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.ctd_stream_def = SBE37_CDM_stream_definition()
def helper_create_highcharts_workflow_def(container):
from interface.services.coi.iresource_registry_service import ResourceRegistryServiceClient
rrclient = ResourceRegistryServiceClient(node=container.node)
# Check to see if the workflow defnition already exist
workflow_def_ids,_ = rrclient.find_resources(restype=RT.WorkflowDefinition, name='Realtime_HighCharts', id_only=True)
if len(workflow_def_ids) > 0:
workflow_def_id = workflow_def_ids[0]
else:
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='Realtime_HighCharts',description='Convert stream data to HighCharts data')
#Add a transformation process definition
procdef_id = helper_create_highcharts_data_process_definition(container)
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=procdef_id)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
from interface.services.ans.iworkflow_management_service import WorkflowManagementServiceClient
workflowclient = WorkflowManagementServiceClient(node=container.node)
workflow_def_id = workflowclient.create_workflow_definition(workflow_def_obj)
return workflow_def_id
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 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.ctd_stream_def = SBE37_CDM_stream_definition()
class TestVisualizationServiceIntegration(VisualizationIntegrationTestHelper):
def setUp(self):
# Start container
logging.disable(logging.ERROR)
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
logging.disable(logging.NOTSET)
# 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)
self.ctd_stream_def = SBE37_CDM_stream_definition()
def validate_messages(self, msgs):
cc = self.container
assertions = self.assertTrue
rdt = RecordDictionaryTool.load_from_granule(msgs.body)
vardict = {}
vardict['temp'] = get_safe(rdt, 'temp')
vardict['time'] = get_safe(rdt, 'time')
print vardict['time']
print vardict['temp']
@attr('LOCOINT')
#@patch.dict('pyon.ion.exchange.CFG', {'container':{'exchange':{'auto_register': False}}})
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
@unittest.skip("in progress")
def test_visualization_queue(self):
assertions = self.assertTrue
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
user_queue_name = 'user_queue'
xq = self.container.ex_manager.create_xn_queue(user_queue_name)
salinity_subscription_id = self.pubsubclient.create_subscription(
query=StreamQuery(data_product_stream_ids),
exchange_name = user_queue_name,
exchange_point = 'science_data',
name = "user visualization queue"
)
subscriber_registrar = StreamSubscriberRegistrar(container=self.container)
#subscriber = subscriber_registrar.create_subscriber(exchange_name=user_queue_name)
#subscriber.start()
#Using endpoint Subscriber directly; but should be a Stream-based subscriber that does nto require a process
#subscriber = Subscriber(from_name=(subscriber_registrar.XP, user_queue_name), callback=cb)
subscriber = Subscriber(from_name=xq)
subscriber.initialize()
# after the queue has been created it is safe to activate the subscription
self.pubsubclient.activate_subscription(subscription_id=salinity_subscription_id)
#Start the output stream listener to monitor and collect messages
#results = self.start_output_stream_and_listen(None, data_product_stream_ids)
#Not sure why this is needed - but it is
#subscriber._chan.stop_consume()
ctd_sim_pid = self.start_simple_input_stream_process(ctd_stream_id)
gevent.sleep(10.0) # Send some messages - don't care how many
msg_count,_ = xq.get_stats()
log.info('Messages in user queue 1: %s ' % msg_count)
#Validate the data from each of the messages along the way
#self.validate_messages(results)
# for x in range(msg_count):
# mo = subscriber.get_one_msg(timeout=1)
# print mo.body
# mo.ack()
msgs = subscriber.get_all_msgs(timeout=2)
for x in range(len(msgs)):
msgs[x].ack()
self.validate_messages(msgs[x])
# print msgs[x].body
#Should be zero after pulling all of the messages.
msg_count,_ = xq.get_stats()
log.info('Messages in user queue 2: %s ' % msg_count)
#Trying to continue to receive messages in the queue
gevent.sleep(5.0) # Send some messages - don't care how many
#Turning off after everything - since it is more representative of an always on stream of data!
