] = np.arange(10, 20)
publisher.publish(rdt.to_granule())
self.wait_until_we_have_enough_granules(dataset_id, 20)
granule = self.data_retriever.retrieve(
dataset_id,
None,
None,
'ion.processes.data.transforms.ctd.ctd_L2_salinity',
'CTDL2SalinityTransformAlgorithm',
kwargs=dict(params=sal_stream_def_id))
rdt = RecordDictionaryTool.load_from_granule(granule)
for i in rdt['salinity']:
self.assertNotEquals(i, 0)
self.streams.append(ctd_stream_id)
self.stop_ingestion(ctd_stream_id)
def test_last_granule(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset(
)
self.start_ingestion(stream_id, dataset_id)
self.publish_hifi(stream_id, route, 0)
self.publish_hifi(stream_id, route, 1)
self.wait_until_we_have_enough_granules(dataset_id,
20) # I just need two
success = False
def verifier():
replay_granule = self.data_retriever.retrieve_last_data_points(
dataset_id, 10)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(10) + 10
if not isinstance(comp, bool):
return comp.all()
return False
success = poll(verifier)
self.assertTrue(success)
success = False
def verify_points():
replay_granule = self.data_retriever.retrieve_last_data_points(
dataset_id, 5)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(15, 20)
if not isinstance(comp, bool):
return comp.all()
return False
success = poll(verify_points)
self.assertTrue(success)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
def test_replay_with_parameters(self):
#--------------------------------------------------------------------------------
# Create the configurations and the dataset
#--------------------------------------------------------------------------------
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(
pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext('binary', param_type=ArrayType())
context_ids.append(
self.dataset_management.create_parameter_context(
'binary', bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext('records', param_type=RecordType())
context_ids.append(
self.dataset_management.create_parameter_context(
'records', rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary(
'replay_pdict',
parameter_context_ids=context_ids,
temporal_context='time')
stream_def_id = self.pubsub_management.create_stream_definition(
'replay_stream', parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream(
'replay_with_params',
exchange_point=self.exchange_point_name,
stream_definition_id=stream_def_id)
config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(
stream_id=stream_id,
ingestion_configuration_id=config_id,
dataset_id=dataset_id)
dataset_modified = Event()
def cb(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified,
callback=cb,
origin=dataset_id)
es.start()
self.addCleanup(es.stop)
self.publish_fake_data(stream_id, route)
self.assertTrue(dataset_modified.wait(30))
query = {
'start_time': 0 - 2208988800,
'end_time': 20 - 2208988800,
'stride_time': 2,
'parameters': ['time', 'temp']
}
retrieved_data = self.data_retriever.retrieve(dataset_id=dataset_id,
query=query)
rdt = RecordDictionaryTool.load_from_granule(retrieved_data)
comp = np.arange(0, 20, 2) == rdt['time']
self.assertTrue(comp.all(), '%s' % rdt.pretty_print())
self.assertEquals(set(rdt.iterkeys()), set(['time', 'temp']))
extents = self.dataset_management.dataset_extents(
dataset_id=dataset_id, parameters=['time', 'temp'])
self.assertTrue(extents['time'] >= 20)
self.assertTrue(extents['temp'] >= 20)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
def test_repersist_data(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset(
)
self.start_ingestion(stream_id, dataset_id)
self.publish_hifi(stream_id, route, 0)
self.publish_hifi(stream_id, route, 1)
self.wait_until_we_have_enough_granules(dataset_id, 20)
config_id = self.get_ingestion_config()
self.ingestion_management.unpersist_data_stream(
stream_id=stream_id, ingestion_configuration_id=config_id)
self.ingestion_management.persist_data_stream(
stream_id=stream_id,
ingestion_configuration_id=config_id,
dataset_id=dataset_id)
self.publish_hifi(stream_id, route, 2)
self.publish_hifi(stream_id, route, 3)
self.wait_until_we_have_enough_granules(dataset_id, 40)
success = False
with gevent.timeout.Timeout(5):
while not success:
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(0, 40)
if not isinstance(comp, bool):
success = comp.all()
gevent.sleep(1)
self.assertTrue(success)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
@attr('LOCOINT')
@unittest.skipIf(os.getenv(
'CEI_LAUNCH_TEST', False
), 'Host requires file-system access to coverage files, CEI mode does not support.'
)
def test_correct_time(self):
# There are 2208988800 seconds between Jan 1 1900 and Jan 1 1970, i.e.
# the conversion factor between unix and NTP time
unix_now = np.floor(time.time())
ntp_now = unix_now + 2208988800
unix_ago = unix_now - 20
ntp_ago = unix_ago + 2208988800
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset(
)
coverage = DatasetManagementService._get_coverage(dataset_id)
coverage.insert_timesteps(20)
coverage.set_parameter_values('time', np.arange(ntp_ago, ntp_now))
temporal_bounds = self.dataset_management.dataset_temporal_bounds(
dataset_id)
self.assertTrue(np.abs(temporal_bounds[0] - unix_ago) < 2)
self.assertTrue(np.abs(temporal_bounds[1] - unix_now) < 2)
@attr('LOCOINT')
@unittest.skipIf(os.getenv(
'CEI_LAUNCH_TEST', False
), 'Host requires file-system access to coverage files, CEI mode does not support.'
)
def test_empty_coverage_time(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset(
)
coverage = DatasetManagementService._get_coverage(dataset_id)
temporal_bounds = self.dataset_management.dataset_temporal_bounds(
dataset_id)
self.assertEquals([coverage.get_parameter_context('time').fill_value] *
2, temporal_bounds)
@attr('LOCOINT')
@unittest.skipIf(os.getenv(
'CEI_LAUNCH_TEST', False
), 'Host requires file-system access to coverage files, CEI mode does not support.'
)
def test_out_of_band_retrieve(self):
# Setup the environemnt
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset(
)
self.start_ingestion(stream_id, dataset_id)
# Fill the dataset
self.publish_fake_data(stream_id, route)
self.wait_until_we_have_enough_granules(dataset_id, 40)
# Retrieve the data
granule = DataRetrieverService.retrieve_oob(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
self.assertTrue((rdt['time'] == np.arange(40)).all())
@attr('LOCOINT')
@unittest.skipIf(os.getenv(
'CEI_LAUNCH_TEST', False
), 'Host requires file-system access to coverage files, CEI mode does not support.'
)
def test_retrieve_cache(self):
DataRetrieverService._refresh_interval = 1
datasets = [self.make_simple_dataset() for i in xrange(10)]
for stream_id, route, stream_def_id, dataset_id in datasets:
coverage = DatasetManagementService._get_coverage(dataset_id)
coverage.insert_timesteps(10)
coverage.set_parameter_values('time', np.arange(10))
coverage.set_parameter_values('temp', np.arange(10))
# Verify cache hit and refresh
dataset_ids = [i[3] for i in datasets]
self.assertTrue(
dataset_ids[0] not in DataRetrieverService._retrieve_cache)
DataRetrieverService._get_coverage(dataset_ids[0]) # Hit the chache
cov, age = DataRetrieverService._retrieve_cache[dataset_ids[0]]
# Verify that it was hit and it's now in there
self.assertTrue(dataset_ids[0] in DataRetrieverService._retrieve_cache)
gevent.sleep(DataRetrieverService._refresh_interval + 0.2)
DataRetrieverService._get_coverage(dataset_ids[0]) # Hit the chache
cov, age2 = DataRetrieverService._retrieve_cache[dataset_ids[0]]
self.assertTrue(age2 != age)
for dataset_id in dataset_ids:
DataRetrieverService._get_coverage(dataset_id)
self.assertTrue(
dataset_ids[0] not in DataRetrieverService._retrieve_cache)
stream_id, route, stream_def, dataset_id = datasets[0]
self.start_ingestion(stream_id, dataset_id)
DataRetrieverService._get_coverage(dataset_id)
self.assertTrue(dataset_id in DataRetrieverService._retrieve_cache)
DataRetrieverService._refresh_interval = 100
self.publish_hifi(stream_id, route, 1)
self.wait_until_we_have_enough_granules(dataset_id, data_size=20)
event = gevent.event.Event()
with gevent.Timeout(20):
while not event.wait(0.1):
if dataset_id not in DataRetrieverService._retrieve_cache:
event.set()
self.assertTrue(event.is_set())
@unittest.skip('Outdated due to ingestion retry')
@attr('LOCOINT')
@unittest.skipIf(os.getenv(
'CEI_LAUNCH_TEST', False
), 'Host requires file-system access to coverage files, CEI mode does not support.'
)
def test_ingestion_failover(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset(
)
self.start_ingestion(stream_id, dataset_id)
event = Event()
def cb(*args, **kwargs):
event.set()
sub = EventSubscriber(event_type="ExceptionEvent",
callback=cb,
origin="stream_exception")
sub.start()
self.publish_fake_data(stream_id, route)
self.wait_until_we_have_enough_granules(dataset_id, 40)
file_path = DatasetManagementService._get_coverage_path(dataset_id)
master_file = os.path.join(file_path, '%s_master.hdf5' % dataset_id)
with open(master_file, 'w') as f:
f.write('this will crash HDF')
self.publish_hifi(stream_id, route, 5)
self.assertTrue(event.wait(10))
sub.stop()
class TestActivateInstrumentIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
super(TestActivateInstrumentIntegration, self).setUp()
config = DotDict()
config.bootstrap.use_es = True
self._start_container()
self.addCleanup(TestActivateInstrumentIntegration.es_cleanup)
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(
node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(
node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
self.usernotificationclient = UserNotificationServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
self.event_publisher = EventPublisher()
@staticmethod
def es_cleanup():
es_host = CFG.get_safe('server.elasticsearch.host', 'localhost')
es_port = CFG.get_safe('server.elasticsearch.port', '9200')
es = ep.ElasticSearch(host=es_host, port=es_port, timeout=10)
indexes = STD_INDEXES.keys()
indexes.append('%s_resources_index' % get_sys_name().lower())
indexes.append('%s_events_index' % get_sys_name().lower())
for index in indexes:
IndexManagementService._es_call(es.river_couchdb_delete, index)
IndexManagementService._es_call(es.index_delete, index)
def create_logger(self, name, stream_id=''):
# logger process
producer_definition = ProcessDefinition(name=name + '_logger')
producer_definition.executable = {
'module': 'ion.processes.data.stream_granule_logger',
'class': 'StreamGranuleLogger'
}
logger_procdef_id = self.processdispatchclient.create_process_definition(
process_definition=producer_definition)
configuration = {
'process': {
'stream_id': stream_id,
}
}
pid = self.processdispatchclient.schedule_process(
process_definition_id=logger_procdef_id,
configuration=configuration)
return pid
def _create_notification(self,
user_name='',
instrument_id='',
product_id=''):
#--------------------------------------------------------------------------------------
# Make notification request objects
#--------------------------------------------------------------------------------------
notification_request_1 = NotificationRequest(
name='notification_1',
origin=instrument_id,
origin_type="instrument",
event_type='ResourceLifecycleEvent')
notification_request_2 = NotificationRequest(
name='notification_2',
origin=product_id,
origin_type="data product",
event_type='DetectionEvent')
#--------------------------------------------------------------------------------------
# Create a user and get the user_id
#--------------------------------------------------------------------------------------
user = UserInfo()
user.name = user_name
user.contact.email = '*****@*****.**' % user_name
user_id, _ = self.rrclient.create(user)
#--------------------------------------------------------------------------------------
# Create notification
#--------------------------------------------------------------------------------------
self.usernotificationclient.create_notification(
notification=notification_request_1, user_id=user_id)
self.usernotificationclient.create_notification(
notification=notification_request_2, user_id=user_id)
log.debug(
"test_activateInstrumentSample: create_user_notifications user_id %s",
str(user_id))
return user_id
def get_datastore(self, dataset_id):
dataset = self.datasetclient.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(
datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def _check_computed_attributes_of_extended_instrument(
self, expected_instrument_device_id='', extended_instrument=None):
# Verify that computed attributes exist for the extended instrument
self.assertIsInstance(extended_instrument.computed.firmware_version,
ComputedFloatValue)
self.assertIsInstance(
extended_instrument.computed.last_data_received_datetime,
ComputedFloatValue)
self.assertIsInstance(
extended_instrument.computed.last_calibration_datetime,
ComputedFloatValue)
self.assertIsInstance(extended_instrument.computed.uptime,
ComputedStringValue)
self.assertIsInstance(
extended_instrument.computed.power_status_roll_up,
ComputedIntValue)
self.assertIsInstance(
extended_instrument.computed.communications_status_roll_up,
ComputedIntValue)
self.assertIsInstance(extended_instrument.computed.data_status_roll_up,
ComputedIntValue)
self.assertIsInstance(
extended_instrument.computed.location_status_roll_up,
ComputedIntValue)
# the following assert will not work without elasticsearch.
#self.assertEqual( 1, len(extended_instrument.computed.user_notification_requests.value) )
self.assertEqual(
extended_instrument.computed.communications_status_roll_up.value,
StatusType.STATUS_WARNING)
self.assertEqual(
extended_instrument.computed.data_status_roll_up.value,
StatusType.STATUS_OK)
self.assertEqual(
extended_instrument.computed.power_status_roll_up.value,
StatusType.STATUS_WARNING)
# Verify the computed attribute for user notification requests
self.assertEqual(
1,
len(extended_instrument.computed.user_notification_requests.value))
notifications = extended_instrument.computed.user_notification_requests.value
notification = notifications[0]
self.assertEqual(notification.origin, expected_instrument_device_id)
self.assertEqual(notification.origin_type, "instrument")
self.assertEqual(notification.event_type, 'ResourceLifecycleEvent')
def _check_computed_attributes_of_extended_product(
self, expected_data_product_id='', extended_data_product=None):
self.assertEqual(expected_data_product_id, extended_data_product._id)
log.debug("extended_data_product.computed: %s",
extended_data_product.computed)
# Verify that computed attributes exist for the extended instrument
self.assertIsInstance(
extended_data_product.computed.product_download_size_estimated,
ComputedIntValue)
self.assertIsInstance(
extended_data_product.computed.number_active_subscriptions,
ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.data_url,
ComputedStringValue)
self.assertIsInstance(extended_data_product.computed.stored_data_size,
ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.recent_granules,
ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.parameters,
ComputedListValue)
self.assertIsInstance(extended_data_product.computed.recent_events,
ComputedEventListValue)
self.assertIsInstance(extended_data_product.computed.provenance,
ComputedDictValue)
self.assertIsInstance(
extended_data_product.computed.user_notification_requests,
ComputedListValue)
self.assertIsInstance(
extended_data_product.computed.active_user_subscriptions,
ComputedListValue)
self.assertIsInstance(
extended_data_product.computed.past_user_subscriptions,
ComputedListValue)
self.assertIsInstance(extended_data_product.computed.last_granule,
ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.is_persisted,
ComputedIntValue)
self.assertIsInstance(
extended_data_product.computed.data_contents_updated,
ComputedStringValue)
self.assertIsInstance(extended_data_product.computed.data_datetime,
ComputedListValue)
# exact text here keeps changing to fit UI capabilities. keep assertion general...
self.assertTrue('ok' in extended_data_product.computed.last_granule.
value['quality_flag'])
self.assertEqual(
2, len(extended_data_product.computed.data_datetime.value))
notifications = extended_data_product.computed.user_notification_requests.value
notification = notifications[0]
self.assertEqual(notification.origin, expected_data_product_id)
self.assertEqual(notification.origin_type, "data product")
self.assertEqual(notification.event_type, 'DetectionEvent')
@attr('LOCOINT')
@unittest.skipIf(not use_es, 'No ElasticSearch')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
@patch.dict(CFG, {'endpoint': {'receive': {'timeout': 60}}})
def test_activateInstrumentSample(self):
self.loggerpids = []
# Create InstrumentModel
instModel_obj = IonObject(RT.InstrumentModel,
name='SBE37IMModel',
description="SBE37IMModel")
instModel_id = self.imsclient.create_instrument_model(instModel_obj)
log.debug('new InstrumentModel id = %s ', instModel_id)
#Create stream alarms
"""
test_two_sided_interval
Test interval alarm and alarm event publishing for a closed
inteval.
"""
# kwargs = {
# 'name' : 'test_sim_warning',
# 'stream_name' : 'parsed',
# 'value_id' : 'temp',
# 'message' : 'Temperature is above test range of 5.0.',
# 'type' : StreamAlarmType.WARNING,
# 'upper_bound' : 5.0,
# 'upper_rel_op' : '<'
# }
kwargs = {
'name': 'temperature_warning_interval',
'stream_name': 'parsed',
'value_id': 'temp',
'message':
'Temperature is below the normal range of 50.0 and above.',
'type': StreamAlarmType.WARNING,
'lower_bound': 50.0,
'lower_rel_op': '<'
}
# Create alarm object.
alarm = {}
alarm['type'] = 'IntervalAlarmDef'
alarm['kwargs'] = kwargs
raw_config = StreamConfiguration(
stream_name='raw',
parameter_dictionary_name='ctd_raw_param_dict',
records_per_granule=2,
granule_publish_rate=5)
parsed_config = StreamConfiguration(
stream_name='parsed',
parameter_dictionary_name='ctd_parsed_param_dict',
records_per_granule=2,
granule_publish_rate=5,
alarms=[alarm])
# Create InstrumentAgent
instAgent_obj = IonObject(
RT.InstrumentAgent,
name='agent007',
description="SBE37IMAgent",
driver_uri=
"http://sddevrepo.oceanobservatories.org/releases/seabird_sbe37smb_ooicore-0.0.1a-py2.7.egg",
stream_configurations=[raw_config, parsed_config])
instAgent_id = self.imsclient.create_instrument_agent(instAgent_obj)
log.debug('new InstrumentAgent id = %s', instAgent_id)
self.imsclient.assign_instrument_model_to_instrument_agent(
instModel_id, instAgent_id)
# Create InstrumentDevice
log.debug(
'test_activateInstrumentSample: Create instrument resource to represent the SBE37 (SA Req: L4-CI-SA-RQ-241) '
)
instDevice_obj = IonObject(RT.InstrumentDevice,
name='SBE37IMDevice',
description="SBE37IMDevice",
serial_number="12345")
instDevice_id = self.imsclient.create_instrument_device(
instrument_device=instDevice_obj)
self.imsclient.assign_instrument_model_to_instrument_device(
instModel_id, instDevice_id)
log.debug(
"test_activateInstrumentSample: new InstrumentDevice id = %s (SA Req: L4-CI-SA-RQ-241) ",
instDevice_id)
port_agent_config = {
'device_addr': CFG.device.sbe37.host,
'device_port': CFG.device.sbe37.port,
'process_type': PortAgentProcessType.UNIX,
'binary_path': "port_agent",
'port_agent_addr': 'localhost',
'command_port': CFG.device.sbe37.port_agent_cmd_port,
'data_port': CFG.device.sbe37.port_agent_data_port,
'log_level': 5,
'type': PortAgentType.ETHERNET
}
instAgentInstance_obj = IonObject(RT.InstrumentAgentInstance,
name='SBE37IMAgentInstance',
description="SBE37IMAgentInstance",
port_agent_config=port_agent_config)
instAgentInstance_id = self.imsclient.create_instrument_agent_instance(
instAgentInstance_obj, instAgent_id, instDevice_id)
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
parsed_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
parsed_stream_def_id = self.pubsubcli.create_stream_definition(
name='parsed', parameter_dictionary_id=parsed_pdict_id)
raw_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_raw_param_dict', id_only=True)
raw_stream_def_id = self.pubsubcli.create_stream_definition(
name='raw', parameter_dictionary_id=raw_pdict_id)
#-------------------------------
# Create Raw and Parsed Data Products for the device
#-------------------------------
dp_obj = IonObject(RT.DataProduct,
name='the parsed data',
description='ctd stream test',
temporal_domain=tdom,
spatial_domain=sdom)
data_product_id1 = self.dpclient.create_data_product(
data_product=dp_obj, stream_definition_id=parsed_stream_def_id)
log.debug('new dp_id = %s', data_product_id1)
self.dpclient.activate_data_product_persistence(
data_product_id=data_product_id1)
self.damsclient.assign_data_product(input_resource_id=instDevice_id,
data_product_id=data_product_id1)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id1,
PRED.hasStream, None, True)
log.debug('Data product streams1 = %s', stream_ids)
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id1,
PRED.hasDataset,
RT.Dataset, True)
log.debug('Data set for data_product_id1 = %s', dataset_ids[0])
self.parsed_dataset = dataset_ids[0]
pid = self.create_logger('ctd_parsed', stream_ids[0])
self.loggerpids.append(pid)
dp_obj = IonObject(RT.DataProduct,
name='the raw data',
description='raw stream test',
temporal_domain=tdom,
spatial_domain=sdom)
data_product_id2 = self.dpclient.create_data_product(
data_product=dp_obj, stream_definition_id=raw_stream_def_id)
log.debug('new dp_id = %s', data_product_id2)
self.damsclient.assign_data_product(input_resource_id=instDevice_id,
data_product_id=data_product_id2)
self.dpclient.activate_data_product_persistence(
data_product_id=data_product_id2)
# setup notifications for the device and parsed data product
user_id_1 = self._create_notification(user_name='user_1',
instrument_id=instDevice_id,
product_id=data_product_id1)
#---------- Create notifications for another user and verify that we see different computed subscriptions for the two users ---------
user_id_2 = self._create_notification(user_name='user_2',
instrument_id=instDevice_id,
product_id=data_product_id2)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id2,
PRED.hasStream, None, True)
log.debug('Data product streams2 = %s', str(stream_ids))
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id2,
PRED.hasDataset,
RT.Dataset, True)
log.debug('Data set for data_product_id2 = %s', dataset_ids[0])
self.raw_dataset = dataset_ids[0]
#elastic search debug
es_indexes, _ = self.container.resource_registry.find_resources(
restype='ElasticSearchIndex')
log.debug('ElasticSearch indexes: %s', [i.name for i in es_indexes])
log.debug('Bootstrap %s', CFG.bootstrap.use_es)
def start_instrument_agent():
self.imsclient.start_instrument_agent_instance(
instrument_agent_instance_id=instAgentInstance_id)
gevent.joinall([gevent.spawn(start_instrument_agent)])
#setup a subscriber to alarm events from the device
self._events_received = []
self._event_count = 0
self._samples_out_of_range = 0
self._samples_complete = False
self._async_sample_result = AsyncResult()
def consume_event(*args, **kwargs):
log.debug(
'TestActivateInstrument recieved ION event: args=%s, kwargs=%s, event=%s.',
str(args), str(kwargs), str(args[0]))
self._events_received.append(args[0])
self._event_count = len(self._events_received)
self._async_sample_result.set()
self._event_subscriber = EventSubscriber(
event_type=
'StreamWarningAlarmEvent', #'StreamWarningAlarmEvent', # StreamAlarmEvent
callback=consume_event,
origin=instDevice_id)
self._event_subscriber.start()
#cleanup
self.addCleanup(self.imsclient.stop_instrument_agent_instance,
instrument_agent_instance_id=instAgentInstance_id)
def stop_subscriber():
self._event_subscriber.stop()
self._event_subscriber = None
self.addCleanup(stop_subscriber)
#wait for start
inst_agent_instance_obj = self.imsclient.read_instrument_agent_instance(
instAgentInstance_id)
gate = ProcessStateGate(self.processdispatchclient.read_process,
inst_agent_instance_obj.agent_process_id,
ProcessStateEnum.RUNNING)
self.assertTrue(
gate. await (30),
"The instrument agent instance (%s) did not spawn in 30 seconds" %
inst_agent_instance_obj.agent_process_id)
log.debug('Instrument agent instance obj: = %s',
str(inst_agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._ia_client = ResourceAgentClient(
instDevice_id,
to_name=inst_agent_instance_obj.agent_process_id,
process=FakeProcess())
log.debug("test_activateInstrumentSample: got ia client %s",
str(self._ia_client))
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
retval = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: initialize %s", str(retval))
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
log.debug("(L4-CI-SA-RQ-334): Sending go_active command ")
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrument: return value from go_active %s",
str(reply))
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
retval = self._ia_client.execute_agent(cmd)
state = retval.result
log.debug(
"(L4-CI-SA-RQ-334): current state after sending go_active command %s",
str(state))
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: run %s", str(reply))
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.PAUSE)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.STOPPED)
cmd = AgentCommand(command=ResourceAgentEvent.RESUME)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.CLEAR)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=SBE37ProtocolEvent.ACQUIRE_SAMPLE)
for i in xrange(10):
retval = self._ia_client.execute_resource(cmd)
log.debug("test_activateInstrumentSample: return from sample %s",
str(retval))
log.debug("test_activateInstrumentSample: calling reset ")
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: return from reset %s",
str(reply))
self._samples_complete = True
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.dataretrieverclient.retrieve(self.parsed_dataset)
self.assertIsInstance(replay_data, Granule)
rdt = RecordDictionaryTool.load_from_granule(replay_data)
log.debug("test_activateInstrumentSample: RDT parsed: %s",
str(rdt.pretty_print()))
temp_vals = rdt['temp']
self.assertEquals(len(temp_vals), 10)
log.debug("test_activateInstrumentSample: all temp_vals: %s",
temp_vals)
#out_of_range_temp_vals = [i for i in temp_vals if i > 5]
out_of_range_temp_vals = [i for i in temp_vals if i < 50.0]
log.debug("test_activateInstrumentSample: Out_of_range_temp_vals: %s",
out_of_range_temp_vals)
self._samples_out_of_range = len(out_of_range_temp_vals)
# if no bad values were produced, then do not wait for an event
if self._samples_out_of_range == 0:
self._async_sample_result.set()
log.debug("test_activateInstrumentSample: _events_received: %s",
self._events_received)
log.debug("test_activateInstrumentSample: _event_count: %s",
self._event_count)
self._async_sample_result.get(timeout=CFG.endpoint.receive.timeout)
replay_data = self.dataretrieverclient.retrieve(self.raw_dataset)
self.assertIsInstance(replay_data, Granule)
rdt = RecordDictionaryTool.load_from_granule(replay_data)
log.debug("RDT raw: %s", str(rdt.pretty_print()))
raw_vals = rdt['raw']
self.assertEquals(len(raw_vals), 10)
log.debug("l4-ci-sa-rq-138")
"""
Physical resource control shall be subject to policy
Instrument management control capabilities shall be subject to policy
The actor accessing the control capabilities must be authorized to send commands.
note from maurice 2012-05-18: Talk to tim M to verify that this is policy. If it is then talk with Stephen to
get an example of a policy test and use that to create a test stub that will be
completed when we have instrument policies.
