def load_data_product(self):
dset_i = 0
dataset_management = DatasetManagementServiceClient()
pubsub_management = PubsubManagementServiceClient()
data_product_management = DataProductManagementServiceClient()
resource_registry = self.container.instance.resource_registry
tdom, sdom = time_series_domain()
tdom = tdom.dump()
sdom = sdom.dump()
dp_obj = DataProduct(
name='instrument_data_product_%i' % dset_i,
description='ctd stream test',
processing_level_code='Parsed_Canonical',
temporal_domain = tdom,
spatial_domain = sdom)
pdict_id = dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
stream_def_id = pubsub_management.create_stream_definition(name='parsed', parameter_dictionary_id=pdict_id)
self.addCleanup(pubsub_management.delete_stream_definition, stream_def_id)
data_product_id = data_product_management.create_data_product(data_product=dp_obj, stream_definition_id=stream_def_id)
self.addCleanup(data_product_management.delete_data_product, data_product_id)
data_product_management.activate_data_product_persistence(data_product_id)
self.addCleanup(data_product_management.suspend_data_product_persistence, data_product_id)
stream_ids, assocs = resource_registry.find_objects(subject=data_product_id, predicate='hasStream', id_only=True)
stream_id = stream_ids[0]
route = pubsub_management.read_stream_route(stream_id)
dataset_ids, assocs = resource_registry.find_objects(subject=data_product_id, predicate='hasDataset', id_only=True)
dataset_id = dataset_ids[0]
return data_product_id, stream_id, route, stream_def_id, dataset_id
def load_data_product(self):
dset_i = 0
dataset_management = DatasetManagementServiceClient()
pubsub_management = PubsubManagementServiceClient()
data_product_management = DataProductManagementServiceClient()
resource_registry = self.container.instance.resource_registry
dp_obj = DataProduct(
name='instrument_data_product_%i' % dset_i,
description='ctd stream test',
processing_level_code='Parsed_Canonical')
pdict_id = dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
stream_def_id = pubsub_management.create_stream_definition(name='parsed', parameter_dictionary_id=pdict_id)
self.addCleanup(pubsub_management.delete_stream_definition, stream_def_id)
data_product_id = data_product_management.create_data_product(data_product=dp_obj, stream_definition_id=stream_def_id)
self.addCleanup(data_product_management.delete_data_product, data_product_id)
data_product_management.activate_data_product_persistence(data_product_id)
self.addCleanup(data_product_management.suspend_data_product_persistence, data_product_id)
stream_ids, assocs = resource_registry.find_objects(subject=data_product_id, predicate='hasStream', id_only=True)
stream_id = stream_ids[0]
route = pubsub_management.read_stream_route(stream_id)
dataset_ids, assocs = resource_registry.find_objects(subject=data_product_id, predicate='hasDataset', id_only=True)
dataset_id = dataset_ids[0]
return data_product_id, stream_id, route, stream_def_id, dataset_id
def publish_rdt_to_data_product(cls,data_product_id, rdt, connection_id='', connection_index=''):
resource_registry = Container.instance.resource_registry
pubsub_management = PubsubManagementServiceClient()
stream_ids, _ = resource_registry.find_objects(data_product_id,'hasStream',id_only=True)
stream_id = stream_ids[0]
route = pubsub_management.read_stream_route(stream_id)
publisher = StandaloneStreamPublisher(stream_id,route)
publisher.publish(rdt.to_granule(connection_id=connection_id, connection_index=connection_index))
class TestTransformPrime(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url(
'res/deploy/r2deploy.yml') # Because hey why not?!