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
#Should see more messages in the queue
msg_count,_ = xq.get_stats()
log.info('Messages in user queue 3: %s ' % msg_count)
msgs = subscriber.get_all_msgs(timeout=2)
for x in range(len(msgs)):
msgs[x].ack()
self.validate_messages(msgs[x])
#Should be zero after pulling all of the messages.
msg_count,_ = xq.get_stats()
log.info('Messages in user queue 4: %s ' % msg_count)
subscriber.close()
#@unittest.skip("in progress")
def test_realtime_visualization(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='GoogleDT_Test_Workflow',description='Tests the workflow of converting stream data to Google DT')
#Add a transformation process definition
google_dt_procdef_id = self.create_google_dt_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=google_dt_procdef_id, persist_process_output_data=True)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id, timeout=20)
ctd_sim_pid = self.start_sinusoidal_input_stream_process(ctd_stream_id)
#TODO - Need to add workflow creation for google data table
vis_params ={}
vis_params['in_product_type'] = 'google_dt'
vis_token = self.vis_client.initiate_realtime_visualization(data_product_id=workflow_product_id, visualization_parameters=vis_params)
#Trying to continue to receive messages in the queue
gevent.sleep(10.0) # Send some messages - don't care how many
#TODO - find out what the actual return data type should be
vis_data = self.vis_client.get_realtime_visualization_data(vis_token)
print vis_data
#Trying to continue to receive messages in the queue
gevent.sleep(5.0) # Send some messages - don't care how many
#Turning off after everything - since it is more representative of an always on stream of data!
#todo remove the try except
try:
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
except:
log.warning("cancelling process did not work")
vis_data = self.vis_client.get_realtime_visualization_data(vis_token)
print vis_data
self.vis_client.terminate_realtime_visualization_data(vis_token)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id, False) # Should test true at some point
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
def test_google_dt_overview_visualization(self):
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
ctd_sim_pid = self.start_sinusoidal_input_stream_process(ctd_stream_id)
# Generate some data for a few seconds
gevent.sleep(5.0)
#Turning off after everything - since it is more representative of an always on stream of data!
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
# Use the data product to test the data retrieval and google dt generation capability of the vis service
vis_data = self.vis_client.get_visualization_data(ctd_parsed_data_product_id)
# validate the returned data
self.validate_vis_service_google_dt_results(vis_data)
def test_mpl_graphs_overview_visualization(self):
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
ctd_sim_pid = self.start_sinusoidal_input_stream_process(ctd_stream_id)
# Generate some data for a few seconds
gevent.sleep(5.0)
#Turning off after everything - since it is more representative of an always on stream of data!
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
# Use the data product to test the data retrieval and google dt generation capability of the vis service
vis_data = self.vis_client.get_visualization_image(ctd_parsed_data_product_id)
# validate the returned data
self.validate_vis_service_mpl_graphs_results(vis_data)
return
class TestWorkflowManagementIntegration(VisualizationIntegrationTestHelper):
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()
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_SA_transform_components(self):
assertions = self.assertTrue
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
###
### Setup the first transformation
###
# Salinity: Data Process Definition
ctd_L2_salinity_dprocdef_id = self.create_salinity_data_process_definition()
l2_salinity_all_data_process_id, ctd_l2_salinity_output_dp_id = self.create_transform_process(ctd_L2_salinity_dprocdef_id,ctd_parsed_data_product_id )
## get the stream id for the transform outputs
stream_ids, _ = self.rrclient.find_objects(ctd_l2_salinity_output_dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) > 0 )
sal_stream_id = stream_ids[0]
data_product_stream_ids.append(sal_stream_id)
###
### Setup the second transformation
###
# Salinity Doubler: Data Process Definition
salinity_doubler_dprocdef_id = self.create_salinity_doubler_data_process_definition()
salinity_double_data_process_id, salinity_doubler_output_dp_id = self.create_transform_process(salinity_doubler_dprocdef_id, ctd_l2_salinity_output_dp_id )
stream_ids, _ = self.rrclient.find_objects(salinity_doubler_output_dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) > 0 )
sal_dbl_stream_id = stream_ids[0]
data_product_stream_ids.append(sal_dbl_stream_id)
#Start the output stream listener to monitor and collect messages
results = self.start_output_stream_and_listen(ctd_stream_id, data_product_stream_ids)
#Stop the transform processes
self.dataprocessclient.deactivate_data_process(salinity_double_data_process_id)
self.dataprocessclient.deactivate_data_process(l2_salinity_all_data_process_id)
#Validate the data from each of the messages along the way
self.validate_messages(results)
@attr('LOCOINT')
@attr('SMOKE')
@unittest.skip("not working")
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='Salinity_Test_Workflow',description='tests a workflow of multiple transform data processes')
workflow_data_product_name = 'TEST-Workflow_Output_Product' #Set a specific output product name
#Add a transformation process definition
ctd_L2_salinity_dprocdef_id = self.create_salinity_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=ctd_L2_salinity_dprocdef_id, persist_process_output_data=False) #Don't persist the intermediate data product
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Add a transformation process definition
salinity_doubler_dprocdef_id = self.create_salinity_doubler_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=salinity_doubler_dprocdef_id, output_data_product_name=workflow_data_product_name)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
aids = self.rrclient.find_associations(workflow_def_id, PRED.hasDataProcessDefinition)
assertions(len(aids) == 2 )
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id, timeout=30)
workflow_output_ids,_ = self.rrclient.find_subjects(RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1 )
#persist the output product
#self.dataproductclient.activate_data_product_persistence(workflow_product_id)