Tim M: The "actor", aka observatory operator, will access the instrument through ION.
"""
#--------------------------------------------------------------------------------
# Get the extended data product to see if it contains the granules
#--------------------------------------------------------------------------------
extended_product = self.dpclient.get_data_product_extension(
data_product_id=data_product_id1, user_id=user_id_1)
def poller(extended_product):
return len(extended_product.computed.user_notification_requests.
value) == 1
poll(poller, extended_product, timeout=30)
self._check_computed_attributes_of_extended_product(
expected_data_product_id=data_product_id1,
extended_data_product=extended_product)
#--------------------------------------------------------------------------------
#put some events into the eventsdb to test - this should set the comms and data status to WARNING
#--------------------------------------------------------------------------------
t = get_ion_ts()
self.event_publisher.publish_event(ts_created=t,
event_type='DeviceStatusEvent',
origin=instDevice_id,
state=DeviceStatusType.OUT_OF_RANGE,
values=[200])
self.event_publisher.publish_event(
ts_created=t,
event_type='DeviceCommsEvent',
origin=instDevice_id,
state=DeviceCommsType.DATA_DELIVERY_INTERRUPTION,
lapse_interval_seconds=20)
#--------------------------------------------------------------------------------
# Get the extended instrument
#--------------------------------------------------------------------------------
extended_instrument = self.imsclient.get_instrument_device_extension(
instrument_device_id=instDevice_id, user_id=user_id_1)
self._check_computed_attributes_of_extended_instrument(
expected_instrument_device_id=instDevice_id,
extended_instrument=extended_instrument)
#--------------------------------------------------------------------------------
# For the second user, check the extended data product and the extended intrument
#--------------------------------------------------------------------------------
extended_product = self.dpclient.get_data_product_extension(
data_product_id=data_product_id2, user_id=user_id_2)
self._check_computed_attributes_of_extended_product(
expected_data_product_id=data_product_id2,
extended_data_product=extended_product)
#---------- Put some events into the eventsdb to test - this should set the comms and data status to WARNING ---------
t = get_ion_ts()
self.event_publisher.publish_event(ts_created=t,
event_type='DeviceStatusEvent',
origin=instDevice_id,
state=DeviceStatusType.OUT_OF_RANGE,
values=[200])
self.event_publisher.publish_event(
ts_created=t,
event_type='DeviceCommsEvent',
origin=instDevice_id,
state=DeviceCommsType.DATA_DELIVERY_INTERRUPTION,
lapse_interval_seconds=20)
#--------------------------------------------------------------------------------
# Get the extended instrument
#--------------------------------------------------------------------------------
extended_instrument = self.imsclient.get_instrument_device_extension(
instrument_device_id=instDevice_id, user_id=user_id_2)
self._check_computed_attributes_of_extended_instrument(
expected_instrument_device_id=instDevice_id,
extended_instrument=extended_instrument)
#--------------------------------------------------------------------------------
# Deactivate loggers
#--------------------------------------------------------------------------------
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
self.dpclient.delete_data_product(data_product_id1)
self.dpclient.delete_data_product(data_product_id2)
def test_dm_integration(self):
'''
test_salinity_transform
Test full DM Services Integration
'''
cc = self.container
assertions = self.assertTrue
#-----------------------------
# Copy below here to run as a script (don't forget the imports of course!)
#-----------------------------
# Create some service clients...
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(
node=cc.node)
dataset_management_service = DatasetManagementServiceClient(
node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
transform_management_service = TransformManagementServiceClient(
node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
# declare some handy variables
datastore_name = 'test_dm_integration'
###
### In the beginning there were two stream definitions...
###
# create a stream definition for the data from the ctd simulator
ctd_stream_def = SBE37_CDM_stream_definition()
ctd_stream_def_id = pubsub_management_service.create_stream_definition(
container=ctd_stream_def, name='Simulated CTD data')
# create a stream definition for the data from the salinity Transform
sal_stream_def_id = pubsub_management_service.create_stream_definition(
container=SalinityTransform.outgoing_stream_def,
name='Scalar Salinity data stream')
###
### And two process definitions...
###
# one for the ctd simulator...
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module': 'ion.processes.data.ctd_stream_publisher',
'class': 'SimpleCtdPublisher'
}
ctd_sim_procdef_id = process_dispatcher.create_process_definition(
process_definition=producer_definition)
# one for the salinity transform
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module': 'ion.processes.data.transforms.ctd.ctd_L2_salinity',
'class': 'SalinityTransform'
}
salinity_transform_procdef_id = process_dispatcher.create_process_definition(
process_definition=producer_definition)
#---------------------------
# Set up ingestion - this is an operator concern - not done by SA in a deployed system
#---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug('Calling create_ingestion_configuration')
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name,
datastore_profile='SCIDATA'),
number_of_workers=1)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
#---------------------------
# Set up the producer (CTD Simulator)
#---------------------------
# Create the stream
ctd_stream_id = pubsub_management_service.create_stream(
stream_definition_id=ctd_stream_def_id)
# Set up the datasets
ctd_dataset_id = dataset_management_service.create_dataset(
stream_id=ctd_stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule')
# Configure ingestion of this dataset
ctd_dataset_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id=ctd_dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id=
ingestion_configuration_id, # you need to know the ingestion configuration id!
)
# Hold onto ctd_dataset_config_id if you want to stop/start ingestion of that dataset by the ingestion service
#---------------------------
# Set up the salinity transform
#---------------------------
# Create the stream
sal_stream_id = pubsub_management_service.create_stream(
stream_definition_id=sal_stream_def_id)
# Set up the datasets
sal_dataset_id = dataset_management_service.create_dataset(
stream_id=sal_stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule')
# Configure ingestion of the salinity as a dataset
sal_dataset_config_id = ingestion_management_service.create_dataset_configuration(
dataset_id=sal_dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id=
ingestion_configuration_id, # you need to know the ingestion configuration id!
)
# Hold onto sal_dataset_config_id if you want to stop/start ingestion of that dataset by the ingestion service
# Create a subscription as input to the transform
sal_transform_input_subscription_id = pubsub_management_service.create_subscription(
query=StreamQuery(stream_ids=[
ctd_stream_id,
]),
exchange_name='salinity_transform_input'
) # how do we make these names??? i.e. Should they be anonymous?
# create the salinity transform
sal_transform_id = transform_management_service.create_transform(
name='example salinity transform',
in_subscription_id=sal_transform_input_subscription_id,
out_streams={
'output': sal_stream_id,
},
process_definition_id=salinity_transform_procdef_id,
# no configuration needed at this time...
)
# start the transform - for a test case it makes sense to do it before starting the producer but it is not required
transform_management_service.activate_transform(
transform_id=sal_transform_id)
# Start the ctd simulator to produce some data
configuration = {
'process': {
'stream_id': ctd_stream_id,
}
}
ctd_sim_pid = process_dispatcher.schedule_process(
process_definition_id=ctd_sim_procdef_id,
configuration=configuration)
###
### Make a subscriber in the test to listen for salinity data
###
salinity_subscription_id = pubsub_management_service.create_subscription(
query=StreamQuery([
sal_stream_id,
]),
exchange_name='salinity_test',
name="test salinity subscription",
)
pid = cc.spawn_process(name='dummy_process_for_test',
module='pyon.ion.process',
cls='SimpleProcess',
config={})
dummy_process = cc.proc_manager.procs[pid]
subscriber_registrar = StreamSubscriberRegistrar(process=dummy_process,
node=cc.node)
result = gevent.event.AsyncResult()
results = []
def message_received(message, headers):
# Heads
log.warn('Salinity data received!')
results.append(message)
if len(results) > 3:
result.set(True)
subscriber = subscriber_registrar.create_subscriber(
exchange_name='salinity_test', callback=message_received)
subscriber.start()
# after the queue has been created it is safe to activate the subscription
pubsub_management_service.activate_subscription(
subscription_id=salinity_subscription_id)
# Assert that we have received data
assertions(result.get(timeout=10))
# stop the flow parse the messages...
process_dispatcher.cancel_process(
ctd_sim_pid
) # kill the ctd simulator process - that is enough data
for message in results:
psd = PointSupplementStreamParser(
stream_definition=SalinityTransform.outgoing_stream_def,
stream_granule=message)
# Test the handy info method for the names of fields in the stream def
assertions('salinity' in psd.list_field_names())
# you have to know the name of the coverage in stream def
salinity = psd.get_values('salinity')
import numpy
assertions(isinstance(salinity, numpy.ndarray))
assertions(numpy.nanmin(salinity) >
0.0) # salinity should always be greater than 0
class ExhaustiveParameterTest(IonIntegrationTestCase):
def setUp(self):
self.i = 0
self._start_container()
self.container.start_rel_from_url('res/deploy/r2params.yml')
self.dataset_management = DatasetManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.resource_registry = self.container.resource_registry
self.data_retriever = DataRetrieverServiceClient()
pdicts, _ = self.resource_registry.find_resources(
restype='ParameterDictionary', id_only=False)
self.dp_ids = []
for pdict in pdicts:
stream_def_id = self.pubsub_management.create_stream_definition(
pdict.name, parameter_dictionary_id=pdict._id)
dp_id = self.make_dp(stream_def_id)
if dp_id: self.dp_ids.append(dp_id)
def make_dp(self, stream_def_id):
tdom, sdom = time_series_domain()
tdom = tdom.dump()
sdom = sdom.dump()
stream_def = self.resource_registry.read(stream_def_id)
dp_obj = DataProduct(name=stream_def.name,
description=stream_def.name,
processing_level_code='Parsed_Canonical',
temporal_domain=tdom,
spatial_domain=sdom)
data_product_id = self.data_product_management.create_data_product(
dp_obj, stream_definition_id=stream_def_id)
self.data_product_management.activate_data_product_persistence(
data_product_id)
return data_product_id
def fill_values(self, ptype, size):
if isinstance(ptype, ArrayType):
return ['blah'] * size
elif isinstance(ptype, QuantityType):
return np.sin(
np.arange(size, dtype=ptype.value_encoding) * 2 * np.pi / 3)
elif isinstance(ptype, RecordType):
return [{'record': 'ok'}] * size
elif isinstance(ptype, ConstantRangeType):
return (1, 1000)
elif isinstance(ptype, ConstantType):
return np.dtype(ptype.value_encoding).type(1)
elif isinstance(ptype, CategoryType):
return ptype.categories.keys()[0]
else:
return
def wait_until_we_have_enough_granules(self, dataset_id='', data_size=40):
'''
Loops until there is a sufficient amount of data in the dataset
'''
done = False
with gevent.Timeout(40):
while not done:
granule = self.data_retriever.retrieve_last_data_points(
dataset_id, 1)
rdt = RecordDictionaryTool.load_from_granule(granule)
extents = self.dataset_management.dataset_extents(
dataset_id, rdt._pdict.temporal_parameter_name)[0]
if rdt[rdt._pdict.temporal_parameter_name] and rdt[
rdt._pdict.
temporal_parameter_name][0] != rdt._pdict.get_context(
rdt._pdict.temporal_parameter_name
).fill_value and extents >= data_size:
done = True
else:
gevent.sleep(0.2)
def write_to_data_product(self, data_product_id):
dataset_ids, _ = self.resource_registry.find_objects(data_product_id,
'hasDataset',
id_only=True)
dataset_id = dataset_ids.pop()
stream_ids, _ = self.resource_registry.find_objects(data_product_id,
'hasStream',
id_only=True)
stream_id = stream_ids.pop()
stream_def_ids, _ = self.resource_registry.find_objects(
stream_id, 'hasStreamDefinition', id_only=True)
stream_def_id = stream_def_ids.pop()
route = self.pubsub_management.read_stream_route(stream_id)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
time_param = rdt._pdict.temporal_parameter_name
if time_param is None:
print '%s has no temporal parameter' % self.resource_registry.read(
data_product_id).name
return
rdt[time_param] = np.arange(40)
for field in rdt.fields:
if field == rdt._pdict.temporal_parameter_name:
continue
rdt[field] = self.fill_values(
rdt._pdict.get_context(field).param_type, 40)
publisher = StandaloneStreamPublisher(stream_id, route)
publisher.publish(rdt.to_granule())
self.wait_until_we_have_enough_granules(dataset_id, 40)
granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(granule)
bad = []
for field in rdt.fields:
if not np.array_equal(rdt[field], rdt_out[field]):
print '%s' % field
print '%s != %s' % (rdt[field], rdt_out[field])
bad.append(field)
return bad
def test_data_products(self):
bad_data_products = {}
for dp_id in self.dp_ids:
try:
bad_fields = self.write_to_data_product(dp_id)
if bad_fields:
bad_data_products[
dp_id] = "Couldn't write and retrieve %s." % bad_fields
except:
import traceback
bad_data_products[dp_id] = traceback.format_exc()
for dp_id, tb in bad_data_products.iteritems():
print '----------'
print 'Problem with %s' % self.resource_registry.read(dp_id).name
print tb
print '----------'
if bad_data_products:
raise AssertionError('There are bad parameter dictionaries.')
class TestActivateRSNVel3DInstrument(IonIntegrationTestCase):
def setUp(self):
# Start container
super(TestActivateRSNVel3DInstrument, self).setUp()
config = DotDict()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(
node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(
node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
def create_logger(self, name, stream_id=''):
# logger process
producer_definition = ProcessDefinition(name=name + '_logger')
producer_definition.executable = {
'module': 'ion.processes.data.stream_granule_logger',
'class': 'StreamGranuleLogger'
}
logger_procdef_id = self.processdispatchclient.create_process_definition(
process_definition=producer_definition)
configuration = {
'process': {
'stream_id': stream_id,
}
}
pid = self.processdispatchclient.schedule_process(
process_definition_id=logger_procdef_id,
configuration=configuration)
return pid
@attr('LOCOINT')
@unittest.skip('under construction')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
@patch.dict(CFG, {'endpoint': {'receive': {'timeout': 180}}})
def test_activate_rsn_vel3d(self):
log.info(
"--------------------------------------------------------------------------------------------------------"
)
# load_parameter_scenarios
self.container.spawn_process(
"Loader",
"ion.processes.bootstrap.ion_loader",
"IONLoader",
config=dict(
op="load",
scenario="BETA",
path="master",
categories=
"ParameterFunctions,ParameterDefs,ParameterDictionary,StreamDefinition",
clearcols="owner_id,org_ids",
assets="res/preload/r2_ioc/ooi_assets",
parseooi="True",
))
self.loggerpids = []
# Create InstrumentModel
instModel_obj = IonObject(RT.InstrumentModel,
name='Vel3DMModel',
description="Vel3DMModel")
instModel_id = self.imsclient.create_instrument_model(instModel_obj)
log.debug('test_activate_rsn_vel3d new InstrumentModel id = %s ',
instModel_id)
raw_config = StreamConfiguration(stream_name='raw',
parameter_dictionary_name='raw')
vel3d_b_sample = StreamConfiguration(
stream_name='vel3d_b_sample',
parameter_dictionary_name='vel3d_b_sample')
vel3d_b_engineering = StreamConfiguration(
stream_name='vel3d_b_engineering',
parameter_dictionary_name='vel3d_b_engineering')
RSN_VEL3D_01 = {
'DEV_ADDR': "10.180.80.6",
'DEV_PORT': 2101,
'DATA_PORT': 1026,
'CMD_PORT': 1025,
'PA_BINARY': "port_agent"
}
# Create InstrumentAgent
instAgent_obj = IonObject(
RT.InstrumentAgent,
name='Vel3DAgent',
description="Vel3DAgent",
driver_uri=
"http://sddevrepo.oceanobservatories.org/releases/nobska_mavs4_ooicore-0.0.7-py2.7.egg",
stream_configurations=[
raw_config, vel3d_b_sample, vel3d_b_engineering
])
instAgent_id = self.imsclient.create_instrument_agent(instAgent_obj)
log.debug('test_activate_rsn_vel3d new InstrumentAgent id = %s',
instAgent_id)
self.imsclient.assign_instrument_model_to_instrument_agent(
instModel_id, instAgent_id)
# Create InstrumentDevice
log.debug(
'test_activate_rsn_vel3d: Create instrument resource to represent the Vel3D '
)
instDevice_obj = IonObject(RT.InstrumentDevice,
name='Vel3DDevice',
description="Vel3DDevice",
serial_number="12345")
instDevice_id = self.imsclient.create_instrument_device(
instrument_device=instDevice_obj)
self.imsclient.assign_instrument_model_to_instrument_device(
instModel_id, instDevice_id)
log.debug("test_activate_rsn_vel3d: new InstrumentDevice id = %s ",
instDevice_id)
port_agent_config = {
'device_addr': '10.180.80.6',
'device_port': 2101,
'process_type': PortAgentProcessType.UNIX,
'binary_path': "port_agent",
'port_agent_addr': 'localhost',
'command_port': 1025,
'data_port': 1026,
'log_level': 5,
'type': PortAgentType.ETHERNET
}
instAgentInstance_obj = IonObject(RT.InstrumentAgentInstance,
name='Vel3DAgentInstance',
description="Vel3DAgentInstance",
port_agent_config=port_agent_config,
alerts=[])
instAgentInstance_id = self.imsclient.create_instrument_agent_instance(
instAgentInstance_obj, instAgent_id, instDevice_id)
parsed_sample_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'vel3d_b_sample', id_only=True)
parsed_sample_stream_def_id = self.pubsubcli.create_stream_definition(
name='vel3d_b_sample',
parameter_dictionary_id=parsed_sample_pdict_id)
parsed_eng_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'vel3d_b_engineering', id_only=True)
parsed_eng_stream_def_id = self.pubsubcli.create_stream_definition(
name='vel3d_b_engineering',
parameter_dictionary_id=parsed_eng_pdict_id)
raw_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'raw', id_only=True)
raw_stream_def_id = self.pubsubcli.create_stream_definition(
name='raw', parameter_dictionary_id=raw_pdict_id)
#-------------------------------
# Create Raw and Parsed Data Products for the device
#-------------------------------
dp_obj = IonObject(RT.DataProduct,
name='vel3d_b_sample',
description='vel3d_b_sample')
sample_data_product_id = self.dpclient.create_data_product(
data_product=dp_obj,
stream_definition_id=parsed_sample_stream_def_id)
log.debug('new dp_id = %s', sample_data_product_id)
self.dpclient.activate_data_product_persistence(
data_product_id=sample_data_product_id)
self.damsclient.assign_data_product(
input_resource_id=instDevice_id,
data_product_id=sample_data_product_id)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(sample_data_product_id,
PRED.hasStream, None, True)
log.debug('sample_data_product streams1 = %s', stream_ids)
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(sample_data_product_id,
PRED.hasDataset,
RT.Dataset, True)
log.debug('Data set for sample_data_product = %s', dataset_ids[0])
self.parsed_dataset = dataset_ids[0]
pid = self.create_logger('vel3d_b_sample', stream_ids[0])
self.loggerpids.append(pid)
dp_obj = IonObject(RT.DataProduct,
name='vel3d_b_engineering',
description='vel3d_b_engineering')
eng_data_product_id = self.dpclient.create_data_product(
data_product=dp_obj, stream_definition_id=parsed_eng_stream_def_id)
log.debug('new dp_id = %s', eng_data_product_id)
self.dpclient.activate_data_product_persistence(
data_product_id=eng_data_product_id)
self.damsclient.assign_data_product(
input_resource_id=instDevice_id,
data_product_id=eng_data_product_id)
dp_obj = IonObject(RT.DataProduct,
name='the raw data',
description='raw stream test')
data_product_id2 = self.dpclient.create_data_product(
data_product=dp_obj, stream_definition_id=raw_stream_def_id)
log.debug('new dp_id = %s', data_product_id2)
self.damsclient.assign_data_product(input_resource_id=instDevice_id,
data_product_id=data_product_id2)
self.dpclient.activate_data_product_persistence(
data_product_id=data_product_id2)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id2,
PRED.hasStream, None, True)
log.debug('test_activate_rsn_vel3d Data product streams2 = %s',
str(stream_ids))
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id2,
PRED.hasDataset,
RT.Dataset, True)
log.debug('test_activate_rsn_vel3d Data set for data_product_id2 = %s',
dataset_ids[0])
self.raw_dataset = dataset_ids[0]
def start_instrument_agent():
self.imsclient.start_instrument_agent_instance(
instrument_agent_instance_id=instAgentInstance_id)
gevent.joinall([gevent.spawn(start_instrument_agent)])
#cleanup
self.addCleanup(self.imsclient.stop_instrument_agent_instance,
instrument_agent_instance_id=instAgentInstance_id)
#wait for start
inst_agent_instance_obj = self.imsclient.read_instrument_agent_instance(
instAgentInstance_id)
gate = AgentProcessStateGate(self.processdispatchclient.read_process,
instDevice_id, ProcessStateEnum.RUNNING)
self.assertTrue(
gate. await (30),
"The instrument agent instance (%s) did not spawn in 30 seconds" %
gate.process_id)
#log.trace('Instrument agent instance obj: = %s' , str(inst_agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._ia_client = ResourceAgentClient(instDevice_id,
to_name=gate.process_id,
process=FakeProcess())
def check_state(label, desired_state):
actual_state = self._ia_client.get_agent_state()
log.debug("%s instrument agent is in state '%s'", label,
actual_state)
self.assertEqual(desired_state, actual_state)
log.debug("test_activate_rsn_vel3d: got ia client %s",
str(self._ia_client))
check_state("just-spawned", ResourceAgentState.UNINITIALIZED)
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
retval = self._ia_client.execute_agent(cmd)
log.debug("test_activate_rsn_vel3d: initialize %s", str(retval))
check_state("initialized", ResourceAgentState.INACTIVE)
log.debug("test_activate_rsn_vel3d Sending go_active command ")
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activate_rsn_vel3d: return value from go_active %s",
str(reply))
check_state("activated", ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
retval = self._ia_client.execute_agent(cmd)
state = retval.result
log.debug("current state after sending go_active command %s",
str(state))
#
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activate_rsn_vel3d: run %s", str(reply))
check_state("commanded", ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
retval = self._ia_client.execute_agent(cmd)
state = retval.result
log.debug("current state after sending run command %s", str(state))
# cmd = AgentCommand(command=ProtocolEvent.START_AUTOSAMPLE)
# reply = self._ia_client.execute_agent(cmd)
# log.debug("test_activate_rsn_vel3d: run %s" , str(reply))
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.COMMAND, state)
#
# gevent.sleep(5)
#
# cmd = AgentCommand(command=ProtocolEvent.STOP_AUTOSAMPLE)
# reply = self._ia_client.execute_agent(cmd)
# log.debug("test_activate_rsn_vel3d: run %s" , str(reply))
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.COMMAND, state)
#
# cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
# retval = self._ia_client.execute_agent(cmd)
# state = retval.result
# log.debug("current state after sending STOP_AUTOSAMPLE command %s" , str(state))
#
# cmd = AgentCommand(command=ResourceAgentEvent.PAUSE)
# retval = self._ia_client.execute_agent(cmd)
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.STOPPED, state)
#
# cmd = AgentCommand(command=ResourceAgentEvent.RESUME)
# retval = self._ia_client.execute_agent(cmd)
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.COMMAND, state)
#
# cmd = AgentCommand(command=ResourceAgentEvent.CLEAR)
# retval = self._ia_client.execute_agent(cmd)
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.IDLE, state)
#
# cmd = AgentCommand(command=ResourceAgentEvent.RUN)
# retval = self._ia_client.execute_agent(cmd)
# state = self._ia_client.get_agent_state()
# self.assertEqual(ResourceAgentState.COMMAND, state)
log.debug("test_activate_rsn_vel3d: calling reset ")
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activate_rsn_vel3d: return from reset %s", str(reply))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data_raw = self.dataretrieverclient.retrieve(self.raw_dataset)
self.assertIsInstance(replay_data_raw, Granule)
rdt_raw = RecordDictionaryTool.load_from_granule(replay_data_raw)
log.debug("RDT raw: %s", str(rdt_raw.pretty_print()))
self.assertIn('raw', rdt_raw)
raw_vals = rdt_raw['raw']
#--------------------------------------------------------------------------------
# Deactivate loggers
#--------------------------------------------------------------------------------
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
self.dpclient.delete_data_product(sample_data_product_id)
self.dpclient.delete_data_product(eng_data_product_id)
self.dpclient.delete_data_product(data_product_id2)
def test_replay_integration(self):
'''
test_replay_integration
'''
import numpy as np
# Keep the import it's used in the vector comparison below even though pycharm says its unused.
cc = self.container
XP = self.XP
assertions = self.assertTrue
### Every thing below here can be run as a script:
log.debug('Got it')
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(
node=cc.node)
dataset_management_service = DatasetManagementServiceClient(
node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
datastore_name = 'dm_test_replay_integration'
producer = Publisher(name=(XP, 'stream producer'))
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id=XP,
couch_storage=CouchStorage(datastore_name=datastore_name,
datastore_profile='SCIDATA'),
hdf_storage=HdfStorage(),
number_of_workers=1)
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
definition = SBE37_CDM_stream_definition()
data_stream_id = definition.data_stream_id
encoding_id = definition.identifiables[data_stream_id].encoding_id
element_count_id = definition.identifiables[
data_stream_id].element_count_id
stream_def_id = pubsub_management_service.create_stream_definition(
container=definition)
stream_id = pubsub_management_service.create_stream(
stream_definition_id=stream_def_id)
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/dataset_by_id')
ingestion_management_service.create_dataset_configuration(
dataset_id=dataset_id,
archive_data=True,
archive_metadata=True,
ingestion_configuration_id=ingestion_configuration_id)
definition.stream_resource_id = stream_id
packet = _create_packet(definition)
input_file = FileSystem.mktemp()
input_file.write(packet.identifiables[data_stream_id].values)
input_file_path = input_file.name
input_file.close()
fields = [
'conductivity', 'height', 'latitude', 'longitude', 'pressure',
'temperature', 'time'
]
input_vectors = acquire_data([input_file_path], fields, 2).next()
producer.publish(msg=packet, to_name=(XP, '%s.data' % stream_id))
replay_id, replay_stream_id = data_retriever_service.define_replay(
dataset_id)
ar = gevent.event.AsyncResult()
def sub_listen(msg, headers):
assertions(isinstance(msg, StreamGranuleContainer),
'replayed message is not a granule.')