self.dataset_management = DatasetManagementServiceClient()
self.data_process_management = DataProcessManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
def setup_streams(self):
in_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'sbe37_L0_test', id_only=True)
out_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'sbe37_L1_test', id_only=True)
in_stream_def_id = self.pubsub_management.create_stream_definition(
'L0 SBE37', parameter_dictionary_id=in_pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition,
in_stream_def_id)
out_stream_def_id = self.pubsub_management.create_stream_definition(
'L1 SBE37', parameter_dictionary_id=out_pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition,
out_stream_def_id)
in_stream_id, in_route = self.pubsub_management.create_stream(
'L0 input',
stream_definition_id=in_stream_def_id,
exchange_point='test')
self.addCleanup(self.pubsub_management.delete_stream, in_stream_id)
out_stream_id, out_route = self.pubsub_management.create_stream(
'L0 output',
stream_definition_id=out_stream_def_id,
exchange_point='test')
self.addCleanup(self.pubsub_management.delete_stream, out_stream_id)
return [(in_stream_id, in_stream_def_id),
(out_stream_id, out_stream_def_id)]
def setup_advanced_streams(self):
in_pdict_id = out_pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'sbe37_LC_TEST', id_only=True)
in_stream_def_id = self.pubsub_management.create_stream_definition(
'sbe37_instrument',
parameter_dictionary_id=in_pdict_id,
available_fields=[
'time', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0', 'lat', 'lon'
])
self.addCleanup(self.pubsub_management.delete_stream_definition,
in_stream_def_id)
out_stream_def_id = self.pubsub_management.create_stream_definition(
'sbe37_l2',
parameter_dictionary_id=out_pdict_id,
available_fields=['time', 'rho', 'PRACSAL_L2'])
self.addCleanup(self.pubsub_management.delete_stream_definition,
out_stream_def_id)
in_stream_id, in_route = self.pubsub_management.create_stream(
'instrument stream',
stream_definition_id=in_stream_def_id,
exchange_point='test')
self.addCleanup(self.pubsub_management.delete_stream, in_stream_id)
out_stream_id, out_route = self.pubsub_management.create_stream(
'data product stream',
stream_definition_id=out_stream_def_id,
exchange_point='test')
self.addCleanup(self.pubsub_management.delete_stream, out_stream_id)
return [(in_stream_id, in_stream_def_id),
(out_stream_id, out_stream_def_id)]
def preload(self):
config = DotDict()
config.op = 'load'
config.scenario = 'BASE,LC_TEST'
config.categories = 'ParameterFunctions,ParameterDefs,ParameterDictionary'
config.path = 'res/preload/r2_ioc'
self.container.spawn_process('preload',
'ion.processes.bootstrap.ion_loader',
'IONLoader', config)
def setup_advanced_transform(self):
self.preload()
queue_name = 'transform_prime'
stream_info = self.setup_advanced_streams()
in_stream_id, in_stream_def_id = stream_info[0]
out_stream_id, out_stream_def_id = stream_info[1]
routes = {}
routes[(in_stream_id, out_stream_id)] = None
config = DotDict()
config.process.queue_name = queue_name
config.process.routes = routes
config.process.publish_streams = {out_stream_id: out_stream_id}
sub_id = self.pubsub_management.create_subscription(
queue_name, stream_ids=[in_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)
self.container.spawn_process(
'transform_prime', 'ion.processes.data.transforms.transform_prime',
'TransformPrime', config)
listen_sub_id = self.pubsub_management.create_subscription(
'listener', stream_ids=[out_stream_id])
self.addCleanup(self.pubsub_management.delete_subscription,
listen_sub_id)
self.pubsub_management.activate_subscription(listen_sub_id)
self.addCleanup(self.pubsub_management.deactivate_subscription,
listen_sub_id)
return [(in_stream_id, in_stream_def_id),
(out_stream_id, out_stream_def_id)]
def setup_transform(self):
self.preload()
queue_name = 'transform_prime'
stream_info = self.setup_streams()
in_stream_id, in_stream_def_id = stream_info[0]
out_stream_id, out_stream_def_id = stream_info[1]
routes = {}
routes[(in_stream_id, out_stream_id)] = None
config = DotDict()
config.process.queue_name = queue_name
config.process.routes = routes
config.process.publish_streams = {out_stream_id: out_stream_id}
sub_id = self.pubsub_management.create_subscription(
queue_name, stream_ids=[in_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)
self.container.spawn_process(
'transform_prime', 'ion.processes.data.transforms.transform_prime',
'TransformPrime', config)
listen_sub_id = self.pubsub_management.create_subscription(
'listener', stream_ids=[out_stream_id])
self.addCleanup(self.pubsub_management.delete_subscription,
listen_sub_id)
self.pubsub_management.activate_subscription(listen_sub_id)
self.addCleanup(self.pubsub_management.deactivate_subscription,
listen_sub_id)
return [(in_stream_id, in_stream_def_id),
(out_stream_id, out_stream_def_id)]
def setup_validator(self, validator):
listener = StandaloneStreamSubscriber('listener', validator)
listener.start()
self.addCleanup(listener.stop)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_execute_advanced_transform(self):
# Runs a transform across L0-L2 with stream definitions including available fields
streams = self.setup_advanced_transform()
in_stream_id, in_stream_def_id = streams[0]
out_stream_id, out_stream_defs_id = streams[1]
validation_event = Event()
def validator(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
if not np.allclose(rdt['rho'], np.array([1001.0055034])):
return
validation_event.set()
self.setup_validator(validator)
in_route = self.pubsub_management.read_stream_route(in_stream_id)
publisher = StandaloneStreamPublisher(in_stream_id, in_route)