dataset_ids,_ = self.rrclient.find_objects(workflow_product_id, PRED.hasDataset, RT.DataSet, True)
assertions(len(dataset_ids) == 1 )
dataset_id = dataset_ids[0]
#Verify the output data product name matches what was specified in the workflow definition
workflow_product = self.rrclient.read(workflow_product_id)
assertions(workflow_product.name == workflow_data_product_name)
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids,_ = self.rrclient.find_objects(workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 2 )
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) == 1 )
data_product_stream_ids.append(stream_ids[0])
#Start the output stream listener to monitor and collect messages
results = self.start_output_stream_and_listen(ctd_stream_id, data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id, False, timeout=15) # Should test true at some point
#Make sure the Workflow object was removed
objs, _ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(objs) == 0)
#Validate the data from each of the messages along the way
self.validate_messages(results)
#validate that the data was persisted and can be retrieved
self.validate_data_ingest_retrieve(dataset_id)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids,_ = self.rrclient.find_resources(restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0 )
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_google_dt_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='GoogleDT_Test_Workflow',description='Tests the workflow of converting stream data to Google DT')
#Add a transformation process definition
google_dt_procdef_id = self.create_google_dt_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=google_dt_procdef_id, persist_process_output_data=True)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id, timeout=20)
workflow_output_ids,_ = self.rrclient.find_subjects(RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1 )
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids,_ = self.rrclient.find_objects(workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 1 )
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) == 1 )
data_product_stream_ids.append(stream_ids[0])
#Start the output stream listener to monitor and collect messages
results = self.start_output_stream_and_listen(ctd_stream_id, data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id, False) # Should test true at some point
#Validate the data from each of the messages along the way
self.validate_google_dt_transform_results(results)
# Check to see if ingestion worked. Extract the granules from data_retrieval.
# First find the dataset associated with the output dp product
ds_ids,_ = self.rrclient.find_objects(workflow_dp_ids[len(workflow_dp_ids) - 1], PRED.hasDataset, RT.DataSet, True)
retrieve_granule = self.data_retriever.retrieve(ds_ids[0])
#Validate the data from each of the messages along the way
self.validate_google_dt_transform_results(retrieve_granule)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids,_ = self.rrclient.find_resources(restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0 )
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_mpl_graphs_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='Mpl_Graphs_Test_Workflow',description='Tests the workflow of converting stream data to Matplotlib graphs')
#Add a transformation process definition
mpl_graphs_procdef_id = self.create_mpl_graphs_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=mpl_graphs_procdef_id, persist_process_output_data=True)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id, timeout=20)
workflow_output_ids,_ = self.rrclient.find_subjects(RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1 )
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids,_ = self.rrclient.find_objects(workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 1 )
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) == 1 )
data_product_stream_ids.append(stream_ids[0])
#Start the output stream listener to monitor and collect messages
results = self.start_output_stream_and_listen(ctd_stream_id, data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id, False) # Should test true at some point
#Validate the data from each of the messages along the way
self.validate_mpl_graphs_transform_results(results)
# Check to see if ingestion worked. Extract the granules from data_retrieval.
# First find the dataset associated with the output dp product
ds_ids,_ = self.rrclient.find_objects(workflow_dp_ids[len(workflow_dp_ids) - 1], PRED.hasDataset, RT.DataSet, True)
retrieve_granule = self.data_retriever.retrieve(ds_ids[0])
#Validate the data from each of the messages along the way
self.validate_mpl_graphs_transform_results(retrieve_granule)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids,_ = self.rrclient.find_resources(restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0 )
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_multiple_workflow_instances(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='Multiple_Test_Workflow',description='Tests the workflow of converting stream data')
#Add a transformation process definition
google_dt_procdef_id = self.create_google_dt_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=google_dt_procdef_id)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the first input data product
ctd_stream_id1, ctd_parsed_data_product_id1 = self.create_ctd_input_stream_and_data_product('ctd_parsed1')
data_product_stream_ids.append(ctd_stream_id1)
#Create and start the first workflow
workflow_id1, workflow_product_id1 = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id1, timeout=20)
#Create the second input data product
ctd_stream_id2, ctd_parsed_data_product_id2 = self.create_ctd_input_stream_and_data_product('ctd_parsed2')
data_product_stream_ids.append(ctd_stream_id2)
#Create and start the first workflow
workflow_id2, workflow_product_id2 = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id2, timeout=20)
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_ids,_ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(workflow_ids) == 2 )
#Start the first input stream process
ctd_sim_pid1 = self.start_sinusoidal_input_stream_process(ctd_stream_id1)
#Start the second input stream process
ctd_sim_pid2 = self.start_simple_input_stream_process(ctd_stream_id2)
#Start the output stream listener to monitor a set number of messages being sent through the workflows
results = self.start_output_stream_and_listen(None, data_product_stream_ids, message_count_per_stream=5)