hdf_string = msg.identifiables[data_stream_id].values
sha1 = hashlib.sha1(hdf_string).hexdigest().upper()
assertions(sha1 == msg.identifiables[encoding_id].sha1,
'Checksum failed.')
assertions(
msg.identifiables[element_count_id].value == 1,
'record replay count is incorrect %d.' %
msg.identifiables[element_count_id].value)
output_file = FileSystem.mktemp()
output_file.write(msg.identifiables[data_stream_id].values)
output_file_path = output_file.name
output_file.close()
output_vectors = acquire_data([output_file_path], fields, 2).next()
for field in fields:
comparison = (input_vectors[field]['values'] ==
output_vectors[field]['values'])
assertions(
comparison.all(), 'vector mismatch: %s vs %s' %
(input_vectors[field]['values'],
output_vectors[field]['values']))
FileSystem.unlink(output_file_path)
ar.set(True)
subscriber = Subscriber(name=(XP, 'replay listener'),
callback=sub_listen)
g = gevent.Greenlet(subscriber.listen,
binding='%s.data' % replay_stream_id)
g.start()
data_retriever_service.start_replay(replay_id)
ar.get(timeout=10)
FileSystem.unlink(input_file_path)
class TestObservatoryManagementFullIntegration(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.RR = ResourceRegistryServiceClient()
self.RR2 = EnhancedResourceRegistryClient(self.RR)
self.OMS = ObservatoryManagementServiceClient()
self.org_management_service = OrgManagementServiceClient()
self.IMS = InstrumentManagementServiceClient()
self.dpclient = DataProductManagementServiceClient()
self.pubsubcli = PubsubManagementServiceClient()
self.damsclient = DataAcquisitionManagementServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self._load_stage = 0
self._resources = {}
def preload_ooi(self, stage=STAGE_LOAD_ASSETS):
# Preloads OOI up to a given stage
if self._load_stage >= stage:
return
if self._load_stage < STAGE_LOAD_ORGS:
log.info("--------------------------------------------------------------------------------------------------------")
log.info("Preloading stage: %s (OOIR2 Orgs, users, roles)", STAGE_LOAD_ORGS)
# load_OOIR2_scenario
self.container.spawn_process("Loader", "ion.processes.bootstrap.ion_loader", "IONLoader", config=dict(
op="load",
scenario="OOIR2",
path="master",
))
self._load_stage = STAGE_LOAD_ORGS
if self._load_stage < STAGE_LOAD_PARAMS:
log.info("--------------------------------------------------------------------------------------------------------")
log.info("Preloading stage: %s (BASE params, streamdefs)", STAGE_LOAD_PARAMS)
# load_parameter_scenarios
self.container.spawn_process("Loader", "ion.processes.bootstrap.ion_loader", "IONLoader", config=dict(
op="load",
scenario="BETA",
path="master",
categories="ParameterFunctions,ParameterDefs,ParameterDictionary,StreamDefinition",
clearcols="owner_id,org_ids",
assets="res/preload/r2_ioc/ooi_assets",
parseooi="True",
))
self._load_stage = STAGE_LOAD_PARAMS
if self._load_stage < STAGE_LOAD_AGENTS:
log.info("--------------------------------------------------------------------------------------------------------")
log.info("Preloading stage: %s (OOIR2_I agents, model links)", STAGE_LOAD_AGENTS)
# load_OOIR2_agents
self.container.spawn_process("Loader", "ion.processes.bootstrap.ion_loader", "IONLoader", config=dict(
op="load",
scenario="OOIR2_I",
path="master",
))
self._load_stage = STAGE_LOAD_AGENTS
if self._load_stage < STAGE_LOAD_ASSETS:
log.info("--------------------------------------------------------------------------------------------------------")
log.info("Preloading stage: %s (OOI assets linked to params, agents)", STAGE_LOAD_ASSETS)
# load_ooi_assets
self.container.spawn_process("Loader", "ion.processes.bootstrap.ion_loader", "IONLoader", config=dict(
op="load",
loadooi="True",
path="master",
assets="res/preload/r2_ioc/ooi_assets",
bulk="True",
debug="True",
ooiuntil="9/1/2013",
ooiparams="True",
#excludecategories: DataProduct,DataProductLink,Deployment,Workflow,WorkflowDefinition
))
self._load_stage = STAGE_LOAD_ASSETS
# 'DataProduct,DataProductLink,WorkflowDefinition,ExternalDataProvider,ExternalDatasetModel,ExternalDataset,ExternalDatasetAgent,ExternalDatasetAgentInstance',
@unittest.skip('Work in progress')
def test_observatory(self):
self._load_stage = 0
self._resources = {}
passing = True
self.assertTrue(True)
# LOAD STEP 1
self.preload_ooi(stage=STAGE_LOAD_ORGS)
passing &= self.orguserrole_assertions()
# LOAD STEP 2
self.preload_ooi(stage=STAGE_LOAD_PARAMS)
passing &= self.parameter_assertions()
# LOAD STEP 3
self.preload_ooi(stage=STAGE_LOAD_AGENTS)
passing &= self.agent_assertions()
# LOAD STEP 4
self.preload_ooi(stage=STAGE_LOAD_ASSETS)
# Check OOI preloaded resources to see if they match needs for this test and for correctness
passing &= self.sites_assertions()
passing &= self.device_assertions()
passing &= self.deployment_assertions()
# Extensive tests on select RSN nodes
passing &= self.rsn_node_checks()
# Extensive tests on select RSN instruments
passing &= self.check_rsn_instrument()
passing &= self.check_rsn_instrument_data_product()
# Extensive tests on a glider
#passing &= self.check_glider()
# Extensive tests on a CG assembly
#passing &= self.check_cg_assembly()
# Add a new instrument agent
# Add a new instrument agent instance
# Check DataProducts
# Check Provenance
IonIntegrationTestCase.assertTrue(self, passing)
# -------------------------------------------------------------------------
def orguserrole_assertions(self):
passing = True
passing &= self._check_marine_facility("MF_CGSN")
passing &= self._check_marine_facility("MF_RSN")
passing &= self._check_marine_facility("MF_EA")
return passing
def _check_marine_facility(self, preload_id):
passing = True
log.debug("Checking marine facility %s and associations", preload_id)
mf_obj = self.retrieve_ooi_asset(preload_id)
mf_id = mf_obj._id
self._resources[preload_id] = mf_id
passing &= self.assertEquals(mf_obj.lcstate, LCS.DEPLOYED)
res_list, _ = self.RR.find_objects(subject=mf_id, predicate=PRED.hasMembership, id_only=True)
passing &= self.assertTrue(len(res_list) >= 3)
res_list, _ = self.RR.find_objects(subject=mf_id, predicate=PRED.hasRole, id_only=False)
passing &= self.assertTrue(len(res_list) >= 5)
passing &= self._check_role_assignments(res_list, "ORG_MANAGER")
passing &= self._check_role_assignments(res_list, "OBSERVATORY_OPERATOR")
passing &= self._check_role_assignments(res_list, "INSTRUMENT_OPERATOR")
return passing
def _check_role_assignments(self, role_list, role_name):
passing = True
role_obj = self._find_resource_in_list(role_list, "governance_name", role_name)
if role_obj:
res_list = self.RR.find_subjects(predicate=PRED.hasRole, object=role_obj._id, id_only=True)
passing &= self.assertTrue(len(res_list) >= 1)
return passing
def parameter_assertions(self):
passing = True
pctx_list, _ = self.RR.find_resources_ext(restype=RT.ParameterContext)
passing &= self.assertTrue(len(pctx_list) >= 10)
pdict_list, _ = self.RR.find_resources_ext(restype=RT.ParameterDictionary)
passing &= self.assertTrue(len(pdict_list) >= 10)
sdef_list, _ = self.RR.find_resources_ext(restype=RT.StreamDefinition)
passing &= self.assertTrue(len(sdef_list) >= 10)
# Verify that a PDict has the appropriate QC parameters defined
pdicts, _ = self.RR.find_resources_ext(restype=RT.ParameterDictionary, alt_id_ns='PRE', alt_id='DICT110')
passing &= self.assertTrue(len(pdicts)==1)
if not pdicts:
return passing
pdict = pdicts[0]
# According to the latest SAF, density should NOT have trend
parameters, _ = self.RR.find_objects(pdict, PRED.hasParameterContext)
names = [i.name for i in parameters if i.name.startswith('density')]
passing &= self.assertTrue('density_trndtst_qc' not in names)
return passing
def agent_assertions(self):
passing = True
# TODO: More tests?
return passing
def sites_assertions(self):
passing = True
observatory_list, _ = self.RR.find_resources_ext(restype=RT.Observatory)
passing &= self.assertTrue(len(observatory_list) >= 40)
for obs in observatory_list:
passing &= self.assertEquals(obs.lcstate, LCS.DEPLOYED)
platform_site_list, _ = self.RR.find_resources(RT.PlatformSite, id_only=False)
log.debug('platform sites: %s', [ps.name for ps in platform_site_list])
passing &= self.assertTrue(len(platform_site_list) >= 30)
return passing
def device_assertions(self):
passing = True
platform_device_list, _ = self.RR.find_resources(RT.PlatformDevice, id_only=False)
passing &= self.assertTrue(len(platform_device_list) >= 30)
for pdev in platform_device_list:
log.debug('platform device: %s', pdev.name)
passing &= self.assertEquals(pdev.lcstate, LCS.PLANNED)
platform_agent_list, _ = self.RR.find_resources(RT.PlatformAgent, id_only=False)
passing &= self.assertTrue(len(platform_agent_list) >= 2)
for pagent in platform_agent_list:
log.debug('platform agent: %s', pagent.name)
passing &= self.assertEquals(pagent.lcstate, LCS.DEPLOYED)
instrument_agent_list, _ = self.RR.find_resources(RT.InstrumentAgent, id_only=False)
passing &= self.assertTrue(len(instrument_agent_list) >= 3)
for iagent in instrument_agent_list:
log.debug('instrument agent: %s', iagent.name)
passing &= self.assertEquals(iagent.lcstate, LCS.DEPLOYED)
model_list, _ = self.RR.find_objects(subject=iagent._id, predicate=PRED.hasModel, id_only=True)
passing &= self.assertTrue(len(model_list) >= 1, "IA %s" % iagent.name)
return passing
def deployment_assertions(self):
passing = True
deployment_list, _ = self.RR.find_resources(RT.Deployment, id_only=False)
passing &= self.assertTrue(len(deployment_list) >= 30)
for deploy in deployment_list:
log.debug('deployment: %s', deploy.name)
passing &= self.assertEquals(deploy.lcstate, LCS.DEPLOYED)
return passing
def rsn_node_checks(self):
"""
Current preload creates:
- PlatformDevice in PLANNED
- PlatformSite in DEPLOYED
- Deployment in DEPLOYED
- Deployment is NOT activated
"""
passing = True
dp_obj = self.retrieve_ooi_asset("CE04OSHY-PN01C_DEP")
passing &= self.assertEquals(dp_obj.lcstate, LCS.DEPLOYED)
passing &= self.assertEquals(dp_obj.availability, AS.AVAILABLE)
log.debug('test_observatory retrieve CE04OSHY-PN01C_DEP deployment: %s', dp_obj)
# Check existing RSN node CE04OSHY-LV01C Deployment (PLANNED lcstate)
CE04OSHY_LV01C_deployment = self.retrieve_ooi_asset('CE04OSHY-LV01C_DEP')
passing &= self.assertEquals(CE04OSHY_LV01C_deployment.lcstate, LCS.DEPLOYED)
passing &= self.assertEquals(CE04OSHY_LV01C_deployment.availability, AS.AVAILABLE)
#self.dump_deployment(CE04OSHY_LV01C_deployment._id)
log.debug('test_observatory retrieve RSN node CE04OSHY-LV01C Deployment: %s', CE04OSHY_LV01C_deployment)
CE04OSHY_LV01C_device = self.retrieve_ooi_asset('CE04OSHY-LV01C_PD')
# Set CE04OSHY-LV01C device to DEVELOPED state
passing &= self.transition_lcs_then_verify(resource_id=CE04OSHY_LV01C_device._id, new_lcs_state=LCE.DEVELOP, verify=LCS.DEVELOPED)
# Set CE04OSHY-LV01C device to INTEGRATED state
passing &= self.transition_lcs_then_verify(resource_id=CE04OSHY_LV01C_device._id, new_lcs_state=LCE.INTEGRATE, verify=LCS.INTEGRATED)
# Set CE04OSHY-LV01C device to DEPLOYED state
passing &= self.transition_lcs_then_verify(resource_id=CE04OSHY_LV01C_device._id, new_lcs_state=LCE.DEPLOY, verify=LCS.DEPLOYED)
# Set CE04OSHY-LV01C Deployment to DEPLOYED state
# NOTE: Deployments are created in DEPLOYED state, currently
#self.transition_lcs_then_verify(resource_id=CE04OSHY_LV01C_deployment._id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
# Activate Deployment for CE04OSHY-LV01C
self.OMS.activate_deployment(CE04OSHY_LV01C_deployment._id)
log.debug('--------- activate_deployment CE04OSHY_LV01C_deployment -------------- ')
self.dump_deployment(CE04OSHY_LV01C_deployment._id)
passing &= self.validate_deployment_activated(CE04OSHY_LV01C_deployment._id)
# (optional) Start CE04OSHY-LV01C platform agent with simulator
# NOTE: DataProduct is generated in DEPLOYED state
# # Set DataProduct for CE04OSHY-LV01C platform to DEPLOYED state
# output_data_product_ids, assns =self.RR.find_objects(subject=CE04OSHY_LV01C_device._id, predicate=PRED.hasOutputProduct, id_only=True)
# if output_data_product_ids:
# #self.assertEquals(len(child_devs), 3)
# for output_data_product_id in output_data_product_ids:
# log.debug('DataProduct for CE04OSHY-LV01C platform: %s', output_data_product_id)
# self.transition_lcs_then_verify(resource_id=output_data_product_id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
# Check events for CE04OSHY-LV01C platform
# Check existing CE04OSBP-LJ01C Deployment (PLANNED lcstate)
# dp_list, _ = self.RR.find_resources_ext(alt_id_ns="PRE", alt_id="CE04OSBP-LJ01C_DEP")
# self.assertEquals(len(dp_list), 1)
# CE04OSHY_LV01C_deployment = dp_list[0]
# self.assertEquals(CE04OSHY_LV01C_deployment.lcstate, 'PLANNED')
# log.debug('test_observatory retrieve RSN node CE04OSBP-LJ01C Deployment: %s', CE04OSHY_LV01C_deployment)
# Set CE04OSBP-LJ01C Deployment to DEPLOYED state
# Update description and other attributes for CE04OSBP-LJ01C device resource
# Create attachment (JPG image) for CE04OSBP-LJ01C device resource
# Activate Deployment for CE04OSBP-LJ01C
# (optional) Add/register CE04OSBP-LJ01C platform agent to parent agent
# (optional) Start CE04OSBP-LJ01C platform agent
return passing
def check_rsn_instrument(self):
"""
Check existing RSN instrument CE04OSBP-LJ01C-06-CTDBPO108 Deployment (PLANNED lcstate)
Current preload creates:
- InstrumentDevice in PLANNED
- InstrumentSite in DEPLOYED
- Deployment in DEPLOYED
- Deployment is activated
"""
passing = True
CE04OSBP_LJ01C_06_CTDBPO108_deploy = self.retrieve_ooi_asset('CE04OSBP-LJ01C-06-CTDBPO108_DEP')
self.dump_deployment(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
#passing &= self.assertEquals(CE04OSBP_LJ01C_06_CTDBPO108_deploy.lcstate, 'PLANNED')
# Set CE04OSBP-LJ01C-06-CTDBPO108 device to DEVELOPED state
CE04OSBP_LJ01C_06_CTDBPO108_device = self.retrieve_ooi_asset('CE04OSBP-LJ01C-06-CTDBPO108_ID')
passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id, new_lcs_state=LCE.DEVELOP, verify='DEVELOPED')
# Set CE04OSBP-LJ01C-06-CTDBPO108 device to INTEGRATED state
passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id, new_lcs_state=LCE.INTEGRATE, verify='INTEGRATED')
# Set CE04OSBP-LJ01C-06-CTDBPO108 device to DEPLOYED state
passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
# Set CE04OSBP-LJ01C-06-CTDBPO108 Deployment to DEPLOYED state
#self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_deploy._id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
# Activate Deployment for CE04OSBP-LJ01C-06-CTDBPO108 instrument
log.debug('--------- activate_deployment CE04OSBP-LJ01C-06-CTDBPO108 deployment -------------- ')
self.OMS.activate_deployment(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
passing &= self.validate_deployment_activated(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
# (optional) Add/register CE04OSBP-LJ01C-06-CTDBPO108 instrument agent to parent agent
# (optional) Start CE04OSBP-LJ01C-06-CTDBPO108 instrument agent with simulator
# Set all DataProducts for CE04OSBP-LJ01C-06-CTDBPO108 to DEPLOYED state
# (optional) Create a substitute Deployment for site CE04OSBP-LJ01C-06-CTDBPO108 with a comparable device
CE04OSBP_LJ01C_06_CTDBPO108_isite = self.retrieve_ooi_asset('CE04OSBP-LJ01C-06-CTDBPO108')
## create device here: retrieve CTD Mooring on Mooring Riser 001 - similiar?
GP03FLMB_RI001_10_CTDMOG999_ID_idevice = self.retrieve_ooi_asset('GP03FLMB-RI001-10-CTDMOG999_ID')
deploy_id_2 = self.create_basic_deployment(name='CE04OSBP-LJ01C-06-CTDBPO108_DEP2', description='substitute Deployment for site CE04OSBP-LJ01C-06-CTDBPO108 with a comparable device')
self.IMS.deploy_instrument_device(instrument_device_id=GP03FLMB_RI001_10_CTDMOG999_ID_idevice._id, deployment_id=deploy_id_2)
self.OMS.deploy_instrument_site(instrument_site_id=CE04OSBP_LJ01C_06_CTDBPO108_isite._id, deployment_id=deploy_id_2)
self.dump_deployment(deploy_id_2)
# (optional) Activate this second deployment - check first deployment is deactivated
self.OMS.deactivate_deployment(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
passing &= self.validate_deployment_deactivated(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
# log.debug('Activate deployment deploy_id_2')
# self.get_deployment_ids(deploy_id_2)
# self.dump_deployment(deploy_id_2, "deploy_id_2")
# self.OMS.activate_deployment(deploy_id_2)
# passing &= self.validate_deployment_deactivated(CE04OSBP_LJ01C_06_CTDBPO108_deploy._id)
#
# # (optional) Set first CE04OSBP-LJ01C-06-CTDBPO108 Deployment to INTEGRATED state
# passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_deploy._id, new_lcs_state=LCE.INTEGRATE, verify='INTEGRATED')
#
# # Set first CE04OSBP-LJ01C-06-CTDBPO108 device to INTEGRATED state
# passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id, new_lcs_state=LCE.INTEGRATE, verify='INTEGRATED')
#
#
# # (optional) Create a third Deployment for site CE04OSBP-LJ01C-06-CTDBPO108 with a same device from first deployment
# deploy_id_3 = self.create_basic_deployment(name='CE04OSBP-LJ01C-06-CTDBPO108_DEP3', description='substitute Deployment for site CE04OSBP-LJ01C-06-CTDBPO108 with same device as first')
# self.IMS.deploy_instrument_device(instrument_device_id=GP03FLMB_RI001_10_CTDMOG999_ID_idevice._id, deployment_id=deploy_id_3)
# self.OMS.deploy_instrument_site(instrument_site_id=CE04OSBP_LJ01C_06_CTDBPO108_isite._id, deployment_id=deploy_id_3)
# self.dump_deployment(deploy_id_3)
#
#
# # Set first CE04OSBP-LJ01C-06-CTDBPO108 device to DEPLOYED state
# passing &= self.transition_lcs_then_verify(resource_id=CE04OSBP_LJ01C_06_CTDBPO108_device._id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
#
# # (optional) Activate this third deployment - check second deployment is deactivated
# log.debug('Activate deployment deploy_id_3')
# self.dump_deployment(deploy_id_3)
# self.OMS.activate_deployment(deploy_id_3)
# #todo: check second deployment is deactivated
return passing
def check_data_product_reference(self, reference_designator, output=[]):
passing = True
data_product_ids, _ = self.RR.find_resources_ext(alt_id_ns='PRE', alt_id='%s_DPI1' % reference_designator, id_only=True) # Assuming DPI1 is parsed
passing &= self.assertEquals(len(data_product_ids), 1)
if not data_product_ids:
return passing
# Let's go ahead and activate it
data_product_id = data_product_ids[0]
self.dpclient.activate_data_product_persistence(data_product_id)
self.addCleanup(self.dpclient.suspend_data_product_persistence, data_product_id)
dataset_ids, _ = self.RR.find_objects(data_product_id, PRED.hasDataset, id_only=True)
passing &= self.assertEquals(len(dataset_ids), 1)
if not dataset_ids:
return passing
dataset_id = dataset_ids[0]
stream_def_ids, _ = self.RR.find_objects(data_product_id, PRED.hasStreamDefinition, id_only=True)
passing &= self.assertEquals(len(dataset_ids), 1)
if not stream_def_ids:
return passing
stream_def_id = stream_def_ids[0]
output.append((data_product_id, stream_def_id, dataset_id))
return passing
def check_tempsf_instrument_data_product(self, reference_designator):
passing = True
info_list = []
passing &= self.check_data_product_reference(reference_designator, info_list)
if not passing: return passing
data_product_id, stream_def_id, dataset_id = info_list.pop()
now = time.time()
ntp_now = now + 2208988800
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [ntp_now]
rdt['temperature'] = [[ 25.3884, 26.9384, 24.3394, 23.3401, 22.9832,
29.4434, 26.9873, 15.2883, 16.3374, 14.5883, 15.7253, 18.4383,
15.3488, 17.2993, 10.2111, 11.5993, 10.9345, 9.4444, 9.9876,
10.9834, 11.0098, 5.3456, 4.2994, 4.3009]]
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ParameterHelper.publish_rdt_to_data_product(data_product_id, rdt)
passing &= self.assertTrue(dataset_monitor.event.wait(20))
if not passing: return passing
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
passing &= self.assert_array_almost_equal(rdt['time'], [ntp_now])
passing &= self.assert_array_almost_equal(rdt['temperature'], [[
25.3884, 26.9384, 24.3394, 23.3401, 22.9832, 29.4434, 26.9873,
15.2883, 16.3374, 14.5883, 15.7253, 18.4383, 15.3488, 17.2993,
10.2111, 11.5993, 10.9345, 9.4444, 9.9876, 10.9834, 11.0098,
5.3456, 4.2994, 4.3009]])
return passing
def check_trhph_instrument_data_products(self, reference_designator):
passing = True
info_list = []
passing &= self.check_data_product_reference(reference_designator, info_list)
if not passing:
return passing
data_product_id, stream_def_id, dataset_id = info_list.pop()
pdict = self.RR2.find_parameter_dictionary_of_stream_definition_using_has_parameter_dictionary(stream_def_id)
passing &= self.assertEquals(pdict.name, 'trhph_sample')
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
# calibration constants
a = 1.98e-9
b = -2.45e-6
c = 9.28e-4
d = -0.0888
e = 0.731
V_s = 1.506
V_c = 0.