# stop the flow of messages...
self.process_dispatcher.cancel_process(ctd_sim_pid1) # kill the ctd simulator process - that is enough data
self.process_dispatcher.cancel_process(ctd_sim_pid2)
#Stop the first workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id1, False) # Should test true at some point
#Stop the second workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id2, False) # Should test true at some point
workflow_ids,_ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(workflow_ids) == 0 )
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids,_ = self.rrclient.find_resources(restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0 )
aid_list = self.rrclient.find_associations(workflow_def_id, PRED.hasDataProcessDefinition)
assertions(len(aid_list) == 0 )
class TestWorkflowManagementIntegration(IonIntegrationTestCase):
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.ctd_stream_def = SBE37_CDM_stream_definition()
def _create_ctd_input_stream_and_data_product(
self, data_product_name='ctd_parsed'):
cc = self.container
assertions = self.assertTrue
#-------------------------------
# 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=self.ctd_stream_def, name='Simulated CTD data')
log.debug('Creating new CDM data product with a stream definition')
dp_obj = IonObject(RT.DataProduct,
name=data_product_name,
description='ctd stream test')
try:
ctd_parsed_data_product_id = self.dataproductclient.create_data_product(
dp_obj, ctd_stream_def_id)
except Exception as ex:
self.fail("failed to create new data product: %s" % ex)
log.debug('new ctd_parsed_data_product_id = ',
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,
persist_data=False,
persist_metadata=False)
# 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 _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_listener(self,
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',
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,
node=cc.node)
result = gevent.event.AsyncResult()
results = []
def message_received(message, headers):
# Heads
log.warn(' data received!')
results.append(message)
if len(results) >= len(
data_product_stream_ids
) * message_count_per_stream: #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)
# Assert that we have received data
assertions(result.get(timeout=30))
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:
try:
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 = psd.get_values('salinity')
log.info('salinity=' + str(numpy.nanmin(salinity)))
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 _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,
persist_data=True,
persist_metadata=True)
#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
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_SA_transform_components(self):
assertions = self.assertTrue
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self._create_ctd_input_stream_and_data_product(
)
data_product_stream_ids.append(ctd_stream_id)
###
### Setup the first transformation
###
# Salinity: Data Process Definition
ctd_L2_salinity_dprocdef_id = self._create_salinity_data_process_definition(
)
l2_salinity_all_data_process_id, ctd_l2_salinity_output_dp_id = self.create_transform_process(
ctd_L2_salinity_dprocdef_id, ctd_parsed_data_product_id)
## get the stream id for the transform outputs
stream_ids, _ = self.rrclient.find_objects(
ctd_l2_salinity_output_dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) > 0)
sal_stream_id = stream_ids[0]
data_product_stream_ids.append(sal_stream_id)
###
### Setup the second transformation
###
# Salinity Doubler: Data Process Definition
salinity_doubler_dprocdef_id = self._create_salinity_doubler_data_process_definition(
)
salinity_double_data_process_id, salinity_doubler_output_dp_id = self.create_transform_process(
salinity_doubler_dprocdef_id, ctd_l2_salinity_output_dp_id)
stream_ids, _ = self.rrclient.find_objects(
salinity_doubler_output_dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) > 0)
sal_dbl_stream_id = stream_ids[0]
data_product_stream_ids.append(sal_dbl_stream_id)
#Start the input stream process
ctd_sim_pid = self._start_simple_input_stream_process(ctd_stream_id)
#Start te output stream listener to monitor and verify messages
results = self._start_output_stream_listener(data_product_stream_ids)
#Stop the transform processes
self.dataprocessclient.deactivate_data_process(
salinity_double_data_process_id)
self.dataprocessclient.deactivate_data_process(
l2_salinity_all_data_process_id)
# stop the flow parse the messages...
self.process_dispatcher.cancel_process(
ctd_sim_pid
) # kill the ctd simulator process - that is enough data
#Validate the data from each of the messages along the way
self._validate_messages(results)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(
RT.WorkflowDefinition,
name='Salinity_Test_Workflow',
description='tests a workflow of multiple transform data processes'
)
workflow_data_product_name = 'TEST-Workflow_Output_Product' #Set a specific output product name
#Add a transformation process definition
ctd_L2_salinity_dprocdef_id = self._create_salinity_data_process_definition(
)
workflow_step_obj = IonObject(
'DataProcessWorkflowStep',
data_process_definition_id=ctd_L2_salinity_dprocdef_id,
persist_process_output_data=False
) #Don't persist the intermediate data product
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Add a transformation process definition
salinity_doubler_dprocdef_id = self._create_salinity_doubler_data_process_definition(
)
workflow_step_obj = IonObject(
'DataProcessWorkflowStep',
data_process_definition_id=salinity_doubler_dprocdef_id,
output_data_product_name=workflow_data_product_name)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(
workflow_def_obj)
aids = self.rrclient.find_associations(workflow_def_id,
PRED.hasDataProcessDefinition)
assertions(len(aids) == 2)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self._create_ctd_input_stream_and_data_product(
)
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(
workflow_def_id, ctd_parsed_data_product_id, timeout=30)
workflow_output_ids, _ = self.rrclient.find_subjects(
RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1)
#Verify the output data product name matches what was specified in the workflow definition
workflow_product = self.rrclient.read(workflow_product_id)
assertions(workflow_product.name == workflow_data_product_name)
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids, _ = self.rrclient.find_objects(
workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 2)
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream,
None, True)
assertions(len(stream_ids) == 1)
data_product_stream_ids.append(stream_ids[0])
#Start the input stream process
ctd_sim_pid = self._start_simple_input_stream_process(ctd_stream_id)
#Start the output stream listener to monitor and verify messages
results = self._start_output_stream_listener(data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(
workflow_id, False, timeout=15) # Should test true at some point
#Make sure the Workflow object was removed
objs, _ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(objs) == 0)
# stop the flow parse the messages...
self.process_dispatcher.cancel_process(
ctd_sim_pid
) # kill the ctd simulator process - that is enough data
#Validate the data from each of the messages along the way
self._validate_messages(results)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids, _ = self.rrclient.find_resources(
restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0)
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_results(self, results_stream_def, results):
cc = self.container
assertions = self.assertTrue
for g in results:
if isinstance(g, Granule):
tx = TaxyTool.load_from_granule(g)
rdt = RecordDictionaryTool.load_from_granule(g)
#log.warn(tx.pretty_print())
#log.warn(rdt.pretty_print())
gdt_component = rdt['google_dt_components'][0]
assertions(
gdt_component['viz_product_type'] == 'google_realtime_dt')
gdt_description = gdt_component['data_table_description']
gdt_content = gdt_component['data_table_content']
assertions(gdt_description[0][0] == 'time')
assertions(len(gdt_description) > 1)
assertions(len(gdt_content) >= 0)
return
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_results(self, results_stream_def, results):
cc = self.container
assertions = self.assertTrue
for g in results:
if isinstance(g, Granule):
tx = TaxyTool.load_from_granule(g)
rdt = RecordDictionaryTool.load_from_granule(g)
#log.warn(tx.pretty_print())
#log.warn(rdt.pretty_print())
graphs = rdt['matplotlib_graphs']
for graph in graphs:
assertions(
graph['viz_product_type'] == 'matplotlib_graphs')
# check to see if the list (numpy array) contians actual images
assertions(
imghdr.what(graph['image_name'], graph['image_obj']) ==
'png')
return
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Not integrated for CEI')
#unittest.skip("Skipping for debugging ")
def test_google_dt_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(
RT.WorkflowDefinition,
name='GoogleDT_Test_Workflow',
description=
'Tests the workflow of converting stream data to Google DT')
#Add a transformation process definition
google_dt_procdef_id = self._create_google_dt_data_process_definition()
workflow_step_obj = IonObject(
'DataProcessWorkflowStep',
data_process_definition_id=google_dt_procdef_id)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(
workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self._create_ctd_input_stream_and_data_product(
)
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(
workflow_def_id, ctd_parsed_data_product_id)
workflow_output_ids, _ = self.rrclient.find_subjects(
RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1)
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids, _ = self.rrclient.find_objects(
workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 1)
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream,
None, True)
assertions(len(stream_ids) == 1)
data_product_stream_ids.append(stream_ids[0])
#Start the input stream process
ctd_sim_pid = self._start_simple_input_stream_process(ctd_stream_id)
#Start the output stream listener to monitor and verify messages
results = self._start_output_stream_listener(data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(