T = 11.8
r1 = 0.906
r2 = 4.095
r3 = 4.095
ORP_V = 1.806
Cl = np.nan
offset = 2008
gain = 4.0
# Normally this would be 50 per the DPS but the precision is %4.0f which truncates the values to the nearest 1...
ORP = ((ORP_V * 1000.) - offset) / gain
ntp_now = time.time() + 2208988800
rdt['cc_a'] = [a]
rdt['cc_b'] = [b]
rdt['cc_c'] = [c]
rdt['cc_d'] = [d]
rdt['cc_e'] = [e]
rdt['ref_temp_volts'] = [V_s]
rdt['resistivity_temp_volts'] = [V_c]
rdt['eh_sensor'] = [ORP_V]
rdt['resistivity_5'] = [r1]
rdt['resistivity_x1'] = [r2]
rdt['resistivity_x5'] = [r3]
rdt['cc_offset'] = [offset]
rdt['cc_gain'] = [gain]
rdt['time'] = [ntp_now]
passing &= self.assert_array_almost_equal(rdt['vent_fluid_temperaure'], [T], 2)
passing &= self.assert_array_almost_equal(rdt['vent_fluid_chloride_conc'], [Cl], 4)
passing &= self.assert_array_almost_equal(rdt['vent_fluid_orp'], [ORP], 4)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ParameterHelper.publish_rdt_to_data_product(data_product_id, rdt)
passing &= self.assertTrue(dataset_monitor.event.wait(60))
if not passing: return passing
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
passing &= self.assert_array_almost_equal(rdt['vent_fluid_temperaure'], [T], 2)
passing &= self.assert_array_almost_equal(rdt['vent_fluid_chloride_conc'], [Cl], 4)
passing &= self.assert_array_almost_equal(rdt['vent_fluid_orp'], [ORP], 4)
return passing
def check_vel3d_instrument_data_products(self, reference_designator):
passing = True
info_list = []
passing &= self.check_data_product_reference(reference_designator, info_list)
if not passing:
return passing
data_product_id, stream_def_id, dataset_id = info_list.pop()
pdict = self.RR2.find_parameter_dictionary_of_stream_definition_using_has_parameter_dictionary(stream_def_id)
self.assertEquals(pdict.name, 'vel3d_b_sample')
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
lat = 14.6846
lon = -51.044
ts = np.array([3319563600, 3319567200, 3319570800, 3319574400,
3319578000, 3319581600, 3319585200, 3319588800, 3319592400,
3319596000], dtype=np.float)
ve = np.array([ -3.2, 0.1, 0. , 2.3, -0.1, 5.6, 5.1, 5.8,
8.8, 10.3])
vn = np.array([ 18.2, 9.9, 12. , 6.6, 7.4, 3.4, -2.6, 0.2,
-1.5, 4.1])
vu = np.array([-1.1, -0.6, -1.4, -2, -1.7, -2, 1.3, -1.6, -1.1, -4.5])
ve_expected = np.array([-0.085136, -0.028752, -0.036007, 0.002136,
-0.023158, 0.043218, 0.056451, 0.054727, 0.088446, 0.085952])
vn_expected = np.array([ 0.164012, 0.094738, 0.114471, 0.06986, 0.07029,
0.049237, -0.009499, 0.019311, 0.012096, 0.070017])
vu_expected = np.array([-0.011, -0.006, -0.014, -0.02, -0.017, -0.02,
0.013, -0.016, -0.011, -0.045])
rdt['time'] = ts
rdt['lat'] = [lat] * 10
rdt['lon'] = [lon] * 10
rdt['turbulent_velocity_east'] = ve
rdt['turbulent_velocity_north'] = vn
rdt['turbulent_velocity_up'] = vu
passing &= self.assert_array_almost_equal(rdt['eastward_turbulent_velocity'],
ve_expected)
passing &= self.assert_array_almost_equal(rdt['northward_turbulent_velocity'],
vn_expected)
passing &= self.assert_array_almost_equal(rdt['upward_turbulent_velocity'],
vu_expected)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ParameterHelper.publish_rdt_to_data_product(data_product_id, rdt)
passing &= self.assertTrue(dataset_monitor.event.wait(20))
if not passing: return passing
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
passing &= self.assert_array_almost_equal(rdt['eastward_turbulent_velocity'],
ve_expected)
passing &= self.assert_array_almost_equal(rdt['northward_turbulent_velocity'],
vn_expected)
passing &= self.assert_array_almost_equal(rdt['upward_turbulent_velocity'],
vu_expected)
return passing
def check_presta_instrument_data_products(self, reference_designator):
# Check the parsed data product make sure it's got everything it needs and can be published persisted etc.
# Absolute Pressure (SFLPRES_L0) is what comes off the instrumnet, SFLPRES_L1 is a pfunc
# Let's go ahead and publish some fake data!!!
# According to https://alfresco.oceanobservatories.org/alfresco/d/d/workspace/SpacesStore/63e16865-9d9e-4b11-b0b3-d5658faa5080/1341-00230_Data_Product_Spec_SFLPRES_OOI.pdf
# Appendix A. Example 1.
# p_psia_tide = 14.8670
# the tide should be 10.2504
passing = True
info_list = []
passing &= self.check_data_product_reference(reference_designator, info_list)
if not passing:
return passing
data_product_id, stream_def_id, dataset_id = info_list.pop()
now = time.time()
ntp_now = now + 2208988800.
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [ntp_now]
rdt['absolute_pressure'] = [14.8670]
passing &= self.assert_array_almost_equal(rdt['seafloor_pressure'], [10.2504], 4)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ParameterHelper.publish_rdt_to_data_product(data_product_id, rdt)
self.assertTrue(dataset_monitor.event.wait(20)) # Bumped to 20 to keep buildbot happy
if not passing: return passing
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
passing &= self.assert_array_almost_equal(rdt['time'], [ntp_now])
passing &= self.assert_array_almost_equal(rdt['seafloor_pressure'], [10.2504], 4)
passing &= self.assert_array_almost_equal(rdt['absolute_pressure'], [14.8670], 4)
return passing
def check_rsn_instrument_data_product(self):
passing = True
# for RS03AXBS-MJ03A-06-PRESTA301 (PREST-A) there are a few listed data products
# Parsed, Engineering
# SFLPRES-0 SFLPRES-1
# Check for the two data products and make sure they have the proper parameters
# SFLPRES-0 should
data_products, _ = self.RR.find_resources_ext(alt_id_ns='PRE', alt_id='RS03AXBS-MJ03A-06-PRESTA301_SFLPRES_L0_DPID', id_only=True)
passing &=self.assertTrue(len(data_products)==1)
if not data_products:
return passing
data_product_id = data_products[0]
stream_defs, _ = self.RR.find_objects(data_product_id,PRED.hasStreamDefinition,id_only=False)
passing &= self.assertTrue(len(stream_defs)==1)
if not stream_defs:
return passing
# Assert that the stream definition has the correct reference designator
stream_def = stream_defs[0]
passing &= self.assertEquals(stream_def.stream_configuration['reference_designator'], 'RS03AXBS-MJ03A-06-PRESTA301')
# Get the pdict and make sure that the parameters corresponding to the available fields
# begin with the appropriate data product identifier
pdict_ids, _ = self.RR.find_objects(stream_def, PRED.hasParameterDictionary, id_only=True)
passing &= self.assertEquals(len(pdict_ids), 1)
if not pdict_ids:
return passing
pdict_id = pdict_ids[0]
pdict = DatasetManagementService.get_parameter_dictionary(pdict_id)
available_params = [pdict.get_context(i) for i in pdict.keys() if i in stream_def.available_fields]
for p in available_params:
if p.name=='time': # Ignore the domain parameter
continue
passing &= self.assertTrue(p.ooi_short_name.startswith('SFLPRES'))
passing &= self.check_presta_instrument_data_products('RS01SLBS-MJ01A-06-PRESTA101')
passing &= self.check_vel3d_instrument_data_products( 'RS01SLBS-MJ01A-12-VEL3DB101')
passing &= self.check_presta_instrument_data_products('RS03AXBS-MJ03A-06-PRESTA301')
passing &= self.check_vel3d_instrument_data_products( 'RS03AXBS-MJ03A-12-VEL3DB301')
passing &= self.check_tempsf_instrument_data_product( 'RS03ASHS-MJ03B-07-TMPSFA301')
passing &= self.check_vel3d_instrument_data_products( 'RS03INT2-MJ03D-12-VEL3DB304')
passing &= self.check_trhph_instrument_data_products( 'RS03INT1-MJ03C-10-TRHPHA301')
self.data_product_management.activate_data_product_persistence(data_product_id)
dataset_id = self.RR2.find_dataset_id_of_data_product_using_has_dataset(data_product_id)
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
self.assert_array_almost_equal(rdt['seafloor_pressure'], [10.2504], 4)
self.assert_array_almost_equal(rdt['absolute_pressure'], [14.8670], 4)
self.data_product_management.suspend_data_product_persistence(data_product_id) # Should do nothing and not raise anything
return passing
def check_glider(self):
'''
# Check that glider GP05MOAS-GL001 assembly is defined by OOI preload (3 instruments)
'''
passing = True
GP05MOAS_GL001_device = self.retrieve_ooi_asset('GP05MOAS-GL001_PD')
child_devs, assns =self.RR.find_objects(subject=GP05MOAS_GL001_device._id, predicate=PRED.hasDevice, id_only=True)
passing &= self.assertEquals(len(child_devs), 3)
# Set GP05MOAS-GL001 Deployment to DEPLOYED
GP05MOAS_GL001_deploy = self.retrieve_ooi_asset('GP05MOAS-GL001_DEP')
passing &= self.transition_lcs_then_verify(resource_id=GP05MOAS_GL001_deploy._id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
# Activate Deployment for GP05MOAS-GL001
#self.OMS.activate_deployment(GP05MOAS_GL001_deploy._id)
# Deactivate Deployment for GP05MOAS-GL001
#self.OMS.deactivate_deployment(GP05MOAS_GL001_deploy._id)
# Create a new Deployment resource X without any assignment
x_deploy_id = self.create_basic_deployment(name='X_Deployment', description='new Deployment resource X without any assignment')
# Assign Deployment X to site GP05MOAS-GL001
GP05MOAS_GL001_psite = self.retrieve_ooi_asset('GP05MOAS-GL001')
self.OMS.deploy_platform_site(GP05MOAS_GL001_psite._id, x_deploy_id)
# Assign Deployment X to first device for GP05MOAS-GL001
GP05MOAS_GL001_device = self.retrieve_ooi_asset('GP05MOAS-GL001_PD')
self.IMS.deploy_platform_device(GP05MOAS_GL001_device._id, x_deploy_id)
# Set GP05MOAS-GL001 Deployment to PLANNED state
#self.transition_lcs_then_verify(resource_id=x_deploy_id, new_lcs_state=LCE.PLAN, verify='PLANNED')
# ??? already in planned
# Set second GP05MOAS-GL001 Deployment to DEPLOYED
passing &= self.transition_lcs_then_verify(resource_id=x_deploy_id, new_lcs_state=LCE.DEPLOY, verify='DEPLOYED')
self.dump_deployment(x_deploy_id)
# Activate second Deployment for GP05MOAS-GL001
#self.OMS.activate_deployment(x_deploy_id)
# Deactivate second Deployment for GP05MOAS-GL001
#self.OMS.deactivate_deployment(x_deploy_id)
return passing
def check_cg_assembly(self):
passing = True
# Set several CE01ISSM-RI002-* instrument devices to DEVELOPED state
# Assemble several CE01ISSM-RI002-* instruments to a CG CE01ISSM-RI002 component platform
# Set several CE01ISSM-RI002-* instrument devices to INTEGRATED state
# Assemble CE01ISSM-RI002 platform to CG CE01ISSM-LM001 station platform
# Set CE01ISSM-RI002 component device to INTEGRATED state
# Set CE01ISSM-LM001 station device to INTEGRATED state
# Set CE01ISSM-LM001 station device to DEPLOYED state (children maybe too?)
# Set CE01ISSM-LM001 Deployment to DEPLOYED
# Activate CE01ISSM-LM001 platform assembly deployment
# Dectivate CE01ISSM-LM001 platform assembly deployment
# Set CE01ISSM-LM001 Deployment to INTEGRATED state
# Set CE01ISSM-LM001 station device to INTEGRATED state
# Set CE01ISSM-RI002 component device to INTEGRATED state
# Set CE01ISSM-RI002 component device to INTEGRATED state
# Disassemble CE01ISSM-RI002 platform from CG CE01ISSM-LM001 station platform
# Disassemble all CE01ISSM-RI002-* instruments from a CG CE01ISSM-RI002 component platform
# Retire instrument one for CE01ISSM-RI002-*
# Retire device one for CE01ISSM-RI002
# Retire device one for CE01ISSM-LM001
return passing
# -------------------------------------------------------------------------
def retrieve_ooi_asset(self, alt_id='', namespace='PRE'):
dp_list, _ = self.RR.find_resources_ext(alt_id_ns=namespace, alt_id=alt_id)
self.assertEquals(len(dp_list), 1)
return dp_list[0]
def transition_lcs_then_verify(self, resource_id, new_lcs_state, verify):
ret = self.RR2.advance_lcs(resource_id, new_lcs_state)
resource_obj = self.RR.read(resource_id)
return self.assertEquals(resource_obj.lcstate, verify)
def create_basic_deployment(self, name='', description=''):
start = IonTime(datetime.datetime(2013,1,1))
end = IonTime(datetime.datetime(2014,1,1))
temporal_bounds = IonObject(OT.TemporalBounds, name='planned', start_datetime=start.to_string(), end_datetime=end.to_string())
deployment_obj = IonObject(RT.Deployment,
name=name,
description=description,
context=IonObject(OT.CabledNodeDeploymentContext),
constraint_list=[temporal_bounds])
return self.OMS.create_deployment(deployment_obj)
def validate_deployment_activated(self, deployment_id=''):
site_id, device_id = self.get_deployment_ids(deployment_id)
assocs = self.RR.find_associations(subject=site_id, predicate=PRED.hasDevice, object=device_id)
return self.assertEquals(len(assocs), 1)
def validate_deployment_deactivated(self, deployment_id=''):
site_id, device_id = self.get_deployment_ids(deployment_id)
assocs = self.RR.find_associations(subject=site_id, predicate=PRED.hasDevice, object=device_id)
return self.assertEquals(len(assocs), 0)
def dump_deployment(self, deployment_id='', name=""):
#site_id, device_id = self.get_deployment_ids(deployment_id)
resource_list,_ = self.RR.find_subjects(predicate=PRED.hasDeployment, object=deployment_id, id_only=True)
resource_list.append(deployment_id)
resources = self.RR.read_mult(resource_list )
log.debug('--------- dump_deployment %s summary---------------', name)
for resource in resources:
log.debug('%s: %s (%s)', resource._get_type(), resource.name, resource._id)
log.debug('--------- dump_deployment %s full dump ---------------', name)
for resource in resources:
log.debug('resource: %s ', resource)
log.debug('--------- dump_deployment %s end ---------------', name)
#assocs = self.container.resource_registry.find_assoctiations(anyside=deployment_id)
# assocs = Container.instance.resource_registry.find_assoctiations(anyside=deployment_id)
# log.debug('--------- dump_deployment ---------------')
# for assoc in assocs:
# log.debug('SUBJECT: %s PREDICATE: %s OBJET: %s', assoc.s, assoc.p, assoc.o)
# log.debug('--------- dump_deployment end ---------------')
def get_deployment_ids(self, deployment_id=''):
devices = []
sites = []
idevice_list,_ = self.RR.find_subjects(RT.InstrumentDevice, PRED.hasDeployment, deployment_id, id_only=True)
pdevice_list,_ = self.RR.find_subjects(RT.PlatformDevice, PRED.hasDeployment, deployment_id, id_only=True)
devices = idevice_list + pdevice_list
self.assertEquals(1, len(devices))
isite_list,_ = self.RR.find_subjects(RT.InstrumentSite, PRED.hasDeployment, deployment_id, id_only=True)
psite_list,_ = self.RR.find_subjects(RT.PlatformSite, PRED.hasDeployment, deployment_id, id_only=True)
sites = isite_list + psite_list
self.assertEquals(1, len(sites))
return sites[0], devices[0]
def _find_resource_in_list(self, res_list, attr, attr_val, assert_found=True):
for res in res_list:
v = getattr(res, attr, None)
if v == attr_val:
return res
if assert_found:
self.assertTrue(False, "Attribute %s value %s not found in list" % (attr, attr_val))
return None
# -------------------------------------------------------------------------
def _get_caller(self):
s = inspect.stack()
return "%s:%s" % (s[2][1], s[2][2])
@assertion_wrapper
def assert_array_almost_equal(self, *args, **kwargs):
np.testing.assert_array_almost_equal(*args, **kwargs)
@assertion_wrapper
def assertEquals(self, *args, **kwargs):
IonIntegrationTestCase.assertEquals(self, *args, **kwargs)
@assertion_wrapper
def assertTrue(self, *args, **kwargs):
IonIntegrationTestCase.assertTrue(self, *args, **kwargs)
class TestDataProductManagementServiceIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
#print 'instantiating container'
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dpsc_cli = DataProductManagementServiceClient(node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.ingestclient = IngestionManagementServiceClient(node=self.container.node)
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.unsc = UserNotificationServiceClient()
self.data_retriever = DataRetrieverServiceClient()
#------------------------------------------
# Create the environment
#------------------------------------------
datastore_name = CACHE_DATASTORE_NAME
self.db = self.container.datastore_manager.get_datastore(datastore_name)
self.stream_def_id = self.pubsubcli.create_stream_definition(name='SBE37_CDM')
self.process_definitions = {}
ingestion_worker_definition = ProcessDefinition(name='ingestion worker')
ingestion_worker_definition.executable = {
'module':'ion.processes.data.ingestion.science_granule_ingestion_worker',
'class' :'ScienceGranuleIngestionWorker'
}
process_definition_id = self.process_dispatcher.create_process_definition(process_definition=ingestion_worker_definition)
self.process_definitions['ingestion_worker'] = process_definition_id
self.pids = []
self.exchange_points = []
self.exchange_names = []
#------------------------------------------------------------------------------------------------
# First launch the ingestors
#------------------------------------------------------------------------------------------------
self.exchange_space = 'science_granule_ingestion'
self.exchange_point = 'science_data'
config = DotDict()
config.process.datastore_name = 'datasets'
config.process.queue_name = self.exchange_space
self.exchange_names.append(self.exchange_space)
self.exchange_points.append(self.exchange_point)
pid = self.process_dispatcher.schedule_process(self.process_definitions['ingestion_worker'],configuration=config)
log.debug("the ingestion worker process id: %s", pid)
self.pids.append(pid)
self.addCleanup(self.cleaning_up)
def cleaning_up(self):
for pid in self.pids:
log.debug("number of pids to be terminated: %s", len(self.pids))
try:
self.process_dispatcher.cancel_process(pid)
log.debug("Terminated the process: %s", pid)
except:
log.debug("could not terminate the process id: %s" % pid)
IngestionManagementIntTest.clean_subscriptions()
for xn in self.exchange_names:
xni = self.container.ex_manager.create_xn_queue(xn)
xni.delete()
for xp in self.exchange_points:
xpi = self.container.ex_manager.create_xp(xp)
xpi.delete()
def get_datastore(self, dataset_id):
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def test_create_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
parameter_dictionary_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict')
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=parameter_dictionary_id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
# Generic time-series data domain creation
tdom, sdom = time_series_domain()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom.dump(),
spatial_domain = sdom.dump())
dp_obj.geospatial_bounds.geospatial_latitude_limit_north = 200.0
dp_obj.geospatial_bounds.geospatial_latitude_limit_south = 100.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_east = 50.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_west = 100.0
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product( data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
self.assertEquals(dp_obj.geospatial_point_center.lat, 150.0)
log.debug('Created data product %s', dp_obj)
#------------------------------------------------------------------------------------------------
# test creating a new data product with a stream definition
#------------------------------------------------------------------------------------------------
log.debug('Creating new data product with a stream definition')
dp_obj = IonObject(RT.DataProduct,
name='DP2',
description='some new dp',
temporal_domain = tdom.dump(),
spatial_domain = sdom.dump())
dp_id2 = self.dpsc_cli.create_data_product(dp_obj, ctd_stream_def_id)
self.dpsc_cli.activate_data_product_persistence(dp_id2)
log.debug('new dp_id = %s' % dp_id2)
#------------------------------------------------------------------------------------------------
#make sure data product is associated with stream def
#------------------------------------------------------------------------------------------------
streamdefs = []
streams, _ = self.rrclient.find_objects(dp_id2, PRED.hasStream, RT.Stream, True)
for s in streams:
log.debug("Checking stream %s" % s)
sdefs, _ = self.rrclient.find_objects(s, PRED.hasStreamDefinition, RT.StreamDefinition, True)
for sd in sdefs:
log.debug("Checking streamdef %s" % sd)
streamdefs.append(sd)
self.assertIn(ctd_stream_def_id, streamdefs)
# test reading a non-existent data product
log.debug('reading non-existent data product')
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product('some_fake_id')
# update a data product (tests read also)
log.debug('Updating data product')
# first get the existing dp object
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# now tweak the object
dp_obj.description = 'the very first dp'
dp_obj.geospatial_bounds.geospatial_latitude_limit_north = 300.0
dp_obj.geospatial_bounds.geospatial_latitude_limit_south = 200.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_east = 150.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_west = 200.0
# now write the dp back to the registry
update_result = self.dpsc_cli.update_data_product(dp_obj)
# now get the dp back to see if it was updated
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertEquals(dp_obj.description,'the very first dp')
self.assertEquals(dp_obj.geospatial_point_center.lat, 250.0)
log.debug('Updated data product %s', dp_obj)
#test extension
extended_product = self.dpsc_cli.get_data_product_extension(dp_id)
self.assertEqual(dp_id, extended_product._id)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.product_download_size_estimated.status)
self.assertEqual(0, extended_product.computed.product_download_size_estimated.value)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.parameters.status)
#log.debug("test_create_data_product: parameters %s" % extended_product.computed.parameters.value)
# now 'delete' the data product
log.debug("deleting data product: %s" % dp_id)
self.dpsc_cli.delete_data_product(dp_id)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# Get the events corresponding to the data product
ret = self.unsc.get_recent_events(resource_id=dp_id)
events = ret.value
for event in events:
log.debug("event time: %s" % event.ts_created)
self.assertTrue(len(events) > 0)
def test_data_product_stream_def(self):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=pdict_id)
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom,
spatial_domain = sdom)
dp_id = self.dpsc_cli.create_data_product(data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
stream_def_id = self.dpsc_cli.get_data_product_stream_definition(dp_id)
self.assertEquals(ctd_stream_def_id, stream_def_id)
def test_activate_suspend_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=pdict_id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
# Construct temporal and spatial Coordinate Reference System objects
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom,
spatial_domain = sdom)
log.debug("Created an IonObject for a data product: %s" % dp_obj)
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product(data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test activate and suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
dataset_ids, _ = self.rrclient.find_objects(subject=dp_id, predicate=PRED.hasDataset, id_only=True)
if not dataset_ids:
raise NotFound("Data Product %s dataset does not exist" % str(dp_id))
self.get_datastore(dataset_ids[0])
# Check that the streams associated with the data product are persisted with
stream_ids, _ = self.rrclient.find_objects(dp_id,PRED.hasStream,RT.Stream,True)
for stream_id in stream_ids:
self.assertTrue(self.ingestclient.is_persisted(stream_id))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_ids[0])
self.assertIsInstance(replay_data, Granule)
log.debug("The data retriever was able to replay the dataset that was attached to the data product "
"we wanted to be persisted. Therefore the data product was indeed persisted with "
"otherwise we could not have retrieved its dataset using the data retriever. Therefore "
"this demonstration shows that L4-CI-SA-RQ-267 is satisfied: 'Data product management shall persist data products'")
data_product_object = self.rrclient.read(dp_id)
self.assertEquals(data_product_object.name,'DP1')
self.assertEquals(data_product_object.description,'some new dp')
log.debug("Towards L4-CI-SA-RQ-308: 'Data product management shall persist data product metadata'. "
" Attributes in create for the data product obj, name= '%s', description='%s', match those of object from the "
"resource registry, name='%s', desc='%s'" % (dp_obj.name, dp_obj.description,data_product_object.name,
data_product_object.description))
#------------------------------------------------------------------------------------------------
# test suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.suspend_data_product_persistence(dp_id)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.rrclient.read(dp_id)
class TestDMEnd2End(IonIntegrationTestCase):
def setUp(self): # Love the non pep-8 convention
self._start_container()
self.container.start_rel_from_url("res/deploy/r2deploy.yml")
self.process_dispatcher = ProcessDispatcherServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.ingestion_management = IngestionManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.pids = []
self.event = Event()
self.exchange_space_name = "test_granules"
self.exchange_point_name = "science_data"
self.i = 0
self.purge_queues()
self.queue_buffer = []
self.streams = []
self.addCleanup(self.stop_all_ingestion)
def purge_queues(self):
xn = self.container.ex_manager.create_xn_queue("science_granule_ingestion")
xn.purge()
def tearDown(self):
self.purge_queues()
for pid in self.pids:
self.container.proc_manager.terminate_process(pid)
IngestionManagementIntTest.clean_subscriptions()
for queue in self.queue_buffer:
if isinstance(queue, ExchangeNameQueue):
queue.delete()
elif isinstance(queue, str):
xn = self.container.ex_manager.create_xn_queue(queue)
xn.delete()
# --------------------------------------------------------------------------------
# Helper/Utility methods
# --------------------------------------------------------------------------------
def create_dataset(self, parameter_dict_id=""):
"""
Creates a time-series dataset
"""
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
if not parameter_dict_id:
parameter_dict_id = self.dataset_management.read_parameter_dictionary_by_name(
"ctd_parsed_param_dict", id_only=True
)
dataset_id = self.dataset_management.create_dataset(
"test_dataset_%i" % self.i,
parameter_dictionary_id=parameter_dict_id,
spatial_domain=sdom,
temporal_domain=tdom,
)
return dataset_id
def get_datastore(self, dataset_id):
"""
Gets an instance of the datastore
This method is primarily used to defeat a bug where integration tests in multiple containers may sometimes
delete a CouchDB datastore and the other containers are unaware of the new state of the datastore.