workflow_id, False) # Should test true at some point
# stop the flow parse the messages...
self.process_dispatcher.cancel_process(
ctd_sim_pid
) # kill the ctd simulator process - that is enough data
#Validate the data from each of the messages along the way
self._validate_google_dt_results(
VizTransformGoogleDT.outgoing_stream_def, results)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids, _ = self.rrclient.find_resources(
restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_mpl_graphs_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(
RT.WorkflowDefinition,
name='Mpl_Graphs_Test_Workflow',
description=
'Tests the workflow of converting stream data to Matplotlib graphs'
)
#Add a transformation process definition
mpl_graphs_procdef_id = self._create_mpl_graphs_data_process_definition(
)
workflow_step_obj = IonObject(
'DataProcessWorkflowStep',
data_process_definition_id=mpl_graphs_procdef_id)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(
workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self._create_ctd_input_stream_and_data_product(
)
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(
workflow_def_id, ctd_parsed_data_product_id)
workflow_output_ids, _ = self.rrclient.find_subjects(
RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1)
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids, _ = self.rrclient.find_objects(
workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 1)
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream,
None, True)
assertions(len(stream_ids) == 1)
data_product_stream_ids.append(stream_ids[0])
#Start the input stream process
ctd_sim_pid = self._start_sinusoidal_input_stream_process(
ctd_stream_id)
#Start the output stream listener to monitor and verify messages
results = self._start_output_stream_listener(data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(
workflow_id, False) # Should test true at some point
# stop the flow parse the messages...
self.process_dispatcher.cancel_process(
ctd_sim_pid
) # kill the ctd simulator process - that is enough data
#Validate the data from each of the messages along the way
self._validate_mpl_graphs_results(
VizTransformGoogleDT.outgoing_stream_def, results)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids, _ = self.rrclient.find_resources(
restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_multiple_workflow_instances(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(
RT.WorkflowDefinition,
name='Multiple_Test_Workflow',
description='Tests the workflow of converting stream data')
#Add a transformation process definition
google_dt_procdef_id = self._create_google_dt_data_process_definition()
workflow_step_obj = IonObject(
'DataProcessWorkflowStep',
data_process_definition_id=google_dt_procdef_id)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(
workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the first input data product
ctd_stream_id1, ctd_parsed_data_product_id1 = self._create_ctd_input_stream_and_data_product(
'ctd_parsed1')
data_product_stream_ids.append(ctd_stream_id1)
#Create and start the first workflow
workflow_id1, workflow_product_id1 = self.workflowclient.create_data_process_workflow(
workflow_def_id, ctd_parsed_data_product_id1)
#Create the second input data product
ctd_stream_id2, ctd_parsed_data_product_id2 = self._create_ctd_input_stream_and_data_product(
'ctd_parsed2')
data_product_stream_ids.append(ctd_stream_id2)
#Create and start the first workflow
workflow_id2, workflow_product_id2 = self.workflowclient.create_data_process_workflow(
workflow_def_id, ctd_parsed_data_product_id2)
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_ids, _ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(workflow_ids) == 2)
#Start the first input stream process
ctd_sim_pid1 = self._start_sinusoidal_input_stream_process(
ctd_stream_id1)
#Start the second input stream process
ctd_sim_pid2 = self._start_simple_input_stream_process(ctd_stream_id2)
#Start the output stream listener to monitor a set number of messages being sent through the workflows
results = self._start_output_stream_listener(
data_product_stream_ids, message_count_per_stream=5)
# stop the flow of messages...
self.process_dispatcher.cancel_process(
ctd_sim_pid1
) # kill the ctd simulator process - that is enough data
self.process_dispatcher.cancel_process(ctd_sim_pid2)
#Stop the first workflow processes
self.workflowclient.terminate_data_process_workflow(
workflow_id1, False) # Should test true at some point
#Stop the second workflow processes
self.workflowclient.terminate_data_process_workflow(
workflow_id2, False) # Should test true at some point
workflow_ids, _ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(workflow_ids) == 0)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids, _ = self.rrclient.find_resources(
restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0)
aid_list = self.rrclient.find_associations(
workflow_def_id, PRED.hasDataProcessDefinition)
assertions(len(aid_list) == 0)
class TestWorkflowManagementIntegration(IonIntegrationTestCase):
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.ctd_stream_def = SBE37_CDM_stream_definition()
def _create_ctd_input_stream_and_data_product(self, data_product_name='ctd_parsed'):
cc = self.container
assertions = self.assertTrue
#-------------------------------
# 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=self.ctd_stream_def, name='Simulated CTD data')
log.debug('Creating new CDM data product with a stream definition')
dp_obj = IonObject(RT.DataProduct,name=data_product_name,description='ctd stream test')
try:
ctd_parsed_data_product_id = self.dataproductclient.create_data_product(dp_obj, ctd_stream_def_id)
except Exception as ex:
self.fail("failed to create new data product: %s" %ex)
log.debug('new ctd_parsed_data_product_id = ', 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, persist_data=False, persist_metadata=False)
# 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 _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_listener(self, 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',
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, node=cc.node)
result = gevent.event.AsyncResult()
results = []
def message_received(message, headers):
# Heads
log.warn(' data received!')
results.append(message)
if len(results) >= len(data_product_stream_ids) * message_count_per_stream: #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)
# Assert that we have received data
assertions(result.get(timeout=30))
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:
try:
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 = psd.get_values('salinity')
log.info( 'salinity=' + str(numpy.nanmin(salinity)))
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 _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, persist_data=True, persist_metadata=True)
#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
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_SA_transform_components(self):
assertions = self.assertTrue
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self._create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
###
### Setup the first transformation
###
# Salinity: Data Process Definition
ctd_L2_salinity_dprocdef_id = self._create_salinity_data_process_definition()
l2_salinity_all_data_process_id, ctd_l2_salinity_output_dp_id = self.create_transform_process(ctd_L2_salinity_dprocdef_id,ctd_parsed_data_product_id )
## get the stream id for the transform outputs
stream_ids, _ = self.rrclient.find_objects(ctd_l2_salinity_output_dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) > 0 )
sal_stream_id = stream_ids[0]
data_product_stream_ids.append(sal_stream_id)
###
### Setup the second transformation
###
# Salinity Doubler: Data Process Definition
salinity_doubler_dprocdef_id = self._create_salinity_doubler_data_process_definition()
salinity_double_data_process_id, salinity_doubler_output_dp_id = self.create_transform_process(salinity_doubler_dprocdef_id, ctd_l2_salinity_output_dp_id )
stream_ids, _ = self.rrclient.find_objects(salinity_doubler_output_dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) > 0 )
sal_dbl_stream_id = stream_ids[0]
data_product_stream_ids.append(sal_dbl_stream_id)
#Start the input stream process
ctd_sim_pid = self._start_simple_input_stream_process(ctd_stream_id)
#Start te output stream listener to monitor and verify messages
results = self._start_output_stream_listener(data_product_stream_ids)
#Stop the transform processes
self.dataprocessclient.deactivate_data_process(salinity_double_data_process_id)
self.dataprocessclient.deactivate_data_process(l2_salinity_all_data_process_id)
# stop the flow parse the messages...
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
#Validate the data from each of the messages along the way
self._validate_messages(results)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='Salinity_Test_Workflow',description='tests a workflow of multiple transform data processes')
workflow_data_product_name = 'TEST-Workflow_Output_Product' #Set a specific output product name
#Add a transformation process definition
ctd_L2_salinity_dprocdef_id = self._create_salinity_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=ctd_L2_salinity_dprocdef_id, persist_process_output_data=False) #Don't persist the intermediate data product
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Add a transformation process definition
salinity_doubler_dprocdef_id = self._create_salinity_doubler_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=salinity_doubler_dprocdef_id, output_data_product_name=workflow_data_product_name)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
aids = self.rrclient.find_associations(workflow_def_id, PRED.hasDataProcessDefinition)
assertions(len(aids) == 2 )
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self._create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id, timeout=30)
workflow_output_ids,_ = self.rrclient.find_subjects(RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1 )
#Verify the output data product name matches what was specified in the workflow definition
workflow_product = self.rrclient.read(workflow_product_id)
assertions(workflow_product.name == workflow_data_product_name)
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids,_ = self.rrclient.find_objects(workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 2 )
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) == 1 )
data_product_stream_ids.append(stream_ids[0])
#Start the input stream process
ctd_sim_pid = self._start_simple_input_stream_process(ctd_stream_id)
#Start the output stream listener to monitor and verify messages
results = self._start_output_stream_listener(data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id, False, timeout=15) # Should test true at some point
#Make sure the Workflow object was removed
objs, _ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(objs) == 0)