"""
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def get_ingestion_config(self):
"""
Grab the ingestion configuration from the resource registry
"""
# The ingestion configuration should have been created by the bootstrap service
# which is configured through r2deploy.yml
ingest_configs, _ = self.resource_registry.find_resources(restype=RT.IngestionConfiguration, id_only=True)
return ingest_configs[0]
def launch_producer(self, stream_id=""):
"""
Launch the producer
"""
pid = self.container.spawn_process(
"better_data_producer",
"ion.processes.data.example_data_producer",
"BetterDataProducer",
{"process": {"stream_id": stream_id}},
)
self.pids.append(pid)
def make_simple_dataset(self):
"""
Makes a stream, a stream definition and a dataset, the essentials for most of these tests
"""
pdict_id = self.dataset_management.read_parameter_dictionary_by_name("ctd_parsed_param_dict", id_only=True)
stream_def_id = self.pubsub_management.create_stream_definition("ctd data", parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream(
"ctd stream %i" % self.i, "xp1", stream_definition_id=stream_def_id
)
dataset_id = self.create_dataset(pdict_id)
self.get_datastore(dataset_id)
self.i += 1
return stream_id, route, stream_def_id, dataset_id
def publish_hifi(self, stream_id, stream_route, offset=0):
"""
Publish deterministic data
"""
pub = StandaloneStreamPublisher(stream_id, stream_route)
stream_def = self.pubsub_management.read_stream_definition(stream_id=stream_id)
stream_def_id = stream_def._id
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt["time"] = np.arange(10) + (offset * 10)
rdt["temp"] = np.arange(10) + (offset * 10)
pub.publish(rdt.to_granule())
def publish_fake_data(self, stream_id, route):
"""
Make four granules
"""
for i in xrange(4):
self.publish_hifi(stream_id, route, i)
def start_ingestion(self, stream_id, dataset_id):
"""
Starts ingestion/persistence for a given dataset
"""
ingest_config_id = self.get_ingestion_config()
self.ingestion_management.persist_data_stream(
stream_id=stream_id, ingestion_configuration_id=ingest_config_id, dataset_id=dataset_id
)
def stop_ingestion(self, stream_id):
ingest_config_id = self.get_ingestion_config()
self.ingestion_management.unpersist_data_stream(
stream_id=stream_id, ingestion_configuration_id=ingest_config_id
)
def stop_all_ingestion(self):
try:
[self.stop_ingestion(sid) for sid in self.streams]
except:
pass
def validate_granule_subscription(self, msg, route, stream_id):
"""
Validation for granule format
"""
if msg == {}:
return
rdt = RecordDictionaryTool.load_from_granule(msg)
log.info("%s", rdt.pretty_print())
self.assertIsInstance(msg, Granule, "Message is improperly formatted. (%s)" % type(msg))
self.event.set()
def wait_until_we_have_enough_granules(self, dataset_id="", data_size=40):
"""
Loops until there is a sufficient amount of data in the dataset
"""
done = False
with gevent.Timeout(40):
while not done:
extents = self.dataset_management.dataset_extents(dataset_id, "time")[0]
granule = self.data_retriever.retrieve_last_data_points(dataset_id, 1)
rdt = RecordDictionaryTool.load_from_granule(granule)
if rdt["time"] and rdt["time"][0] != rdt._pdict.get_context("time").fill_value and extents >= data_size:
done = True
else:
gevent.sleep(0.2)
# --------------------------------------------------------------------------------
# Test Methods
# --------------------------------------------------------------------------------
@attr("SMOKE")
def test_dm_end_2_end(self):
# --------------------------------------------------------------------------------
# Set up a stream and have a mock instrument (producer) send data
# --------------------------------------------------------------------------------
self.event.clear()
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name("ctd_parsed_param_dict", id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext("binary", param_type=ArrayType())
context_ids.append(self.dataset_management.create_parameter_context("binary", bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext("records", param_type=RecordType())
context_ids.append(self.dataset_management.create_parameter_context("records", rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary(
"replay_pdict", parameter_context_ids=context_ids, temporal_context="time"
)
stream_definition = self.pubsub_management.create_stream_definition(
"ctd data", parameter_dictionary_id=pdict_id
)
stream_id, route = self.pubsub_management.create_stream(
"producer", exchange_point=self.exchange_point_name, stream_definition_id=stream_definition
)
# --------------------------------------------------------------------------------
# Start persisting the data on the stream
# - Get the ingestion configuration from the resource registry
# - Create the dataset
# - call persist_data_stream to setup the subscription for the ingestion workers
# on the stream that you specify which causes the data to be persisted
# --------------------------------------------------------------------------------
ingest_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(
stream_id=stream_id, ingestion_configuration_id=ingest_config_id, dataset_id=dataset_id
)
# --------------------------------------------------------------------------------
# Now the granules are ingesting and persisted
# --------------------------------------------------------------------------------
self.launch_producer(stream_id)
self.wait_until_we_have_enough_granules(dataset_id, 40)
# --------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
# --------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_id)
self.assertIsInstance(replay_data, Granule)
rdt = RecordDictionaryTool.load_from_granule(replay_data)
self.assertTrue((rdt["time"][:10] == np.arange(10)).all(), "%s" % rdt["time"][:])
self.assertTrue((rdt["binary"][:10] == np.array(["hi"] * 10, dtype="object")).all())
# --------------------------------------------------------------------------------
# Now to try the streamed approach
# --------------------------------------------------------------------------------
replay_stream_id, replay_route = self.pubsub_management.create_stream(
"replay_out", exchange_point=self.exchange_point_name, stream_definition_id=stream_definition
)
self.replay_id, process_id = self.data_retriever.define_replay(
dataset_id=dataset_id, stream_id=replay_stream_id
)
log.info("Process ID: %s", process_id)
replay_client = ReplayClient(process_id)
# --------------------------------------------------------------------------------
# Create the listening endpoint for the the retriever to talk to
# --------------------------------------------------------------------------------
xp = self.container.ex_manager.create_xp(self.exchange_point_name)
subscriber = StandaloneStreamSubscriber(self.exchange_space_name, self.validate_granule_subscription)
self.queue_buffer.append(self.exchange_space_name)
subscriber.start()
subscriber.xn.bind(replay_route.routing_key, xp)
self.data_retriever.start_replay_agent(self.replay_id)
self.assertTrue(replay_client.await_agent_ready(5), "The process never launched")
replay_client.start_replay()
self.assertTrue(self.event.wait(10))
subscriber.stop()
self.data_retriever.cancel_replay_agent(self.replay_id)
# --------------------------------------------------------------------------------
# Test the slicing capabilities
# --------------------------------------------------------------------------------
granule = self.data_retriever.retrieve(dataset_id=dataset_id, query={"tdoa": slice(0, 5)})
rdt = RecordDictionaryTool.load_from_granule(granule)
b = rdt["time"] == np.arange(5)
self.assertTrue(b.all() if not isinstance(b, bool) else b)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
@unittest.skip("Doesnt work")
@attr("LOCOINT")
@unittest.skipIf(os.getenv("CEI_LAUNCH_TEST", False), "Skip test while in CEI LAUNCH mode")
def test_replay_pause(self):
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name("ctd_parsed_param_dict", id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext("binary", param_type=ArrayType())
context_ids.append(self.dataset_management.create_parameter_context("binary", bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext("records", param_type=RecordType())
context_ids.append(self.dataset_management.create_parameter_context("records", rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary(
"replay_pdict", parameter_context_ids=context_ids, temporal_context="time"
)
stream_def_id = self.pubsub_management.create_stream_definition(
"replay_stream", parameter_dictionary_id=pdict_id
)
replay_stream, replay_route = self.pubsub_management.create_stream(
"replay", "xp1", stream_definition_id=stream_def_id
)
dataset_id = self.create_dataset(pdict_id)
scov = DatasetManagementService._get_coverage(dataset_id)
bb = CoverageCraft(scov)
bb.rdt["time"] = np.arange(100)
bb.rdt["temp"] = np.random.random(100) + 30
bb.sync_with_granule()
DatasetManagementService._persist_coverage(
dataset_id, bb.coverage
) # This invalidates it for multi-host configurations
# Set up the subscriber to verify the data
subscriber = StandaloneStreamSubscriber(self.exchange_space_name, self.validate_granule_subscription)
xp = self.container.ex_manager.create_xp("xp1")
self.queue_buffer.append(self.exchange_space_name)
subscriber.start()
subscriber.xn.bind(replay_route.routing_key, xp)
# Set up the replay agent and the client wrapper
# 1) Define the Replay (dataset and stream to publish on)
self.replay_id, process_id = self.data_retriever.define_replay(dataset_id=dataset_id, stream_id=replay_stream)
# 2) Make a client to the interact with the process (optionall provide it a process to bind with)
replay_client = ReplayClient(process_id)
# 3) Start the agent (launch the process)
self.data_retriever.start_replay_agent(self.replay_id)
# 4) Start replaying...
replay_client.start_replay()
# Wait till we get some granules
self.assertTrue(self.event.wait(5))
# We got granules, pause the replay, clear the queue and allow the process to finish consuming
replay_client.pause_replay()
gevent.sleep(1)
subscriber.xn.purge()
self.event.clear()
# Make sure there's no remaining messages being consumed
self.assertFalse(self.event.wait(1))
# Resume the replay and wait until we start getting granules again
replay_client.resume_replay()
self.assertTrue(self.event.wait(5))
# Stop the replay, clear the queues
replay_client.stop_replay()
gevent.sleep(1)
subscriber.xn.purge()
self.event.clear()
# Make sure that it did indeed stop
self.assertFalse(self.event.wait(1))
subscriber.stop()
def test_retrieve_and_transform(self):
# Make a simple dataset and start ingestion, pretty standard stuff.
ctd_stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(ctd_stream_id, dataset_id)
# Stream definition for the salinity data
salinity_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
"ctd_parsed_param_dict", id_only=True
)
sal_stream_def_id = self.pubsub_management.create_stream_definition(
"sal data", parameter_dictionary_id=salinity_pdict_id
)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt["time"] = np.arange(10)
rdt["temp"] = np.random.randn(10) * 10 + 30
rdt["conductivity"] = np.random.randn(10) * 2 + 10
rdt["pressure"] = np.random.randn(10) * 1 + 12
publisher = StandaloneStreamPublisher(ctd_stream_id, route)
publisher.publish(rdt.to_granule())
rdt["time"] = np.arange(10, 20)
publisher.publish(rdt.to_granule())
self.wait_until_we_have_enough_granules(dataset_id, 20)
granule = self.data_retriever.retrieve(
dataset_id,
None,
None,
"ion.processes.data.transforms.ctd.ctd_L2_salinity",
"CTDL2SalinityTransformAlgorithm",
kwargs=dict(params=sal_stream_def_id),
)
rdt = RecordDictionaryTool.load_from_granule(granule)
for i in rdt["salinity"]:
self.assertNotEquals(i, 0)
self.streams.append(ctd_stream_id)
self.stop_ingestion(ctd_stream_id)
def test_last_granule(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
self.publish_hifi(stream_id, route, 0)
self.publish_hifi(stream_id, route, 1)
self.wait_until_we_have_enough_granules(dataset_id, 20) # I just need two
success = False
def verifier():
replay_granule = self.data_retriever.retrieve_last_data_points(dataset_id, 10)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt["time"] == np.arange(10) + 10
if not isinstance(comp, bool):
return comp.all()
return False
success = poll(verifier)
self.assertTrue(success)
success = False
def verify_points():
replay_granule = self.data_retriever.retrieve_last_data_points(dataset_id, 5)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt["time"] == np.arange(15, 20)
if not isinstance(comp, bool):
return comp.all()
return False
success = poll(verify_points)
self.assertTrue(success)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
def test_replay_with_parameters(self):
# --------------------------------------------------------------------------------
# Create the configurations and the dataset
# --------------------------------------------------------------------------------
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name("ctd_parsed_param_dict", id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext("binary", param_type=ArrayType())
context_ids.append(self.dataset_management.create_parameter_context("binary", bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext("records", param_type=RecordType())
context_ids.append(self.dataset_management.create_parameter_context("records", rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary(
"replay_pdict", parameter_context_ids=context_ids, temporal_context="time"
)
stream_def_id = self.pubsub_management.create_stream_definition(
"replay_stream", parameter_dictionary_id=pdict_id
)
stream_id, route = self.pubsub_management.create_stream(
"replay_with_params", exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id
)
config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(
stream_id=stream_id, ingestion_configuration_id=config_id, dataset_id=dataset_id
)
# --------------------------------------------------------------------------------
# Coerce the datastore into existence (beats race condition)
# --------------------------------------------------------------------------------
self.get_datastore(dataset_id)
self.launch_producer(stream_id)
self.wait_until_we_have_enough_granules(dataset_id, 40)
query = {
"start_time": 0 - 2208988800,
"end_time": 20 - 2208988800,
"stride_time": 2,
"parameters": ["time", "temp"],
}
retrieved_data = self.data_retriever.retrieve(dataset_id=dataset_id, query=query)
rdt = RecordDictionaryTool.load_from_granule(retrieved_data)
comp = np.arange(0, 20, 2) == rdt["time"]
self.assertTrue(comp.all(), "%s" % rdt.pretty_print())
self.assertEquals(set(rdt.iterkeys()), set(["time", "temp"]))
extents = self.dataset_management.dataset_extents(dataset_id=dataset_id, parameters=["time", "temp"])
self.assertTrue(extents["time"] >= 20)
self.assertTrue(extents["temp"] >= 20)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
def test_repersist_data(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
self.publish_hifi(stream_id, route, 0)
self.publish_hifi(stream_id, route, 1)
self.wait_until_we_have_enough_granules(dataset_id, 20)
config_id = self.get_ingestion_config()
self.ingestion_management.unpersist_data_stream(stream_id=stream_id, ingestion_configuration_id=config_id)
self.ingestion_management.persist_data_stream(
stream_id=stream_id, ingestion_configuration_id=config_id, dataset_id=dataset_id
)
self.publish_hifi(stream_id, route, 2)
self.publish_hifi(stream_id, route, 3)
self.wait_until_we_have_enough_granules(dataset_id, 40)
success = False
with gevent.timeout.Timeout(5):
while not success:
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt["time"] == np.arange(0, 40)
if not isinstance(comp, bool):
success = comp.all()
gevent.sleep(1)
self.assertTrue(success)
self.streams.append(stream_id)
self.stop_ingestion(stream_id)
@attr("LOCOINT")
@unittest.skipIf(
os.getenv("CEI_LAUNCH_TEST", False),
"Host requires file-system access to coverage files, CEI mode does not support.",
)
def test_correct_time(self):
# There are 2208988800 seconds between Jan 1 1900 and Jan 1 1970, i.e.
# the conversion factor between unix and NTP time
unix_now = np.floor(time.time())
ntp_now = unix_now + 2208988800
unix_ago = unix_now - 20
ntp_ago = unix_ago + 2208988800
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
coverage = DatasetManagementService._get_coverage(dataset_id)
coverage.insert_timesteps(20)
coverage.set_parameter_values("time", np.arange(ntp_ago, ntp_now))
temporal_bounds = self.dataset_management.dataset_temporal_bounds(dataset_id)
self.assertTrue(np.abs(temporal_bounds[0] - unix_ago) < 2)
self.assertTrue(np.abs(temporal_bounds[1] - unix_now) < 2)
@attr("LOCOINT")
@unittest.skipIf(
os.getenv("CEI_LAUNCH_TEST", False),
"Host requires file-system access to coverage files, CEI mode does not support.",
)
def test_empty_coverage_time(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
coverage = DatasetManagementService._get_coverage(dataset_id)
temporal_bounds = self.dataset_management.dataset_temporal_bounds(dataset_id)
self.assertEquals([coverage.get_parameter_context("time").fill_value] * 2, temporal_bounds)
@attr("LOCOINT")
@unittest.skipIf(
os.getenv("CEI_LAUNCH_TEST", False),
"Host requires file-system access to coverage files, CEI mode does not support.",
)
def test_out_of_band_retrieve(self):
# Setup the environemnt
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
# Fill the dataset
self.publish_fake_data(stream_id, route)
self.wait_until_we_have_enough_granules(dataset_id, 40)
# Retrieve the data
granule = DataRetrieverService.retrieve_oob(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
self.assertTrue((rdt["time"] == np.arange(40)).all())
@attr("LOCOINT")
@unittest.skipIf(
os.getenv("CEI_LAUNCH_TEST", False),
"Host requires file-system access to coverage files, CEI mode does not support.",
)
def test_retrieve_cache(self):
DataRetrieverService._refresh_interval = 1
datasets = [self.make_simple_dataset() for i in xrange(10)]
for stream_id, route, stream_def_id, dataset_id in datasets:
coverage = DatasetManagementService._get_coverage(dataset_id)
coverage.insert_timesteps(10)
coverage.set_parameter_values("time", np.arange(10))
coverage.set_parameter_values("temp", np.arange(10))
# Verify cache hit and refresh
dataset_ids = [i[3] for i in datasets]
self.assertTrue(dataset_ids[0] not in DataRetrieverService._retrieve_cache)
DataRetrieverService._get_coverage(dataset_ids[0]) # Hit the chache
cov, age = DataRetrieverService._retrieve_cache[dataset_ids[0]]
# Verify that it was hit and it's now in there
self.assertTrue(dataset_ids[0] in DataRetrieverService._retrieve_cache)
gevent.sleep(DataRetrieverService._refresh_interval + 0.2)
DataRetrieverService._get_coverage(dataset_ids[0]) # Hit the chache
cov, age2 = DataRetrieverService._retrieve_cache[dataset_ids[0]]
self.assertTrue(age2 != age)
for dataset_id in dataset_ids:
DataRetrieverService._get_coverage(dataset_id)
self.assertTrue(dataset_ids[0] not in DataRetrieverService._retrieve_cache)
stream_id, route, stream_def, dataset_id = datasets[0]
self.start_ingestion(stream_id, dataset_id)
DataRetrieverService._get_coverage(dataset_id)
self.assertTrue(dataset_id in DataRetrieverService._retrieve_cache)
DataRetrieverService._refresh_interval = 100
self.publish_hifi(stream_id, route, 1)
self.wait_until_we_have_enough_granules(dataset_id, data_size=20)
event = gevent.event.Event()
with gevent.Timeout(20):
while not event.wait(0.1):
if dataset_id not in DataRetrieverService._retrieve_cache:
event.set()
self.assertTrue(event.is_set())
@unittest.skip("Outdated due to ingestion retry")
@attr("LOCOINT")
@unittest.skipIf(
os.getenv("CEI_LAUNCH_TEST", False),
"Host requires file-system access to coverage files, CEI mode does not support.",
)
def test_ingestion_failover(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
event = Event()
def cb(*args, **kwargs):
event.set()
sub = EventSubscriber(event_type="ExceptionEvent", callback=cb, origin="stream_exception")
sub.start()
self.publish_fake_data(stream_id, route)
self.wait_until_we_have_enough_granules(dataset_id, 40)
file_path = DatasetManagementService._get_coverage_path(dataset_id)
master_file = os.path.join(file_path, "%s_master.hdf5" % dataset_id)
with open(master_file, "w") as f:
f.write("this will crash HDF")
self.publish_hifi(stream_id, route, 5)
self.assertTrue(event.wait(10))
sub.stop()
class TestDMEnd2End(IonIntegrationTestCase):
def setUp(self): # Love the non pep-8 convention
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.process_dispatcher = ProcessDispatcherServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.ingestion_management = IngestionManagementServiceClient()
self.data_retriever = DataRetrieverServiceClient()
self.event = Event()
self.exchange_space_name = 'test_granules'
self.exchange_point_name = 'science_data'
self.i = 0
self.cci = 0
#--------------------------------------------------------------------------------
# Helper/Utility methods
#--------------------------------------------------------------------------------
def create_dataset(self, parameter_dict_id=''):
'''
Creates a time-series dataset
'''
if not parameter_dict_id:
parameter_dict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
dataset = Dataset('test_dataset_%i'%self.i)
dataset_id = self.dataset_management.create_dataset(dataset, parameter_dictionary_id=parameter_dict_id)
self.addCleanup(self.dataset_management.delete_dataset, dataset_id)
return dataset_id
def get_datastore(self, dataset_id):
'''
Gets an instance of the datastore
This method is primarily used to defeat a bug where integration tests in multiple containers may sometimes
delete a CouchDB datastore and the other containers are unaware of the new state of the datastore.
'''
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def get_ingestion_config(self):
'''
Grab the ingestion configuration from the resource registry
'''
# The ingestion configuration should have been created by the bootstrap service
# which is configured through r2deploy.yml
ingest_configs, _ = self.resource_registry.find_resources(restype=RT.IngestionConfiguration,id_only=True)
return ingest_configs[0]
def launch_producer(self, stream_id=''):
'''
Launch the producer
'''
pid = self.container.spawn_process('better_data_producer', 'ion.processes.data.example_data_producer', 'BetterDataProducer', {'process':{'stream_id':stream_id}})
self.addCleanup(self.container.terminate_process, pid)
def make_simple_dataset(self):
'''
Makes a stream, a stream definition and a dataset, the essentials for most of these tests
'''
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
stream_def_id = self.pubsub_management.create_stream_definition('ctd data %i' % self.i, parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
stream_id, route = self.pubsub_management.create_stream('ctd stream %i' % self.i, 'xp1', stream_definition_id=stream_def_id)
self.addCleanup(self.pubsub_management.delete_stream, stream_id)
dataset_id = self.create_dataset(pdict_id)
# self.get_datastore(dataset_id)
self.i += 1
return stream_id, route, stream_def_id, dataset_id
def publish_hifi(self,stream_id,stream_route,offset=0):
'''
Publish deterministic data
'''
pub = StandaloneStreamPublisher(stream_id, stream_route)
stream_def = self.pubsub_management.read_stream_definition(stream_id=stream_id)
stream_def_id = stream_def._id
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(10) + (offset * 10)
rdt['temp'] = np.arange(10) + (offset * 10)
pub.publish(rdt.to_granule())
def publish_fake_data(self,stream_id, route):
'''
Make four granules
'''
for i in xrange(4):
self.publish_hifi(stream_id,route,i)
def start_ingestion(self, stream_id, dataset_id):
'''
Starts ingestion/persistence for a given dataset
'''
ingest_config_id = self.get_ingestion_config()
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingest_config_id, dataset_id=dataset_id)
def stop_ingestion(self, stream_id):
ingest_config_id = self.get_ingestion_config()
self.ingestion_management.unpersist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingest_config_id)
def validate_granule_subscription(self, msg, route, stream_id):
'''
Validation for granule format
'''
if msg == {}:
return
rdt = RecordDictionaryTool.load_from_granule(msg)
log.info('%s', rdt.pretty_print())
self.assertIsInstance(msg,Granule,'Message is improperly formatted. (%s)' % type(msg))
self.event.set()
def wait_until_we_have_enough_granules(self, dataset_id='',data_size=40):
'''
Loops until there is a sufficient amount of data in the dataset
'''
done = False
with gevent.Timeout(40):
while not done:
extents = self.dataset_management.dataset_extents(dataset_id, 'time')
granule = self.data_retriever.retrieve_last_data_points(dataset_id, 1)
rdt = RecordDictionaryTool.load_from_granule(granule)
if rdt['time'] and rdt['time'][0] != rdt._pdict.get_context('time').fill_value and extents >= data_size:
done = True
else:
gevent.sleep(0.2)
#--------------------------------------------------------------------------------
# Test Methods
#--------------------------------------------------------------------------------
def test_dm_end_2_end(self):
#--------------------------------------------------------------------------------
# Set up a stream and have a mock instrument (producer) send data
#--------------------------------------------------------------------------------
self.event.clear()
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict',id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext('binary', param_type=ArrayType())
context_ids.append(self.dataset_management.create_parameter_context('binary', bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext('records', param_type=RecordType())
context_ids.append(self.dataset_management.create_parameter_context('records', rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary('replay_pdict', parameter_context_ids=context_ids, temporal_context='time')
stream_definition = self.pubsub_management.create_stream_definition('ctd data', parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream('producer', exchange_point=self.exchange_point_name, stream_definition_id=stream_definition)
#--------------------------------------------------------------------------------
# Start persisting the data on the stream
# - Get the ingestion configuration from the resource registry
# - Create the dataset
# - call persist_data_stream to setup the subscription for the ingestion workers
# on the stream that you specify which causes the data to be persisted
#--------------------------------------------------------------------------------
ingest_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingest_config_id, dataset_id=dataset_id)
self.addCleanup(self.stop_ingestion, stream_id)
#--------------------------------------------------------------------------------
# Now the granules are ingesting and persisted
#--------------------------------------------------------------------------------
self.launch_producer(stream_id)
self.wait_until_we_have_enough_granules(dataset_id,40)
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_id)
self.assertIsInstance(replay_data, Granule)
rdt = RecordDictionaryTool.load_from_granule(replay_data)
self.assertTrue((rdt['time'][:10] == np.arange(10)).all(),'%s' % rdt['time'][:])
self.assertTrue((rdt['binary'][:10] == np.array(['hi']*10, dtype='object')).all())
#--------------------------------------------------------------------------------
# Now to try the streamed approach
#--------------------------------------------------------------------------------
replay_stream_id, replay_route = self.pubsub_management.create_stream('replay_out', exchange_point=self.exchange_point_name, stream_definition_id=stream_definition)
self.replay_id, process_id = self.data_retriever.define_replay(dataset_id=dataset_id, stream_id=replay_stream_id)
log.info('Process ID: %s', process_id)
replay_client = ReplayClient(process_id)
#--------------------------------------------------------------------------------
# Create the listening endpoint for the the retriever to talk to
#--------------------------------------------------------------------------------
sub_id = self.pubsub_management.create_subscription(self.exchange_space_name,stream_ids=[replay_stream_id])
self.addCleanup(self.pubsub_management.delete_subscription, sub_id)
self.pubsub_management.activate_subscription(sub_id)
self.addCleanup(self.pubsub_management.deactivate_subscription, sub_id)
subscriber = StandaloneStreamSubscriber(self.exchange_space_name, self.validate_granule_subscription)
subscriber.start()
self.addCleanup(subscriber.stop)
self.data_retriever.start_replay_agent(self.replay_id)
self.assertTrue(replay_client.await_agent_ready(5), 'The process never launched')
replay_client.start_replay()
self.assertTrue(self.event.wait(10))
self.data_retriever.cancel_replay_agent(self.replay_id)
#--------------------------------------------------------------------------------
# Test the slicing capabilities
#--------------------------------------------------------------------------------
granule = self.data_retriever.retrieve(dataset_id=dataset_id, query={'tdoa':slice(0,5)})
rdt = RecordDictionaryTool.load_from_granule(granule)
b = rdt['time'] == np.arange(5)
self.assertTrue(b.all() if not isinstance(b,bool) else b)
def test_coverage_transform(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_parsed()
stream_def_id = self.pubsub_management.create_stream_definition('ctd parsed', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
stream_id, route = self.pubsub_management.create_stream('example', exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id)
self.addCleanup(self.pubsub_management.delete_stream, stream_id)
ingestion_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingestion_config_id, dataset_id=dataset_id)
self.addCleanup(self.ingestion_management.unpersist_data_stream, stream_id, ingestion_config_id)
publisher = StandaloneStreamPublisher(stream_id, route)
rdt = ph.get_rdt(stream_def_id)
ph.fill_parsed_rdt(rdt)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_monitor.wait())
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_array_almost_equal(rdt_out['time'], rdt['time'])
np.testing.assert_array_almost_equal(rdt_out['temp'], rdt['temp'])
np.testing.assert_allclose(rdt_out['conductivity_L1'], np.array([42.914]))
np.testing.assert_allclose(rdt_out['temp_L1'], np.array([20.]))