# stop the flow parse the messages...
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
#Validate the data from each of the messages along the way
self._validate_messages(results)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids,_ = self.rrclient.find_resources(restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0 )
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_results(self, results_stream_def, results):
cc = self.container
assertions = self.assertTrue
for g in results:
if isinstance(g,Granule):
tx = TaxyTool.load_from_granule(g)
rdt = RecordDictionaryTool.load_from_granule(g)
#log.warn(tx.pretty_print())
#log.warn(rdt.pretty_print())
gdt_component = rdt['google_dt_components'][0]
assertions(gdt_component['viz_product_type'] == 'google_realtime_dt' )
gdt_description = gdt_component['data_table_description']
gdt_content = gdt_component['data_table_content']
assertions(gdt_description[0][0] == 'time')
assertions(len(gdt_description) > 1)
assertions(len(gdt_content) >= 0)
return
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_results(self, results_stream_def, results):
cc = self.container
assertions = self.assertTrue
for g in results:
if isinstance(g,Granule):
tx = TaxyTool.load_from_granule(g)
rdt = RecordDictionaryTool.load_from_granule(g)
#log.warn(tx.pretty_print())
#log.warn(rdt.pretty_print())
graphs = rdt['matplotlib_graphs']
for graph in graphs:
assertions(graph['viz_product_type'] == 'matplotlib_graphs' )
# check to see if the list (numpy array) contians actual images
assertions(imghdr.what(graph['image_name'], graph['image_obj']) == 'png')
return
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#unittest.skip("Skipping for debugging ")
def test_google_dt_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='GoogleDT_Test_Workflow',description='Tests the workflow of converting stream data to Google DT')
#Add a transformation process definition
google_dt_procdef_id = self._create_google_dt_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=google_dt_procdef_id)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self._create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id)
workflow_output_ids,_ = self.rrclient.find_subjects(RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1 )
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids,_ = self.rrclient.find_objects(workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 1 )
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) == 1 )
data_product_stream_ids.append(stream_ids[0])
#Start the input stream process
ctd_sim_pid = self._start_simple_input_stream_process(ctd_stream_id)
#Start the output stream listener to monitor and verify messages
results = self._start_output_stream_listener(data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id, False) # Should test true at some point
# stop the flow parse the messages...
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
#Validate the data from each of the messages along the way
self._validate_google_dt_results(VizTransformGoogleDT.outgoing_stream_def, results)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids,_ = self.rrclient.find_resources(restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0 )
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_mpl_graphs_transform_workflow(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='Mpl_Graphs_Test_Workflow',description='Tests the workflow of converting stream data to Matplotlib graphs')
#Add a transformation process definition
mpl_graphs_procdef_id = self._create_mpl_graphs_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=mpl_graphs_procdef_id)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self._create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id)
workflow_output_ids,_ = self.rrclient.find_subjects(RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1 )
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids,_ = self.rrclient.find_objects(workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 1 )
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) == 1 )
data_product_stream_ids.append(stream_ids[0])
#Start the input stream process
ctd_sim_pid = self._start_sinusoidal_input_stream_process(ctd_stream_id)
#Start the output stream listener to monitor and verify messages
results = self._start_output_stream_listener(data_product_stream_ids)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id, False) # Should test true at some point
# stop the flow parse the messages...
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
#Validate the data from each of the messages along the way
self._validate_mpl_graphs_results(VizTransformGoogleDT.outgoing_stream_def, results)
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids,_ = self.rrclient.find_resources(restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0 )
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),'Not integrated for CEI')
#@unittest.skip("Skipping for debugging ")
def test_multiple_workflow_instances(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='Multiple_Test_Workflow',description='Tests the workflow of converting stream data')
#Add a transformation process definition
google_dt_procdef_id = self._create_google_dt_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=google_dt_procdef_id)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the first input data product
ctd_stream_id1, ctd_parsed_data_product_id1 = self._create_ctd_input_stream_and_data_product('ctd_parsed1')
data_product_stream_ids.append(ctd_stream_id1)
#Create and start the first workflow
workflow_id1, workflow_product_id1 = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id1)
#Create the second input data product
ctd_stream_id2, ctd_parsed_data_product_id2 = self._create_ctd_input_stream_and_data_product('ctd_parsed2')
data_product_stream_ids.append(ctd_stream_id2)
#Create and start the first workflow
workflow_id2, workflow_product_id2 = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id2)
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_ids,_ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(workflow_ids) == 2 )
#Start the first input stream process
ctd_sim_pid1 = self._start_sinusoidal_input_stream_process(ctd_stream_id1)
#Start the second input stream process
ctd_sim_pid2 = self._start_simple_input_stream_process(ctd_stream_id2)
#Start the output stream listener to monitor a set number of messages being sent through the workflows
results = self._start_output_stream_listener(data_product_stream_ids, message_count_per_stream=5)
# stop the flow of messages...
self.process_dispatcher.cancel_process(ctd_sim_pid1) # kill the ctd simulator process - that is enough data
self.process_dispatcher.cancel_process(ctd_sim_pid2)
#Stop the first workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id1, False) # Should test true at some point
#Stop the second workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id2, False) # Should test true at some point
workflow_ids,_ = self.rrclient.find_resources(restype=RT.Workflow)
assertions(len(workflow_ids) == 0 )
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
workflow_def_ids,_ = self.rrclient.find_resources(restype=RT.WorkflowDefinition)
assertions(len(workflow_def_ids) == 0 )
aid_list = self.rrclient.find_associations(workflow_def_id, PRED.hasDataProcessDefinition)
assertions(len(aid_list) == 0 )