np.testing.assert_allclose(rdt_out['pressure_L1'], np.array([3.068]))
np.testing.assert_allclose(rdt_out['density'], np.array([1021.7144739593881], dtype='float32'))
np.testing.assert_allclose(rdt_out['salinity'], np.array([30.935132729668283], dtype='float32'))
def test_ingestion_pause(self):
ctd_stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
ingestion_config_id = self.get_ingestion_config()
self.start_ingestion(ctd_stream_id, dataset_id)
self.addCleanup(self.stop_ingestion, ctd_stream_id)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(10)
publisher = StandaloneStreamPublisher(ctd_stream_id, route)
monitor = DatasetMonitor(dataset_id)
self.addCleanup(monitor.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(monitor.wait())
granule = self.data_retriever.retrieve(dataset_id)
self.ingestion_management.pause_data_stream(ctd_stream_id, ingestion_config_id)
monitor.event.clear()
rdt['time'] = np.arange(10,20)
publisher.publish(rdt.to_granule())
self.assertFalse(monitor.event.wait(1))
self.ingestion_management.resume_data_stream(ctd_stream_id, ingestion_config_id)
self.assertTrue(monitor.wait())
granule = self.data_retriever.retrieve(dataset_id)
rdt2 = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_almost_equal(rdt2['time'], np.arange(20))
def test_last_granule(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
self.addCleanup(self.stop_ingestion, stream_id)
self.publish_hifi(stream_id,route, 0)
self.publish_hifi(stream_id,route, 1)
self.wait_until_we_have_enough_granules(dataset_id,20) # I just need two
success = False
def verifier():
replay_granule = self.data_retriever.retrieve_last_data_points(dataset_id, 10)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(10) + 10
if not isinstance(comp,bool):
return comp.all()
return False
success = poll(verifier)
self.assertTrue(success)
success = False
def verify_points():
replay_granule = self.data_retriever.retrieve_last_data_points(dataset_id,5)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(15,20)
if not isinstance(comp,bool):
return comp.all()
return False
success = poll(verify_points)
self.assertTrue(success)
def test_replay_with_parameters(self):
#--------------------------------------------------------------------------------
# Create the configurations and the dataset
#--------------------------------------------------------------------------------
# Get a precompiled parameter dictionary with basic ctd fields
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict',id_only=True)
context_ids = self.dataset_management.read_parameter_contexts(pdict_id, id_only=True)
# Add a field that supports binary data input.
bin_context = ParameterContext('binary', param_type=ArrayType())
context_ids.append(self.dataset_management.create_parameter_context('binary', bin_context.dump()))
# Add another field that supports dictionary elements.
rec_context = ParameterContext('records', param_type=RecordType())
context_ids.append(self.dataset_management.create_parameter_context('records', rec_context.dump()))
pdict_id = self.dataset_management.create_parameter_dictionary('replay_pdict', parameter_context_ids=context_ids, temporal_context='time')
stream_def_id = self.pubsub_management.create_stream_definition('replay_stream', parameter_dictionary_id=pdict_id)
stream_id, route = self.pubsub_management.create_stream('replay_with_params', exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id)
config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=config_id, dataset_id=dataset_id)
self.addCleanup(self.stop_ingestion, stream_id)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
self.publish_fake_data(stream_id, route)
self.assertTrue(dataset_monitor.wait())
query = {
'start_time': 0 - 2208988800,
'end_time': 19 - 2208988800,
'stride_time' : 2,
'parameters': ['time','temp']
}
retrieved_data = self.data_retriever.retrieve(dataset_id=dataset_id,query=query)
rdt = RecordDictionaryTool.load_from_granule(retrieved_data)
np.testing.assert_array_equal(rdt['time'], np.arange(0,20,2))
self.assertEquals(set(rdt.iterkeys()), set(['time','temp']))
extents = self.dataset_management.dataset_extents(dataset_id=dataset_id, parameters=['time','temp'])
self.assertTrue(extents['time']>=20)
self.assertTrue(extents['temp']>=20)
def test_repersist_data(self):
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
self.publish_hifi(stream_id,route,0)
self.publish_hifi(stream_id,route,1)
self.wait_until_we_have_enough_granules(dataset_id,20)
config_id = self.get_ingestion_config()
self.ingestion_management.unpersist_data_stream(stream_id=stream_id,ingestion_configuration_id=config_id)
self.ingestion_management.persist_data_stream(stream_id=stream_id,ingestion_configuration_id=config_id,dataset_id=dataset_id)
self.addCleanup(self.stop_ingestion, stream_id)
self.publish_hifi(stream_id,route,2)
self.publish_hifi(stream_id,route,3)
self.wait_until_we_have_enough_granules(dataset_id,40)
success = False
with gevent.timeout.Timeout(5):
while not success:
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
comp = rdt['time'] == np.arange(0,40)
if not isinstance(comp,bool):
success = comp.all()
gevent.sleep(1)
self.assertTrue(success)
@unittest.skip('deprecated')
def test_correct_time(self):
# There are 2208988800 seconds between Jan 1 1900 and Jan 1 1970, i.e.
# the conversion factor between unix and NTP time
unix_now = np.floor(time.time())
ntp_now = unix_now + 2208988800
unix_ago = unix_now - 20
ntp_ago = unix_ago + 2208988800
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
coverage = DatasetManagementService._get_simplex_coverage(dataset_id, mode='a')
coverage.insert_timesteps(20)
coverage.set_parameter_values('time', np.arange(ntp_ago,ntp_now))
temporal_bounds = self.dataset_management.dataset_temporal_bounds(dataset_id)
self.assertTrue( np.abs(temporal_bounds[0] - unix_ago) < 2)
self.assertTrue( np.abs(temporal_bounds[1] - unix_now) < 2)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Host requires file-system access to coverage files, CEI mode does not support.')
def test_out_of_band_retrieve(self):
# Setup the environemnt
stream_id, route, stream_def_id, dataset_id = self.make_simple_dataset()
self.start_ingestion(stream_id, dataset_id)
# Fill the dataset
self.publish_fake_data(stream_id, route)
self.wait_until_we_have_enough_granules(dataset_id,40)
# Retrieve the data
granule = DataRetrieverService.retrieve_oob(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
self.assertTrue((rdt['time'] == np.arange(40)).all())
def publish_and_wait(self, dataset_id, granule):
stream_ids, _ = self.resource_registry.find_objects(dataset_id, PRED.hasStream,id_only=True)
stream_id=stream_ids[0]
route = self.pubsub_management.read_stream_route(stream_id)
publisher = StandaloneStreamPublisher(stream_id,route)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
publisher.publish(granule)
self.assertTrue(dataset_monitor.wait())
def test_sparse_values(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_sparse()
stream_def_id = self.pubsub_management.create_stream_definition('sparse', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
stream_id, route = self.pubsub_management.create_stream('example', exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id)
self.addCleanup(self.pubsub_management.delete_stream, stream_id)
dataset_id = self.create_dataset(pdict_id)
self.start_ingestion(stream_id,dataset_id)
self.addCleanup(self.stop_ingestion, stream_id)
# Publish initial granule
# the first one has the sparse value set inside it, sets lat to 45 and lon to -71
ntp_now = time.time() + 2208988800
rdt = ph.get_rdt(stream_def_id)
rdt['time'] = [ntp_now]
rdt['internal_timestamp'] = [ntp_now]
rdt['temp'] = [300000]
rdt['preferred_timestamp'] = ['driver_timestamp']
rdt['port_timestamp'] = [ntp_now]
rdt['quality_flag'] = ['']
rdt['lat'] = [45]
rdt['conductivity'] = [4341400]
rdt['driver_timestamp'] = [ntp_now]
rdt['lon'] = [-71]
rdt['pressure'] = [256.8]
publisher = StandaloneStreamPublisher(stream_id, route)
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_monitor.wait())
dataset_monitor.reset()
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
# Check the values and make sure they're correct
np.testing.assert_allclose(rdt_out['time'], rdt['time'])
np.testing.assert_allclose(rdt_out['temp'], rdt['temp'])
np.testing.assert_allclose(rdt_out['lat'], np.array([45]))
np.testing.assert_allclose(rdt_out['lon'], np.array([-71]))
np.testing.assert_allclose(rdt_out['conductivity_L1'], np.array([42.914]))
np.testing.assert_allclose(rdt_out['temp_L1'], np.array([20.]))
np.testing.assert_allclose(rdt_out['pressure_L1'], np.array([3.068]))
np.testing.assert_allclose(rdt_out['density'], np.array([1021.7144739593881], dtype='float32'))
np.testing.assert_allclose(rdt_out['salinity'], np.array([30.935132729668283], dtype='float32'))
# We're going to change the lat/lon
rdt = ph.get_rdt(stream_def_id)
rdt['time'] = time.time() + 2208988800
rdt['lat'] = [46]
rdt['lon'] = [-73]
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_monitor.wait())
dataset_monitor.reset()
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_allclose(rdt_out['time'], rdt['time'])
for i in xrange(9):
ntp_now = time.time() + 2208988800
rdt['time'] = [ntp_now]
rdt['internal_timestamp'] = [ntp_now]
rdt['temp'] = [300000]
rdt['preferred_timestamp'] = ['driver_timestamp']
rdt['port_timestamp'] = [ntp_now]
rdt['quality_flag'] = [None]
rdt['conductivity'] = [4341400]
rdt['driver_timestamp'] = [ntp_now]
rdt['pressure'] = [256.8]
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_monitor.wait())
dataset_monitor.reset()
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_allclose(rdt_out['pressure'], np.array([256.8] * 10))
np.testing.assert_allclose(rdt_out['lat'], np.array([45] + [46] * 9))
np.testing.assert_allclose(rdt_out['lon'], np.array([-71] + [-73] * 9))
class TestActivateInstrumentIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
super(TestActivateInstrumentIntegration, self).setUp()
config = DotDict()
config.bootstrap.use_es = True
self._start_container()
self.addCleanup(TestActivateInstrumentIntegration.es_cleanup)
self.container.start_rel_from_url('res/deploy/r2deploy.yml', config)
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataretrieverclient = DataRetrieverServiceClient(node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
self.usernotificationclient = UserNotificationServiceClient()
#setup listerner vars
self._data_greenlets = []
self._no_samples = None
self._samples_received = []
self.event_publisher = EventPublisher()
@staticmethod
def es_cleanup():
es_host = CFG.get_safe('server.elasticsearch.host', 'localhost')
es_port = CFG.get_safe('server.elasticsearch.port', '9200')
es = ep.ElasticSearch(
host=es_host,
port=es_port,
timeout=10
)
indexes = STD_INDEXES.keys()
indexes.append('%s_resources_index' % get_sys_name().lower())
indexes.append('%s_events_index' % get_sys_name().lower())
for index in indexes:
IndexManagementService._es_call(es.river_couchdb_delete,index)
IndexManagementService._es_call(es.index_delete,index)
def create_logger(self, name, stream_id=''):
# logger process
producer_definition = ProcessDefinition(name=name+'_logger')
producer_definition.executable = {
'module':'ion.processes.data.stream_granule_logger',
'class':'StreamGranuleLogger'
}
logger_procdef_id = self.processdispatchclient.create_process_definition(process_definition=producer_definition)
configuration = {
'process':{
'stream_id':stream_id,
}
}
pid = self.processdispatchclient.schedule_process(process_definition_id=logger_procdef_id,
configuration=configuration)
return pid
def _create_notification(self, user_name = '', instrument_id='', product_id=''):
#--------------------------------------------------------------------------------------
# Make notification request objects
#--------------------------------------------------------------------------------------
notification_request_1 = NotificationRequest( name= 'notification_1',
origin=instrument_id,
origin_type="instrument",
event_type='ResourceLifecycleEvent')
notification_request_2 = NotificationRequest( name='notification_2',
origin=product_id,
origin_type="data product",
event_type='DetectionEvent')
#--------------------------------------------------------------------------------------
# Create a user and get the user_id
#--------------------------------------------------------------------------------------
user = UserInfo()
user.name = user_name
user.contact.email = '*****@*****.**' % user_name
user_id, _ = self.rrclient.create(user)
#--------------------------------------------------------------------------------------
# Create notification
#--------------------------------------------------------------------------------------
self.usernotificationclient.create_notification(notification=notification_request_1, user_id=user_id)
self.usernotificationclient.create_notification(notification=notification_request_2, user_id=user_id)
log.debug( "test_activateInstrumentSample: create_user_notifications user_id %s", str(user_id) )
return user_id
def get_datastore(self, dataset_id):
dataset = self.datasetclient.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def _check_computed_attributes_of_extended_instrument(self, expected_instrument_device_id = '',extended_instrument = None):
# Verify that computed attributes exist for the extended instrument
self.assertIsInstance(extended_instrument.computed.firmware_version, ComputedFloatValue)
self.assertIsInstance(extended_instrument.computed.last_data_received_datetime, ComputedFloatValue)
self.assertIsInstance(extended_instrument.computed.last_calibration_datetime, ComputedFloatValue)
self.assertIsInstance(extended_instrument.computed.uptime, ComputedStringValue)
self.assertIsInstance(extended_instrument.computed.power_status_roll_up, ComputedIntValue)
self.assertIsInstance(extended_instrument.computed.communications_status_roll_up, ComputedIntValue)
self.assertIsInstance(extended_instrument.computed.data_status_roll_up, ComputedIntValue)
self.assertIsInstance(extended_instrument.computed.location_status_roll_up, ComputedIntValue)
# the following assert will not work without elasticsearch.
#self.assertEqual( 1, len(extended_instrument.computed.user_notification_requests.value) )
self.assertEqual(extended_instrument.computed.communications_status_roll_up.value, StatusType.STATUS_WARNING)
self.assertEqual(extended_instrument.computed.data_status_roll_up.value, StatusType.STATUS_OK)
self.assertEqual(extended_instrument.computed.power_status_roll_up.value, StatusType.STATUS_WARNING)
# Verify the computed attribute for user notification requests
self.assertEqual( 1, len(extended_instrument.computed.user_notification_requests.value) )
notifications = extended_instrument.computed.user_notification_requests.value
notification = notifications[0]
self.assertEqual(notification.origin, expected_instrument_device_id)
self.assertEqual(notification.origin_type, "instrument")
self.assertEqual(notification.event_type, 'ResourceLifecycleEvent')
def _check_computed_attributes_of_extended_product(self, expected_data_product_id = '', extended_data_product = None):
self.assertEqual(expected_data_product_id, extended_data_product._id)
log.debug("extended_data_product.computed: %s", extended_data_product.computed)
# Verify that computed attributes exist for the extended instrument
self.assertIsInstance(extended_data_product.computed.product_download_size_estimated, ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.number_active_subscriptions, ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.data_url, ComputedStringValue)
self.assertIsInstance(extended_data_product.computed.stored_data_size, ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.recent_granules, ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.parameters, ComputedListValue)
self.assertIsInstance(extended_data_product.computed.recent_events, ComputedEventListValue)
self.assertIsInstance(extended_data_product.computed.provenance, ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.user_notification_requests, ComputedListValue)
self.assertIsInstance(extended_data_product.computed.active_user_subscriptions, ComputedListValue)
self.assertIsInstance(extended_data_product.computed.past_user_subscriptions, ComputedListValue)
self.assertIsInstance(extended_data_product.computed.last_granule, ComputedDictValue)
self.assertIsInstance(extended_data_product.computed.is_persisted, ComputedIntValue)
self.assertIsInstance(extended_data_product.computed.data_contents_updated, ComputedStringValue)
self.assertIsInstance(extended_data_product.computed.data_datetime, ComputedListValue)
# exact text here keeps changing to fit UI capabilities. keep assertion general...
self.assertTrue( 'ok' in extended_data_product.computed.last_granule.value['quality_flag'] )
self.assertEqual( 2, len(extended_data_product.computed.data_datetime.value) )
notifications = extended_data_product.computed.user_notification_requests.value
notification = notifications[0]
self.assertEqual(notification.origin, expected_data_product_id)
self.assertEqual(notification.origin_type, "data product")
self.assertEqual(notification.event_type, 'DetectionEvent')
@attr('LOCOINT')
@unittest.skipIf(not use_es, 'No ElasticSearch')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
@patch.dict(CFG, {'endpoint':{'receive':{'timeout': 60}}})
def test_activateInstrumentSample(self):
self.loggerpids = []
# Create InstrumentModel
instModel_obj = IonObject(RT.InstrumentModel,
name='SBE37IMModel',
description="SBE37IMModel")
instModel_id = self.imsclient.create_instrument_model(instModel_obj)
log.debug( 'new InstrumentModel id = %s ', instModel_id)
#Create stream alarms
"""
test_two_sided_interval
Test interval alarm and alarm event publishing for a closed
inteval.
"""
# kwargs = {
# 'name' : 'test_sim_warning',
# 'stream_name' : 'parsed',
# 'value_id' : 'temp',
# 'message' : 'Temperature is above test range of 5.0.',
# 'type' : StreamAlarmType.WARNING,
# 'upper_bound' : 5.0,
# 'upper_rel_op' : '<'
# }
kwargs = {
'name' : 'temperature_warning_interval',
'stream_name' : 'parsed',
'value_id' : 'temp',
'message' : 'Temperature is below the normal range of 50.0 and above.',
'type' : StreamAlarmType.WARNING,
'lower_bound' : 50.0,
'lower_rel_op' : '<'
}
# Create alarm object.
alarm = {}
alarm['type'] = 'IntervalAlarmDef'
alarm['kwargs'] = kwargs
raw_config = StreamConfiguration(stream_name='raw', parameter_dictionary_name='ctd_raw_param_dict', records_per_granule=2, granule_publish_rate=5 )
parsed_config = StreamConfiguration(stream_name='parsed', parameter_dictionary_name='ctd_parsed_param_dict', records_per_granule=2, granule_publish_rate=5, alarms=[alarm] )
# Create InstrumentAgent
instAgent_obj = IonObject(RT.InstrumentAgent,
name='agent007',
description="SBE37IMAgent",
driver_uri="http://sddevrepo.oceanobservatories.org/releases/seabird_sbe37smb_ooicore-0.0.1a-py2.7.egg",
stream_configurations = [raw_config, parsed_config])
instAgent_id = self.imsclient.create_instrument_agent(instAgent_obj)
log.debug('new InstrumentAgent id = %s', instAgent_id)
self.imsclient.assign_instrument_model_to_instrument_agent(instModel_id, instAgent_id)
# Create InstrumentDevice
log.debug('test_activateInstrumentSample: Create instrument resource to represent the SBE37 (SA Req: L4-CI-SA-RQ-241) ')
instDevice_obj = IonObject(RT.InstrumentDevice,
name='SBE37IMDevice',
description="SBE37IMDevice",
serial_number="12345" )
instDevice_id = self.imsclient.create_instrument_device(instrument_device=instDevice_obj)
self.imsclient.assign_instrument_model_to_instrument_device(instModel_id, instDevice_id)
log.debug("test_activateInstrumentSample: new InstrumentDevice id = %s (SA Req: L4-CI-SA-RQ-241) " , instDevice_id)
port_agent_config = {
'device_addr': CFG.device.sbe37.host,
'device_port': CFG.device.sbe37.port,
'process_type': PortAgentProcessType.UNIX,
'binary_path': "port_agent",
'port_agent_addr': 'localhost',
'command_port': CFG.device.sbe37.port_agent_cmd_port,
'data_port': CFG.device.sbe37.port_agent_data_port,
'log_level': 5,
'type': PortAgentType.ETHERNET
}
instAgentInstance_obj = IonObject(RT.InstrumentAgentInstance, name='SBE37IMAgentInstance',
description="SBE37IMAgentInstance",
port_agent_config = port_agent_config)
instAgentInstance_id = self.imsclient.create_instrument_agent_instance(instAgentInstance_obj,
instAgent_id,
instDevice_id)
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
parsed_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
parsed_stream_def_id = self.pubsubcli.create_stream_definition(name='parsed', parameter_dictionary_id=parsed_pdict_id)
raw_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_raw_param_dict', id_only=True)
raw_stream_def_id = self.pubsubcli.create_stream_definition(name='raw', parameter_dictionary_id=raw_pdict_id)
#-------------------------------
# Create Raw and Parsed Data Products for the device
#-------------------------------
dp_obj = IonObject(RT.DataProduct,
name='the parsed data',
description='ctd stream test',
temporal_domain = tdom,
spatial_domain = sdom)
data_product_id1 = self.dpclient.create_data_product(data_product=dp_obj, stream_definition_id=parsed_stream_def_id)
log.debug( 'new dp_id = %s' , data_product_id1)
self.dpclient.activate_data_product_persistence(data_product_id=data_product_id1)
self.damsclient.assign_data_product(input_resource_id=instDevice_id, data_product_id=data_product_id1)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id1, PRED.hasStream, None, True)
log.debug('Data product streams1 = %s', stream_ids)
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id1, PRED.hasDataset, RT.Dataset, True)
log.debug('Data set for data_product_id1 = %s' , dataset_ids[0])
self.parsed_dataset = dataset_ids[0]
pid = self.create_logger('ctd_parsed', stream_ids[0] )
self.loggerpids.append(pid)
dp_obj = IonObject(RT.DataProduct,
name='the raw data',
description='raw stream test',
temporal_domain = tdom,
spatial_domain = sdom)
data_product_id2 = self.dpclient.create_data_product(data_product=dp_obj, stream_definition_id=raw_stream_def_id)
log.debug('new dp_id = %s', data_product_id2)
self.damsclient.assign_data_product(input_resource_id=instDevice_id, data_product_id=data_product_id2)
self.dpclient.activate_data_product_persistence(data_product_id=data_product_id2)
# setup notifications for the device and parsed data product
user_id_1 = self._create_notification( user_name='user_1', instrument_id=instDevice_id, product_id=data_product_id1)
#---------- Create notifications for another user and verify that we see different computed subscriptions for the two users ---------
user_id_2 = self._create_notification( user_name='user_2', instrument_id=instDevice_id, product_id=data_product_id2)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id2, PRED.hasStream, None, True)
log.debug('Data product streams2 = %s' , str(stream_ids))
# Retrieve the id of the OUTPUT stream from the out Data Product
dataset_ids, _ = self.rrclient.find_objects(data_product_id2, PRED.hasDataset, RT.Dataset, True)
log.debug('Data set for data_product_id2 = %s' , dataset_ids[0])
self.raw_dataset = dataset_ids[0]
#elastic search debug
es_indexes, _ = self.container.resource_registry.find_resources(restype='ElasticSearchIndex')
log.debug('ElasticSearch indexes: %s', [i.name for i in es_indexes])
log.debug('Bootstrap %s', CFG.bootstrap.use_es)
def start_instrument_agent():
self.imsclient.start_instrument_agent_instance(instrument_agent_instance_id=instAgentInstance_id)
gevent.joinall([gevent.spawn(start_instrument_agent)])
#setup a subscriber to alarm events from the device
self._events_received= []
self._event_count = 0
self._samples_out_of_range = 0
self._samples_complete = False
self._async_sample_result = AsyncResult()
def consume_event(*args, **kwargs):
log.debug('TestActivateInstrument recieved ION event: args=%s, kwargs=%s, event=%s.',
str(args), str(kwargs), str(args[0]))
self._events_received.append(args[0])
self._event_count = len(self._events_received)
self._async_sample_result.set()
self._event_subscriber = EventSubscriber(
event_type= 'StreamWarningAlarmEvent', #'StreamWarningAlarmEvent', # StreamAlarmEvent
callback=consume_event,
origin=instDevice_id)
self._event_subscriber.start()
#cleanup
self.addCleanup(self.imsclient.stop_instrument_agent_instance,
instrument_agent_instance_id=instAgentInstance_id)
def stop_subscriber():
self._event_subscriber.stop()
self._event_subscriber = None
self.addCleanup(stop_subscriber)
#wait for start
inst_agent_instance_obj = self.imsclient.read_instrument_agent_instance(instAgentInstance_id)
gate = ProcessStateGate(self.processdispatchclient.read_process,
inst_agent_instance_obj.agent_process_id,
ProcessStateEnum.RUNNING)
self.assertTrue(gate.await(30), "The instrument agent instance (%s) did not spawn in 30 seconds" %
inst_agent_instance_obj.agent_process_id)
log.debug('Instrument agent instance obj: = %s' , str(inst_agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._ia_client = ResourceAgentClient(instDevice_id,
to_name=inst_agent_instance_obj.agent_process_id,
process=FakeProcess())
log.debug("test_activateInstrumentSample: got ia client %s" , str(self._ia_client))
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
retval = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: initialize %s" , str(retval))
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
log.debug("(L4-CI-SA-RQ-334): Sending go_active command ")
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrument: return value from go_active %s" , str(reply))
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.GET_RESOURCE_STATE)
retval = self._ia_client.execute_agent(cmd)
state = retval.result
log.debug("(L4-CI-SA-RQ-334): current state after sending go_active command %s" , str(state))
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: run %s" , str(reply))
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.PAUSE)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.STOPPED)
cmd = AgentCommand(command=ResourceAgentEvent.RESUME)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.CLEAR)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
retval = self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=SBE37ProtocolEvent.ACQUIRE_SAMPLE)
for i in xrange(10):
retval = self._ia_client.execute_resource(cmd)
log.debug("test_activateInstrumentSample: return from sample %s" , str(retval))
log.debug( "test_activateInstrumentSample: calling reset ")
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
reply = self._ia_client.execute_agent(cmd)
log.debug("test_activateInstrumentSample: return from reset %s" , str(reply))
self._samples_complete = True
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.dataretrieverclient.retrieve(self.parsed_dataset)
self.assertIsInstance(replay_data, Granule)
rdt = RecordDictionaryTool.load_from_granule(replay_data)
log.debug("test_activateInstrumentSample: RDT parsed: %s", str(rdt.pretty_print()) )
temp_vals = rdt['temp']
self.assertEquals(len(temp_vals) , 10)
log.debug("test_activateInstrumentSample: all temp_vals: %s", temp_vals )
#out_of_range_temp_vals = [i for i in temp_vals if i > 5]
out_of_range_temp_vals = [i for i in temp_vals if i < 50.0]
log.debug("test_activateInstrumentSample: Out_of_range_temp_vals: %s", out_of_range_temp_vals )
self._samples_out_of_range = len(out_of_range_temp_vals)
# if no bad values were produced, then do not wait for an event
if self._samples_out_of_range == 0:
self._async_sample_result.set()
log.debug("test_activateInstrumentSample: _events_received: %s", self._events_received )
log.debug("test_activateInstrumentSample: _event_count: %s", self._event_count )
self._async_sample_result.get(timeout=CFG.endpoint.receive.timeout)
replay_data = self.dataretrieverclient.retrieve(self.raw_dataset)
self.assertIsInstance(replay_data, Granule)
rdt = RecordDictionaryTool.load_from_granule(replay_data)
log.debug("RDT raw: %s", str(rdt.pretty_print()) )
raw_vals = rdt['raw']
self.assertEquals(len(raw_vals) , 10)
log.debug("l4-ci-sa-rq-138")
"""
Physical resource control shall be subject to policy
Instrument management control capabilities shall be subject to policy
The actor accessing the control capabilities must be authorized to send commands.
note from maurice 2012-05-18: Talk to tim M to verify that this is policy. If it is then talk with Stephen to
get an example of a policy test and use that to create a test stub that will be
completed when we have instrument policies.
Tim M: The "actor", aka observatory operator, will access the instrument through ION.
"""
#--------------------------------------------------------------------------------
# Get the extended data product to see if it contains the granules
#--------------------------------------------------------------------------------
extended_product = self.dpclient.get_data_product_extension(data_product_id=data_product_id1, user_id=user_id_1)
def poller(extended_product):
return len(extended_product.computed.user_notification_requests.value) == 1
poll(poller, extended_product, timeout=30)
self._check_computed_attributes_of_extended_product( expected_data_product_id = data_product_id1, extended_data_product = extended_product)
#--------------------------------------------------------------------------------
#put some events into the eventsdb to test - this should set the comms and data status to WARNING
#--------------------------------------------------------------------------------
t = get_ion_ts()
self.event_publisher.publish_event( ts_created= t, event_type = 'DeviceStatusEvent',
origin = instDevice_id, state=DeviceStatusType.OUT_OF_RANGE, values = [200] )
self.event_publisher.publish_event( ts_created= t, event_type = 'DeviceCommsEvent',
origin = instDevice_id, state=DeviceCommsType.DATA_DELIVERY_INTERRUPTION, lapse_interval_seconds = 20 )
#--------------------------------------------------------------------------------
# Get the extended instrument
#--------------------------------------------------------------------------------
extended_instrument = self.imsclient.get_instrument_device_extension(instrument_device_id=instDevice_id, user_id=user_id_1)
self._check_computed_attributes_of_extended_instrument(expected_instrument_device_id = instDevice_id, extended_instrument = extended_instrument)
#--------------------------------------------------------------------------------
# For the second user, check the extended data product and the extended intrument
#--------------------------------------------------------------------------------
extended_product = self.dpclient.get_data_product_extension(data_product_id=data_product_id2, user_id=user_id_2)
self._check_computed_attributes_of_extended_product(expected_data_product_id = data_product_id2, extended_data_product = extended_product)
#---------- Put some events into the eventsdb to test - this should set the comms and data status to WARNING ---------
t = get_ion_ts()
self.event_publisher.publish_event( ts_created= t, event_type = 'DeviceStatusEvent',
origin = instDevice_id, state=DeviceStatusType.OUT_OF_RANGE, values = [200] )
self.event_publisher.publish_event( ts_created= t, event_type = 'DeviceCommsEvent',
origin = instDevice_id, state=DeviceCommsType.DATA_DELIVERY_INTERRUPTION, lapse_interval_seconds = 20 )
#--------------------------------------------------------------------------------
# Get the extended instrument
#--------------------------------------------------------------------------------
extended_instrument = self.imsclient.get_instrument_device_extension(instrument_device_id=instDevice_id, user_id=user_id_2)
self._check_computed_attributes_of_extended_instrument(expected_instrument_device_id = instDevice_id, extended_instrument = extended_instrument)
#--------------------------------------------------------------------------------
# Deactivate loggers
#--------------------------------------------------------------------------------
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
self.dpclient.delete_data_product(data_product_id1)
self.dpclient.delete_data_product(data_product_id2)
def test_usgs_integration(self):
'''
test_usgs_integration
Test full DM Services Integration using usgs
'''
cc = self.container
assertions = self.assertTrue
#-----------------------------
# Copy below here
#-----------------------------
pubsub_management_service = PubsubManagementServiceClient(node=cc.node)
ingestion_management_service = IngestionManagementServiceClient(node=cc.node)
dataset_management_service = DatasetManagementServiceClient(node=cc.node)
data_retriever_service = DataRetrieverServiceClient(node=cc.node)
transform_management_service = TransformManagementServiceClient(node=cc.node)
process_dispatcher = ProcessDispatcherServiceClient(node=cc.node)
process_list = []
datasets = []
datastore_name = 'test_usgs_integration'
#---------------------------
# Set up ingestion
#---------------------------
# Configure ingestion using eight workers, ingesting to test_dm_integration datastore with the SCIDATA profile
log.debug('Calling create_ingestion_configuration')
ingestion_configuration_id = ingestion_management_service.create_ingestion_configuration(
exchange_point_id='science_data',
couch_storage=CouchStorage(datastore_name=datastore_name,datastore_profile='SCIDATA'),
number_of_workers=8
)
#
ingestion_management_service.activate_ingestion_configuration(
ingestion_configuration_id=ingestion_configuration_id)
usgs_stream_def = USGS_stream_definition()
stream_def_id = pubsub_management_service.create_stream_definition(container=usgs_stream_def, name='Junk definition')
#---------------------------
# Set up the producers (CTD Simulators)
#---------------------------
# Launch five simulated CTD producers
for iteration in xrange(2):
# Make a stream to output on
stream_id = pubsub_management_service.create_stream(stream_definition_id=stream_def_id)
#---------------------------
# Set up the datasets
#---------------------------
dataset_id = dataset_management_service.create_dataset(
stream_id=stream_id,
datastore_name=datastore_name,
view_name='datasets/stream_join_granule'
)
# Keep track of the datasets
datasets.append(dataset_id)
stream_policy_id = ingestion_management_service.create_dataset_configuration(
dataset_id = dataset_id,
archive_data = True,
archive_metadata = True,
ingestion_configuration_id = ingestion_configuration_id
)
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module':'ion.agents.eoi.handler.usgs_stream_publisher',
'class':'UsgsPublisher'
}
configuration = {
'process':{
'stream_id':stream_id,
}
}
procdef_id = process_dispatcher.create_process_definition(process_definition=producer_definition)
log.debug('LUKE_DEBUG: procdef_id: %s', procdef_id)
pid = process_dispatcher.schedule_process(process_definition_id=procdef_id, configuration=configuration)
# Keep track, we'll kill 'em later.
process_list.append(pid)
# Get about 4 seconds of data
time.sleep(4)
#---------------------------
# Stop producing data
#---------------------------
for process in process_list:
process_dispatcher.cancel_process(process)
#----------------------------------------------
# The replay and the transform, a love story.
#----------------------------------------------
# Happy Valentines to the clever coder who catches the above!
transform_definition = ProcessDefinition()
transform_definition.executable = {
'module':'ion.processes.data.transforms.transform_example',
'class':'TransformCapture'
}
transform_definition_id = process_dispatcher.create_process_definition(process_definition=transform_definition)
dataset_id = datasets.pop() # Just need one for now
replay_id, stream_id = data_retriever_service.define_replay(dataset_id=dataset_id)
#--------------------------------------------
# I'm Selling magazine subscriptions here!
#--------------------------------------------
subscription = pubsub_management_service.create_subscription(query=StreamQuery(stream_ids=[stream_id]),
exchange_name='transform_capture_point')
#--------------------------------------------
# Start the transform (capture)
#--------------------------------------------
transform_id = transform_management_service.create_transform(
name='capture_transform',
in_subscription_id=subscription,
process_definition_id=transform_definition_id
)
transform_management_service.activate_transform(transform_id=transform_id)
#--------------------------------------------
# BEGIN REPLAY!
#--------------------------------------------
data_retriever_service.start_replay(replay_id=replay_id)
#--------------------------------------------
# Lets get some boundaries
#--------------------------------------------
bounds = dataset_management_service.get_dataset_bounds(dataset_id=dataset_id)
class TestDataProductManagementServiceIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
#print 'instantiating container'
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dpsc_cli = DataProductManagementServiceClient()
self.rrclient = ResourceRegistryServiceClient()
self.damsclient = DataAcquisitionManagementServiceClient()
self.pubsubcli = PubsubManagementServiceClient()
self.ingestclient = IngestionManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.unsc = UserNotificationServiceClient()
self.data_retriever = DataRetrieverServiceClient()
#------------------------------------------
# Create the environment
#------------------------------------------
datastore_name = CACHE_DATASTORE_NAME
self.db = self.container.datastore_manager.get_datastore(datastore_name)
self.stream_def_id = self.pubsubcli.create_stream_definition(name='SBE37_CDM')
self.process_definitions = {}
ingestion_worker_definition = ProcessDefinition(name='ingestion worker')
ingestion_worker_definition.executable = {
'module':'ion.processes.data.ingestion.science_granule_ingestion_worker',
'class' :'ScienceGranuleIngestionWorker'
}
process_definition_id = self.process_dispatcher.create_process_definition(process_definition=ingestion_worker_definition)
self.process_definitions['ingestion_worker'] = process_definition_id
self.pids = []
self.exchange_points = []
self.exchange_names = []
#------------------------------------------------------------------------------------------------
# First launch the ingestors
#------------------------------------------------------------------------------------------------
self.exchange_space = 'science_granule_ingestion'
self.exchange_point = 'science_data'
config = DotDict()
config.process.datastore_name = 'datasets'
config.process.queue_name = self.exchange_space
self.exchange_names.append(self.exchange_space)
self.exchange_points.append(self.exchange_point)
pid = self.process_dispatcher.schedule_process(self.process_definitions['ingestion_worker'],configuration=config)
log.debug("the ingestion worker process id: %s", pid)
self.pids.append(pid)
self.addCleanup(self.cleaning_up)
def cleaning_up(self):
for pid in self.pids:
log.debug("number of pids to be terminated: %s", len(self.pids))
try:
self.process_dispatcher.cancel_process(pid)
log.debug("Terminated the process: %s", pid)
except:
log.debug("could not terminate the process id: %s" % pid)
IngestionManagementIntTest.clean_subscriptions()
for xn in self.exchange_names:
xni = self.container.ex_manager.create_xn_queue(xn)
xni.delete()
for xp in self.exchange_points:
xpi = self.container.ex_manager.create_xp(xp)
xpi.delete()
def get_datastore(self, dataset_id):
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
@attr('EXT')
@attr('PREP')
def test_create_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
parameter_dictionary = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict')
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=parameter_dictionary._id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
# Generic time-series data domain creation
tdom, sdom = time_series_domain()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom.dump(),
spatial_domain = sdom.dump())
dp_obj.geospatial_bounds.geospatial_latitude_limit_north = 10.0
dp_obj.geospatial_bounds.geospatial_latitude_limit_south = -10.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_east = 10.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_west = -10.0
dp_obj.ooi_product_name = "PRODNAME"
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product( data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
# Assert that the data product has an associated stream at this stage
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, RT.Stream, True)
self.assertNotEquals(len(stream_ids), 0)
# Assert that the data product has an associated stream def at this stage
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStreamDefinition, RT.StreamDefinition, True)
self.assertNotEquals(len(stream_ids), 0)
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
self.assertEquals(dp_obj.geospatial_point_center.lat, 0.0)
log.debug('Created data product %s', dp_obj)
#------------------------------------------------------------------------------------------------
# test creating a new data product with a stream definition
#------------------------------------------------------------------------------------------------
log.debug('Creating new data product with a stream definition')
dp_obj = IonObject(RT.DataProduct,
name='DP2',
description='some new dp',
temporal_domain = tdom.dump(),
spatial_domain = sdom.dump())
dp_id2 = self.dpsc_cli.create_data_product(dp_obj, ctd_stream_def_id)
self.dpsc_cli.activate_data_product_persistence(dp_id2)
log.debug('new dp_id = %s' % dp_id2)
#------------------------------------------------------------------------------------------------
#make sure data product is associated with stream def
#------------------------------------------------------------------------------------------------
streamdefs = []
streams, _ = self.rrclient.find_objects(dp_id2, PRED.hasStream, RT.Stream, True)
for s in streams:
log.debug("Checking stream %s" % s)
sdefs, _ = self.rrclient.find_objects(s, PRED.hasStreamDefinition, RT.StreamDefinition, True)
for sd in sdefs:
log.debug("Checking streamdef %s" % sd)
streamdefs.append(sd)
self.assertIn(ctd_stream_def_id, streamdefs)
group_names = self.dpsc_cli.get_data_product_group_list()
self.assertIn("PRODNAME", group_names)
# test reading a non-existent data product
log.debug('reading non-existent data product')
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product('some_fake_id')
# update a data product (tests read also)
log.debug('Updating data product')
# first get the existing dp object
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# now tweak the object
dp_obj.description = 'the very first dp'
dp_obj.geospatial_bounds.geospatial_latitude_limit_north = 20.0
dp_obj.geospatial_bounds.geospatial_latitude_limit_south = -20.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_east = 20.0
dp_obj.geospatial_bounds.geospatial_longitude_limit_west = -20.0
# now write the dp back to the registry
update_result = self.dpsc_cli.update_data_product(dp_obj)
# now get the dp back to see if it was updated
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertEquals(dp_obj.description,'the very first dp')
self.assertEquals(dp_obj.geospatial_point_center.lat, 0.0)
log.debug('Updated data product %s', dp_obj)
#test extension
extended_product = self.dpsc_cli.get_data_product_extension(dp_id)
self.assertEqual(dp_id, extended_product._id)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.product_download_size_estimated.status)
self.assertEqual(0, extended_product.computed.product_download_size_estimated.value)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.parameters.status)
#log.debug("test_create_data_product: parameters %s" % extended_product.computed.parameters.value)
def ion_object_encoder(obj):
return obj.__dict__
#test prepare for create
data_product_data = self.dpsc_cli.prepare_data_product_support()
#print simplejson.dumps(data_product_data, default=ion_object_encoder, indent= 2)
self.assertEqual(data_product_data._id, "")
self.assertEqual(data_product_data.type_, OT.DataProductPrepareSupport)
self.assertEqual(len(data_product_data.associations['StreamDefinition'].resources), 2)
self.assertEqual(len(data_product_data.associations['Dataset'].resources), 0)
self.assertEqual(len(data_product_data.associations['StreamDefinition'].associated_resources), 0)
self.assertEqual(len(data_product_data.associations['Dataset'].associated_resources), 0)
#test prepare for update
data_product_data = self.dpsc_cli.prepare_data_product_support(dp_id)
#print simplejson.dumps(data_product_data, default=ion_object_encoder, indent= 2)
self.assertEqual(data_product_data._id, dp_id)
self.assertEqual(data_product_data.type_, OT.DataProductPrepareSupport)
self.assertEqual(len(data_product_data.associations['StreamDefinition'].resources), 2)
self.assertEqual(len(data_product_data.associations['Dataset'].resources), 1)
self.assertEqual(len(data_product_data.associations['StreamDefinition'].associated_resources), 1)
self.assertEqual(data_product_data.associations['StreamDefinition'].associated_resources[0].s, dp_id)
self.assertEqual(len(data_product_data.associations['Dataset'].associated_resources), 1)
self.assertEqual(data_product_data.associations['Dataset'].associated_resources[0].s, dp_id)
# now 'delete' the data product
log.debug("deleting data product: %s" % dp_id)
self.dpsc_cli.delete_data_product(dp_id)
# Assert that there are no associated streams leftover after deleting the data product
stream_ids, assoc_ids = self.rrclient.find_objects(dp_id, PRED.hasStream, RT.Stream, True)
self.assertEquals(len(stream_ids), 0)
self.assertEquals(len(assoc_ids), 0)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# Get the events corresponding to the data product
ret = self.unsc.get_recent_events(resource_id=dp_id)
events = ret.value
for event in events:
log.debug("event time: %s" % event.ts_created)
self.assertTrue(len(events) > 0)
def test_data_product_stream_def(self):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=pdict_id)
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom,
spatial_domain = sdom)
dp_id = self.dpsc_cli.create_data_product(data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
stream_def_id = self.dpsc_cli.get_data_product_stream_definition(dp_id)
self.assertEquals(ctd_stream_def_id, stream_def_id)
def test_derived_data_product(self):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='ctd parsed', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsubcli.delete_stream_definition, ctd_stream_def_id)
tdom, sdom = time_series_domain()
dp = DataProduct(name='Instrument DP', temporal_domain=tdom.dump(), spatial_domain=sdom.dump())
dp_id = self.dpsc_cli.create_data_product(dp, stream_definition_id=ctd_stream_def_id)
self.addCleanup(self.dpsc_cli.force_delete_data_product, dp_id)
self.dpsc_cli.activate_data_product_persistence(dp_id)
self.addCleanup(self.dpsc_cli.suspend_data_product_persistence, dp_id)
dataset_ids, _ = self.rrclient.find_objects(subject=dp_id, predicate=PRED.hasDataset, id_only=True)
if not dataset_ids:
raise NotFound("Data Product %s dataset does not exist" % str(dp_id))
dataset_id = dataset_ids[0]
# Make the derived data product
simple_stream_def_id = self.pubsubcli.create_stream_definition(name='TEMPWAT stream def', parameter_dictionary_id=pdict_id, available_fields=['time','temp'])
tempwat_dp = DataProduct(name='TEMPWAT')
tempwat_dp_id = self.dpsc_cli.create_data_product(tempwat_dp, stream_definition_id=simple_stream_def_id, parent_data_product_id=dp_id)
self.addCleanup(self.dpsc_cli.delete_data_product, tempwat_dp_id)
# Check that the streams associated with the data product are persisted with
stream_ids, _ = self.rrclient.find_objects(dp_id,PRED.hasStream,RT.Stream,True)
for stream_id in stream_ids:
self.assertTrue(self.ingestclient.is_persisted(stream_id))
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
rdt = RecordDictionaryTool(stream_definition_id=ctd_stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = np.arange(20)
rdt['pressure'] = np.arange(20)
publisher = StandaloneStreamPublisher(stream_id,route)
dataset_modified = Event()
def cb(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb, origin=dataset_id, auto_delete=True)
es.start()
self.addCleanup(es.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
tempwat_dataset_ids, _ = self.rrclient.find_objects(tempwat_dp_id, PRED.hasDataset, id_only=True)
tempwat_dataset_id = tempwat_dataset_ids[0]
granule = self.data_retriever.retrieve(tempwat_dataset_id, delivery_format=simple_stream_def_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt['time'], np.arange(20))
self.assertEquals(set(rdt.fields), set(['time','temp']))
def test_activate_suspend_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=pdict_id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
# Construct temporal and spatial Coordinate Reference System objects
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom,
spatial_domain = sdom)
log.debug("Created an IonObject for a data product: %s" % dp_obj)
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product(data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test activate and suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
dataset_ids, _ = self.rrclient.find_objects(subject=dp_id, predicate=PRED.hasDataset, id_only=True)
if not dataset_ids:
raise NotFound("Data Product %s dataset does not exist" % str(dp_id))
dataset_id = dataset_ids[0]
# Check that the streams associated with the data product are persisted with
stream_ids, _ = self.rrclient.find_objects(dp_id,PRED.hasStream,RT.Stream,True)
for stream_id in stream_ids:
self.assertTrue(self.ingestclient.is_persisted(stream_id))
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
rdt = RecordDictionaryTool(stream_definition_id=ctd_stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = np.arange(20)
publisher = StandaloneStreamPublisher(stream_id,route)
dataset_modified = Event()
def cb(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb, origin=dataset_id, auto_delete=True)
es.start()
self.addCleanup(es.stop)
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_ids[0])
self.assertIsInstance(replay_data, Granule)
log.debug("The data retriever was able to replay the dataset that was attached to the data product "
"we wanted to be persisted. Therefore the data product was indeed persisted with "
"otherwise we could not have retrieved its dataset using the data retriever. Therefore "
"this demonstration shows that L4-CI-SA-RQ-267 is satisfied: 'Data product management shall persist data products'")
data_product_object = self.rrclient.read(dp_id)
self.assertEquals(data_product_object.name,'DP1')
self.assertEquals(data_product_object.description,'some new dp')
log.debug("Towards L4-CI-SA-RQ-308: 'Data product management shall persist data product metadata'. "
" Attributes in create for the data product obj, name= '%s', description='%s', match those of object from the "
"resource registry, name='%s', desc='%s'" % (dp_obj.name, dp_obj.description,data_product_object.name,
data_product_object.description))
#------------------------------------------------------------------------------------------------
# test suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.suspend_data_product_persistence(dp_id)
dataset_modified.clear()
rdt['time'] = np.arange(20,40)
publisher.publish(rdt.to_granule())
self.assertFalse(dataset_modified.wait(2))
self.dpsc_cli.activate_data_product_persistence(dp_id)
dataset_modified.clear()
publisher.publish(rdt.to_granule())
self.assertTrue(dataset_modified.wait(30))
granule = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_almost_equal(rdt['time'], np.arange(40))
dataset_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasDataset, id_only=True)
self.assertEquals(len(dataset_ids), 1)
self.dpsc_cli.suspend_data_product_persistence(dp_id)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.rrclient.read(dp_id)
def test_lookup_values(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_lookups()
stream_def_id = self.pubsubcli.create_stream_definition('lookup', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsubcli.delete_stream_definition, stream_def_id)
data_product = DataProduct(name='lookup data product')
tdom, sdom = time_series_domain()
data_product.temporal_domain = tdom.dump()
data_product.spatial_domain = sdom.dump()
data_product_id = self.dpsc_cli.create_data_product(data_product, stream_definition_id=stream_def_id)
self.addCleanup(self.dpsc_cli.delete_data_product, data_product_id)
data_producer = DataProducer(name='producer')
data_producer.producer_context = DataProcessProducerContext()
data_producer.producer_context.configuration['qc_keys'] = ['offset_document']
data_producer_id, _ = self.rrclient.create(data_producer)
self.addCleanup(self.rrclient.delete, data_producer_id)
assoc,_ = self.rrclient.create_association(subject=data_product_id, object=data_producer_id, predicate=PRED.hasDataProducer)
self.addCleanup(self.rrclient.delete_association, assoc)
document_keys = self.damsclient.list_qc_references(data_product_id)
self.assertEquals(document_keys, ['offset_document'])
svm = StoredValueManager(self.container)
svm.stored_value_cas('offset_document', {'offset_a':2.0})
self.dpsc_cli.activate_data_product_persistence(data_product_id)
dataset_ids, _ = self.rrclient.find_objects(subject=data_product_id, predicate=PRED.hasDataset, id_only=True)
dataset_id = dataset_ids[0]
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [0]
rdt['temp'] = [20.]
granule = rdt.to_granule()
stream_ids, _ = self.rrclient.find_objects(subject=data_product_id, predicate=PRED.hasStream, id_only=True)
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
publisher = StandaloneStreamPublisher(stream_id, route)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(10))
granule = self.data_retriever.retrieve(dataset_id)
rdt2 = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt['temp'], rdt2['temp'])
np.testing.assert_array_almost_equal(rdt2['calibrated'], np.array([22.0]))
svm.stored_value_cas('updated_document', {'offset_a':3.0})
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ep = EventPublisher(event_type=OT.ExternalReferencesUpdatedEvent)
ep.publish_event(origin=data_product_id, reference_keys=['updated_document'])
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [1]
rdt['temp'] = [20.]
granule = rdt.to_granule()
gevent.sleep(2) # Yield so that the event goes through
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(10))
granule = self.data_retriever.retrieve(dataset_id)
rdt2 = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt2['temp'],np.array([20.,20.]))
np.testing.assert_array_almost_equal(rdt2['calibrated'], np.array([22.0,23.0]))
class VisualizationIntegrationTestHelper(IonIntegrationTestCase):
def create_ctd_input_stream_and_data_product(self, data_product_name='ctd_parsed'):
cc = self.container
assertions = self.assertTrue
# Now create client to DataProductManagementService
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubclient = PubsubManagementServiceClient(node=self.container.node)
self.ingestclient = IngestionManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.datasetclient = DatasetManagementServiceClient(node=self.container.node)
self.workflowclient = WorkflowManagementServiceClient(node=self.container.node)
self.process_dispatcher = ProcessDispatcherServiceClient(node=self.container.node)
self.vis_client = VisualizationServiceClient(node=self.container.node)
#-------------------------------
# Create CTD Parsed as the initial data product
#-------------------------------
# create a stream definition for the data from the ctd simulator
ctd_stream_def = SBE37_CDM_stream_definition()
ctd_stream_def_id = self.pubsubclient.create_stream_definition(container=ctd_stream_def, name='Simulated CTD data')
log.debug('Creating new CDM data product with a stream definition')
craft = CoverageCraft
sdom, tdom = craft.create_domains()
sdom = sdom.dump()
tdom = tdom.dump()
parameter_dictionary = craft.create_parameters()
parameter_dictionary = parameter_dictionary.dump()
dp_obj = IonObject(RT.DataProduct,
name=data_product_name,
description='ctd stream test',
temporal_domain = tdom,
spatial_domain = sdom)
ctd_parsed_data_product_id = self.dataproductclient.create_data_product(dp_obj, ctd_stream_def_id, parameter_dictionary)
log.debug('new ctd_parsed_data_product_id = %s' % ctd_parsed_data_product_id)
#Only ever need one device for testing purposes.
instDevice_obj,_ = self.rrclient.find_resources(restype=RT.InstrumentDevice, name='SBE37IMDevice')
if instDevice_obj:
instDevice_id = instDevice_obj[0]._id
else:
instDevice_obj = IonObject(RT.InstrumentDevice, name='SBE37IMDevice', description="SBE37IMDevice", serial_number="12345" )
instDevice_id = self.imsclient.create_instrument_device(instrument_device=instDevice_obj)
self.damsclient.assign_data_product(input_resource_id=instDevice_id, data_product_id=ctd_parsed_data_product_id)
self.dataproductclient.activate_data_product_persistence(data_product_id=ctd_parsed_data_product_id)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(ctd_parsed_data_product_id, PRED.hasStream, None, True)
assertions(len(stream_ids) > 0 )
ctd_stream_id = stream_ids[0]
return ctd_stream_id, ctd_parsed_data_product_id
def create_data_product(self, dp_name = "", dp_description = ""):
craft = CoverageCraft
sdom, tdom = craft.create_domains()
sdom = sdom.dump()
tdom = tdom.dump()
parameter_dictionary = craft.create_parameters() # this creates a ParameterDictionary object
parameter_dictionary = parameter_dictionary.dump() # this returns a python dictionary
data_prod_obj = IonObject(RT.DataProduct,
name=dp_name,
description=dp_description,
temporal_domain = tdom,
spatial_domain = sdom)
data_prod_id = self.create_data_product(data_prod_obj, stream_definition_id, parameter_dictionary)
return data_prod_id, data_prod_obj
def start_simple_input_stream_process(self, ctd_stream_id):
return self.start_input_stream_process(ctd_stream_id)
def start_sinusoidal_input_stream_process(self, ctd_stream_id):
return self.start_input_stream_process(ctd_stream_id, 'ion.processes.data.sinusoidal_stream_publisher', 'SinusoidalCtdPublisher')
def start_input_stream_process(self, ctd_stream_id, module = 'ion.processes.data.ctd_stream_publisher', class_name= 'SimpleCtdPublisher'):
###
### Start the process for producing the CTD data
###
# process definition for the ctd simulator...
producer_definition = ProcessDefinition()
producer_definition.executable = {
'module':module,
'class':class_name
}
ctd_sim_procdef_id = self.process_dispatcher.create_process_definition(process_definition=producer_definition)
# Start the ctd simulator to produce some data
configuration = {
'process':{
'stream_id':ctd_stream_id,
}
}
ctd_sim_pid = self.process_dispatcher.schedule_process(process_definition_id=ctd_sim_procdef_id, configuration=configuration)
return ctd_sim_pid
def start_output_stream_and_listen(self, ctd_stream_id, data_product_stream_ids, message_count_per_stream=10):
cc = self.container
assertions = self.assertTrue
###
### Make a subscriber in the test to listen for transformed data
###
salinity_subscription_id = self.pubsubclient.create_subscription(
query=StreamQuery(data_product_stream_ids),
exchange_name = 'workflow_test',
exchange_point = 'science_data',
name = "test workflow transformations",
)
pid = cc.spawn_process(name='dummy_process_for_test',
module='pyon.ion.process',
cls='SimpleProcess',
config={})
dummy_process = cc.proc_manager.procs[pid]
subscriber_registrar = StreamSubscriberRegistrar(process=dummy_process, container=cc)
result = gevent.event.AsyncResult()
results = []
message_count = len(data_product_stream_ids) * message_count_per_stream
def message_received(message, headers):
# Heads
results.append(message)
if len(results) >= message_count: #Only wait for so many messages - per stream
result.set(True)
subscriber = subscriber_registrar.create_subscriber(exchange_name='workflow_test', callback=message_received)
subscriber.start()
# after the queue has been created it is safe to activate the subscription
self.pubsubclient.activate_subscription(subscription_id=salinity_subscription_id)
#Start the input stream process
if ctd_stream_id is not None:
ctd_sim_pid = self.start_simple_input_stream_process(ctd_stream_id)
# Assert that we have received data
assertions(result.get(timeout=30))
# stop the flow parse the messages...
if ctd_stream_id is not None:
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
self.pubsubclient.deactivate_subscription(subscription_id=salinity_subscription_id)
subscriber.stop()
return results
def validate_messages(self, results):
cc = self.container
assertions = self.assertTrue
first_salinity_values = None
for message in results:
rdt = RecordDictionaryTool.load_from_granule(message)
try:
temp = get_safe(rdt, 'temp')
# psd = PointSupplementStreamParser(stream_definition=self.ctd_stream_def, stream_granule=message)
# temp = psd.get_values('temperature')
# log.info(psd.list_field_names())
except KeyError as ke:
temp = None
if temp is not None:
assertions(isinstance(temp, numpy.ndarray))
log.info( 'temperature=' + str(numpy.nanmin(temp)))
first_salinity_values = None
else:
#psd = PointSupplementStreamParser(stream_definition=SalinityTransform.outgoing_stream_def, stream_granule=message)
#log.info( psd.list_field_names())
# Test the handy info method for the names of fields in the stream def
#assertions('salinity' in psd.list_field_names())
# you have to know the name of the coverage in stream def
salinity = get_safe(rdt, 'salinity')
#salinity = psd.get_values('salinity')
log.info( 'salinity=' + str(numpy.nanmin(salinity)))
# Check to see if salinity has values
assertions(salinity != None)
assertions(isinstance(salinity, numpy.ndarray))
assertions(numpy.nanmin(salinity) > 0.0) # salinity should always be greater than 0
if first_salinity_values is None:
first_salinity_values = salinity.tolist()
else:
second_salinity_values = salinity.tolist()
assertions(len(first_salinity_values) == len(second_salinity_values))
for idx in range(0,len(first_salinity_values)):
assertions(first_salinity_values[idx]*2.0 == second_salinity_values[idx])
def validate_data_ingest_retrieve(self, dataset_id):
assertions = self.assertTrue
self.data_retriever = DataRetrieverServiceClient(node=self.container.node)
#validate that data was ingested
replay_granule = self.data_retriever.retrieve_last_granule(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(replay_granule)
salinity = get_safe(rdt, 'salinity')
assertions(salinity != None)
#retrieve all the granules from the database and check the values
replay_granule_all = self.data_retriever.retrieve(dataset_id)
rdt = RecordDictionaryTool.load_from_granule(replay_granule_all)
for k, v in rdt.iteritems():
if k == 'salinity':
for val in numpy.nditer(v):
assertions(val > 0)
def create_salinity_data_process_definition(self):
# Salinity: Data Process Definition
#First look to see if it exists and if not, then create it
dpd,_ = self.rrclient.find_resources(restype=RT.DataProcessDefinition, name='ctd_salinity')
if len(dpd) > 0:
return dpd[0]
log.debug("Create data process definition SalinityTransform")
dpd_obj = IonObject(RT.DataProcessDefinition,
name='ctd_salinity',
description='create a salinity data product',
module='ion.processes.data.transforms.ctd.ctd_L2_salinity',
class_name='SalinityTransform',
process_source='SalinityTransform source code here...')
try:
ctd_L2_salinity_dprocdef_id = self.dataprocessclient.create_data_process_definition(dpd_obj)
except Excpetion as ex:
self.fail("failed to create new SalinityTransform data process definition: %s" %ex)
# create a stream definition for the data from the salinity Transform
sal_stream_def_id = self.pubsubclient.create_stream_definition(container=SalinityTransform.outgoing_stream_def, name='Salinity')
self.dataprocessclient.assign_stream_definition_to_data_process_definition(sal_stream_def_id, ctd_L2_salinity_dprocdef_id )
return ctd_L2_salinity_dprocdef_id
def create_salinity_doubler_data_process_definition(self):
#First look to see if it exists and if not, then create it
dpd,_ = self.rrclient.find_resources(restype=RT.DataProcessDefinition, name='salinity_doubler')
if len(dpd) > 0:
return dpd[0]
# Salinity Doubler: Data Process Definition
log.debug("Create data process definition SalinityDoublerTransform")
dpd_obj = IonObject(RT.DataProcessDefinition,
name='salinity_doubler',
description='create a salinity doubler data product',
module='ion.processes.data.transforms.example_double_salinity',
class_name='SalinityDoubler',
process_source='SalinityDoubler source code here...')
try:
salinity_doubler_dprocdef_id = self.dataprocessclient.create_data_process_definition(dpd_obj)
except Exception as ex:
self.fail("failed to create new SalinityDoubler data process definition: %s" %ex)
# create a stream definition for the data from the salinity Transform
salinity_double_stream_def_id = self.pubsubclient.create_stream_definition(container=SalinityDoubler.outgoing_stream_def, name='SalinityDoubler')
self.dataprocessclient.assign_stream_definition_to_data_process_definition(salinity_double_stream_def_id, salinity_doubler_dprocdef_id )
return salinity_doubler_dprocdef_id
def create_transform_process(self, data_process_definition_id, data_process_input_dp_id):
data_process_definition = self.rrclient.read(data_process_definition_id)
# Find the link between the output Stream Definition resource and the Data Process Definition resource
stream_ids,_ = self.rrclient.find_objects(data_process_definition._id, PRED.hasStreamDefinition, RT.StreamDefinition, id_only=True)
if not stream_ids:
raise Inconsistent("The data process definition %s is missing an association to an output stream definition" % data_process_definition._id )
process_output_stream_def_id = stream_ids[0]
#Concatenate the name of the workflow and data process definition for the name of the data product output
data_process_name = data_process_definition.name
# Create the output data product of the transform
transform_dp_obj = IonObject(RT.DataProduct, name=data_process_name,description=data_process_definition.description)
transform_dp_id = self.dataproductclient.create_data_product(transform_dp_obj, process_output_stream_def_id)
self.dataproductclient.activate_data_product_persistence(data_product_id=transform_dp_id)
#last one out of the for loop is the output product id
output_data_product_id = transform_dp_id
# Create the transform data process
log.debug("create data_process and start it")
data_process_id = self.dataprocessclient.create_data_process(data_process_definition._id, [data_process_input_dp_id], {'output':transform_dp_id})
self.dataprocessclient.activate_data_process(data_process_id)
#Find the id of the output data stream
stream_ids, _ = self.rrclient.find_objects(transform_dp_id, PRED.hasStream, None, True)
if not stream_ids:
raise Inconsistent("The data process %s is missing an association to an output stream" % data_process_id )
return data_process_id, output_data_product_id
def create_google_dt_data_process_definition(self):
#First look to see if it exists and if not, then create it
dpd,_ = self.rrclient.find_resources(restype=RT.DataProcessDefinition, name='google_dt_transform')
if len(dpd) > 0:
return dpd[0]
# Data Process Definition
log.debug("Create data process definition GoogleDtTransform")
dpd_obj = IonObject(RT.DataProcessDefinition,
name='google_dt_transform',
description='Convert data streams to Google DataTables',
module='ion.processes.data.transforms.viz.google_dt',
class_name='VizTransformGoogleDT',
process_source='VizTransformGoogleDT source code here...')
try:
procdef_id = self.dataprocessclient.create_data_process_definition(dpd_obj)
except Exception as ex:
self.fail("failed to create new VizTransformGoogleDT data process definition: %s" %ex)
# create a stream definition for the data from the
stream_def_id = self.pubsubclient.create_stream_definition(container=VizTransformGoogleDT.outgoing_stream_def, name='VizTransformGoogleDT')
self.dataprocessclient.assign_stream_definition_to_data_process_definition(stream_def_id, procdef_id )
return procdef_id
def validate_google_dt_transform_results(self, results):
cc = self.container
assertions = self.assertTrue
# if its just one granule, wrap it up in a list so we can use the following for loop for a couple of cases
if isinstance(results,Granule):
results =[results]
for g in results:
if isinstance(g,Granule):
tx = TaxyTool.load_from_granule(g)
rdt = RecordDictionaryTool.load_from_granule(g)
gdt_data = get_safe(rdt, 'google_dt_components')
# IF this granule does not contains google dt, skip
if gdt_data == None:
continue
gdt = gdt_data[0]
assertions(gdt['viz_product_type'] == 'google_dt' )
assertions(len(gdt['data_description']) >= 0) # Need to come up with a better check
assertions(len(gdt['data_content']) >= 0)
def create_mpl_graphs_data_process_definition(self):
#First look to see if it exists and if not, then create it
dpd,_ = self.rrclient.find_resources(restype=RT.DataProcessDefinition, name='mpl_graphs_transform')
if len(dpd) > 0:
return dpd[0]
#Data Process Definition
log.debug("Create data process definition MatplotlibGraphsTransform")
dpd_obj = IonObject(RT.DataProcessDefinition,
name='mpl_graphs_transform',
description='Convert data streams to Matplotlib graphs',
module='ion.processes.data.transforms.viz.matplotlib_graphs',
class_name='VizTransformMatplotlibGraphs',
process_source='VizTransformMatplotlibGraphs source code here...')
try:
procdef_id = self.dataprocessclient.create_data_process_definition(dpd_obj)
except Exception as ex:
self.fail("failed to create new VizTransformMatplotlibGraphs data process definition: %s" %ex)
# create a stream definition for the data
stream_def_id = self.pubsubclient.create_stream_definition(container=VizTransformMatplotlibGraphs.outgoing_stream_def, name='VizTransformMatplotlibGraphs')
self.dataprocessclient.assign_stream_definition_to_data_process_definition(stream_def_id, procdef_id )
return procdef_id
def validate_mpl_graphs_transform_results(self, results):
cc = self.container
assertions = self.assertTrue
# if its just one granule, wrap it up in a list so we can use the following for loop for a couple of cases
if isinstance(results,Granule):
results =[results]
for g in results:
if isinstance(g,Granule):
tx = TaxyTool.load_from_granule(g)
rdt = RecordDictionaryTool.load_from_granule(g)
graphs = get_safe(rdt, 'matplotlib_graphs')
if graphs == None:
continue
for graph in graphs[0]:
# At this point only dictionaries containing image data should be passed
# For some reason non dictionary values are filtering through.
if not isinstance(graph, dict):
continue
assertions(graph['viz_product_type'] == 'matplotlib_graphs' )
# check to see if the list (numpy array) contains actual images
assertions(imghdr.what(graph['image_name'], h = graph['image_obj']) == 'png')
def validate_vis_service_google_dt_results(self, results):
assertions = self.assertTrue
assertions(results)
gdt_str = (results.lstrip("google.visualization.Query.setResponse(")).rstrip(")")
assertions(len(gdt_str) > 0)
return
def validate_vis_service_mpl_graphs_results(self, results):
assertions = self.assertTrue
assertions(results)
# check to see if the object passed is a dictionary with a valid image object in it
image_format = results["content_type"].lstrip("image/")
assertions(imghdr.what(results['image_name'], h = base64.decodestring(results['image_obj'])) == image_format)
return
class TestDataProductManagementServiceIntegration(IonIntegrationTestCase):
def setUp(self):
# Start container
#print 'instantiating container'
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dpsc_cli = DataProductManagementServiceClient(node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.ingestclient = IngestionManagementServiceClient(node=self.container.node)
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.unsc = UserNotificationServiceClient()
self.data_retriever = DataRetrieverServiceClient()
#------------------------------------------
# Create the environment
#------------------------------------------
datastore_name = CACHE_DATASTORE_NAME
self.db = self.container.datastore_manager.get_datastore(datastore_name)
self.stream_def_id = self.pubsubcli.create_stream_definition(name='SBE37_CDM')
self.process_definitions = {}
ingestion_worker_definition = ProcessDefinition(name='ingestion worker')
ingestion_worker_definition.executable = {
'module':'ion.processes.data.ingestion.science_granule_ingestion_worker',
'class' :'ScienceGranuleIngestionWorker'
}
process_definition_id = self.process_dispatcher.create_process_definition(process_definition=ingestion_worker_definition)
self.process_definitions['ingestion_worker'] = process_definition_id
self.pids = []
self.exchange_points = []
self.exchange_names = []
#------------------------------------------------------------------------------------------------
# First launch the ingestors
#------------------------------------------------------------------------------------------------
self.exchange_space = 'science_granule_ingestion'
self.exchange_point = 'science_data'
config = DotDict()
config.process.datastore_name = 'datasets'
config.process.queue_name = self.exchange_space
self.exchange_names.append(self.exchange_space)
self.exchange_points.append(self.exchange_point)
pid = self.process_dispatcher.schedule_process(self.process_definitions['ingestion_worker'],configuration=config)
log.debug("the ingestion worker process id: %s", pid)
self.pids.append(pid)
self.addCleanup(self.cleaning_up)
def cleaning_up(self):
for pid in self.pids:
log.debug("number of pids to be terminated: %s", len(self.pids))
try:
self.process_dispatcher.cancel_process(pid)
log.debug("Terminated the process: %s", pid)
except:
log.debug("could not terminate the process id: %s" % pid)
IngestionManagementIntTest.clean_subscriptions()
for xn in self.exchange_names:
xni = self.container.ex_manager.create_xn_queue(xn)
xni.delete()
for xp in self.exchange_points:
xpi = self.container.ex_manager.create_xp(xp)
xpi.delete()
def get_datastore(self, dataset_id):
dataset = self.dataset_management.read_dataset(dataset_id)
datastore_name = dataset.datastore_name
datastore = self.container.datastore_manager.get_datastore(datastore_name, DataStore.DS_PROFILE.SCIDATA)
return datastore
def test_create_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
parameter_dictionary_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict')
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=parameter_dictionary_id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
# Generic time-series data domain creation
tdom, sdom = time_series_domain()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom.dump(),
spatial_domain = sdom.dump())
log.debug("Created an IonObject for a data product: %s" % dp_obj)
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product( data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
#------------------------------------------------------------------------------------------------
# test creating a new data product with a stream definition
#------------------------------------------------------------------------------------------------
log.debug('Creating new data product with a stream definition')
dp_obj = IonObject(RT.DataProduct,
name='DP2',
description='some new dp',
temporal_domain = tdom.dump(),
spatial_domain = sdom.dump())
dp_id2 = self.dpsc_cli.create_data_product(dp_obj, ctd_stream_def_id)
self.dpsc_cli.activate_data_product_persistence(dp_id2)
log.debug('new dp_id = %s' % dp_id2)
#------------------------------------------------------------------------------------------------
#make sure data product is associated with stream def
#------------------------------------------------------------------------------------------------
streamdefs = []
streams, _ = self.rrclient.find_objects(dp_id2, PRED.hasStream, RT.Stream, True)
for s in streams:
log.debug("Checking stream %s" % s)
sdefs, _ = self.rrclient.find_objects(s, PRED.hasStreamDefinition, RT.StreamDefinition, True)
for sd in sdefs:
log.debug("Checking streamdef %s" % sd)
streamdefs.append(sd)
self.assertIn(ctd_stream_def_id, streamdefs)
# test reading a non-existent data product
log.debug('reading non-existent data product')
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product('some_fake_id')
# update a data product (tests read also)
log.debug('Updating data product')
# first get the existing dp object
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# now tweak the object
dp_obj.description = 'the very first dp'
# now write the dp back to the registry
update_result = self.dpsc_cli.update_data_product(dp_obj)
# now get the dp back to see if it was updated
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertEquals(dp_obj.description,'the very first dp')
#test extension
extended_product = self.dpsc_cli.get_data_product_extension(dp_id)
self.assertEqual(dp_id, extended_product._id)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.product_download_size_estimated.status)
self.assertEqual(0, extended_product.computed.product_download_size_estimated.value)
self.assertEqual(ComputedValueAvailability.PROVIDED,
extended_product.computed.parameters.status)
#log.debug("test_create_data_product: parameters %s" % extended_product.computed.parameters.value)
# now 'delete' the data product
log.debug("deleting data product: %s" % dp_id)
self.dpsc_cli.delete_data_product(dp_id)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.dpsc_cli.read_data_product(dp_id)
# Get the events corresponding to the data product
ret = self.unsc.get_recent_events(resource_id=dp_id)
events = ret.value
for event in events:
log.debug("event time: %s" % event.ts_created)
# self.assertTrue(len(events) > 0)
def test_data_product_stream_def(self):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=pdict_id)
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom,
spatial_domain = sdom)
dp_id = self.dpsc_cli.create_data_product(data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
stream_def_id = self.dpsc_cli.get_data_product_stream_definition(dp_id)
self.assertEquals(ctd_stream_def_id, stream_def_id)
def test_activate_suspend_data_product(self):
#------------------------------------------------------------------------------------------------
# create a stream definition for the data from the ctd simulator
#------------------------------------------------------------------------------------------------
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
ctd_stream_def_id = self.pubsubcli.create_stream_definition(name='Simulated CTD data', parameter_dictionary_id=pdict_id)
log.debug("Created stream def id %s" % ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test creating a new data product w/o a stream definition
#------------------------------------------------------------------------------------------------
# Construct temporal and spatial Coordinate Reference System objects
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
dp_obj = IonObject(RT.DataProduct,
name='DP1',
description='some new dp',
temporal_domain = tdom,
spatial_domain = sdom)
log.debug("Created an IonObject for a data product: %s" % dp_obj)
#------------------------------------------------------------------------------------------------
# Create a set of ParameterContext objects to define the parameters in the coverage, add each to the ParameterDictionary
#------------------------------------------------------------------------------------------------
dp_id = self.dpsc_cli.create_data_product(data_product= dp_obj,
stream_definition_id=ctd_stream_def_id)
#------------------------------------------------------------------------------------------------
# test activate and suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.activate_data_product_persistence(dp_id)
dp_obj = self.dpsc_cli.read_data_product(dp_id)
self.assertIsNotNone(dp_obj)
dataset_ids, _ = self.rrclient.find_objects(subject=dp_id, predicate=PRED.hasDataset, id_only=True)
if not dataset_ids:
raise NotFound("Data Product %s dataset does not exist" % str(dp_id))
self.get_datastore(dataset_ids[0])
# Check that the streams associated with the data product are persisted with
stream_ids, _ = self.rrclient.find_objects(dp_id,PRED.hasStream,RT.Stream,True)
for stream_id in stream_ids:
self.assertTrue(self.ingestclient.is_persisted(stream_id))
#--------------------------------------------------------------------------------
# Now get the data in one chunk using an RPC Call to start_retreive
#--------------------------------------------------------------------------------
replay_data = self.data_retriever.retrieve(dataset_ids[0])
self.assertIsInstance(replay_data, Granule)
log.debug("The data retriever was able to replay the dataset that was attached to the data product "
"we wanted to be persisted. Therefore the data product was indeed persisted with "
"otherwise we could not have retrieved its dataset using the data retriever. Therefore "
"this demonstration shows that L4-CI-SA-RQ-267 is satisfied: 'Data product management shall persist data products'")
data_product_object = self.rrclient.read(dp_id)
self.assertEquals(data_product_object.name,'DP1')
self.assertEquals(data_product_object.description,'some new dp')
log.debug("Towards L4-CI-SA-RQ-308: 'Data product management shall persist data product metadata'. "
" Attributes in create for the data product obj, name= '%s', description='%s', match those of object from the "
"resource registry, name='%s', desc='%s'" % (dp_obj.name, dp_obj.description,data_product_object.name,
data_product_object.description))
#------------------------------------------------------------------------------------------------
# test suspend data product persistence
#------------------------------------------------------------------------------------------------
self.dpsc_cli.suspend_data_product_persistence(dp_id)
self.dpsc_cli.force_delete_data_product(dp_id)
# now try to get the deleted dp object
with self.assertRaises(NotFound):
dp_obj = self.rrclient.read(dp_id)