outbound_rdt = RecordDictionaryTool(
stream_definition_id=in_stream_def_id)
outbound_rdt['time'] = [0]
outbound_rdt['TEMPWAT_L0'] = [280000]
outbound_rdt['CONDWAT_L0'] = [100000]
outbound_rdt['PRESWAT_L0'] = [2789]
outbound_rdt['lat'] = [45]
outbound_rdt['lon'] = [-71]
outbound_granule = outbound_rdt.to_granule()
publisher.publish(outbound_granule)
self.assertTrue(validation_event.wait(2))
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_execute_transform(self):
streams = self.setup_transform()
in_stream_id, in_stream_def_id = streams[0]
out_stream_id, out_stream_def_id = streams[1]
validation_event = Event()
def validator(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
if not np.allclose(rdt['TEMPWAT_L1'], np.array([18.])):
return
if not np.allclose(rdt['CONDWAT_L1'], np.array([0.5])):
return
if not np.allclose(rdt['PRESWAT_L1'], np.array([0.04536611])):
return
validation_event.set()
self.setup_validator(validator)
in_route = self.pubsub_management.read_stream_route(in_stream_id)
publisher = StandaloneStreamPublisher(in_stream_id, in_route)
outbound_rdt = RecordDictionaryTool(
stream_definition_id=in_stream_def_id)
outbound_rdt['time'] = [0]
outbound_rdt['TEMPWAT_L0'] = [280000]
outbound_rdt['CONDWAT_L0'] = [100000]
outbound_rdt['PRESWAT_L0'] = [2789]
outbound_rdt['lat'] = [45]
outbound_rdt['lon'] = [-71]
outbound_granule = outbound_rdt.to_granule()
publisher.publish(outbound_granule)
self.assertTrue(validation_event.wait(2))
class TestTransformWorker(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
# Instantiate a process to represent the test
process=TransformWorkerTestProcess()
self.dataset_management_client = DatasetManagementServiceClient(node=self.container.node)
self.pubsub_client = PubsubManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceProcessClient(node=self.container.node, process = process)
self.time_dom, self.spatial_dom = time_series_domain()
self.ph = ParameterHelper(self.dataset_management_client, self.addCleanup)
self.wait_time = CFG.get_safe('endpoint.receive.timeout', 10)
def push_granule(self, data_product_id):
'''
Publishes and monitors that the granule arrived
'''
datasets, _ = self.rrclient.find_objects(data_product_id, PRED.hasDataset, id_only=True)
dataset_monitor = DatasetMonitor(datasets[0])
rdt = self.ph.rdt_for_data_product(data_product_id)
self.ph.fill_parsed_rdt(rdt)
self.ph.publish_rdt_to_data_product(data_product_id, rdt)
assert dataset_monitor.wait()
dataset_monitor.stop()
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_transform_worker(self):
# test that a data process (type: data-product-in / data-product-out) can be defined and launched.
# verify that the output granule fields are correctly populated
# test that the input and output data products are linked to facilitate provenance
self.dp_list = []
self.data_process_objs = []
self._output_stream_ids = []
self.granule_verified = Event()
self.worker_assigned_event_verified = Event()
self.dp_created_event_verified = Event()
self.heartbeat_event_verified = Event()
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition, self.stream_def_id)
# create the DataProduct that is the input to the data processes
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product', description='input test stream',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
self.start_event_listener()
# create the DPD, DataProcess and output DataProduct
dataprocessdef_id, dataprocess_id, dataproduct_id = self.create_data_process()
self.dp_list.append(dataprocess_id)
# validate the repository for data product algorithms persists the new resources NEW SA-1
# create_data_process call created one of each
dpd_ids, _ = self.rrclient.find_resources(restype=OT.DataProcessDefinition, id_only=False)
# there will be more than one becuase of the DPDs that reperesent the PFs in the data product above
self.assertTrue(dpd_ids is not None)
dp_ids, _ = self.rrclient.find_resources(restype=OT.DataProcess, id_only=False)
# only one DP becuase the PFs that are in the code dataproduct above are not activated yet.
self.assertEquals(len(dp_ids), 1)
# validate the name and version label NEW SA - 2
dataprocessdef_obj = self.dataprocessclient.read_data_process_definition(dataprocessdef_id)
self.assertEqual(dataprocessdef_obj.version_label, '1.0a')
self.assertEqual(dataprocessdef_obj.name, 'add_arrays')
# validate that the DPD has an attachment NEW SA - 21
attachment_ids, assoc_ids = self.rrclient.find_objects(dataprocessdef_id, PRED.hasAttachment, RT.Attachment, True)
self.assertEqual(len(attachment_ids), 1)
attachment_obj = self.rrclient.read_attachment(attachment_ids[0])
log.debug('attachment: %s', attachment_obj)
# validate that the data process resource has input and output data products associated
# L4-CI-SA-RQ-364 and NEW SA-3
outproduct_ids, assoc_ids = self.rrclient.find_objects(dataprocess_id, PRED.hasOutputProduct, RT.DataProduct, True)
self.assertEqual(len(outproduct_ids), 1)
inproduct_ids, assoc_ids = self.rrclient.find_objects(dataprocess_id, PRED.hasInputProduct, RT.DataProduct, True)
self.assertEqual(len(inproduct_ids), 1)
# Test for provenance. Get Data product produced by the data processes
output_data_product_id,_ = self.rrclient.find_objects(subject=dataprocess_id,
object_type=RT.DataProduct,
predicate=PRED.hasOutputProduct,
id_only=True)
output_data_product_provenance = self.dataproductclient.get_data_product_provenance(output_data_product_id[0])
# Do a basic check to see if there were 3 entries in the provenance graph. Parent and Child and the
# DataProcessDefinition creating the child from the parent.
self.assertTrue(len(output_data_product_provenance) == 2)
self.assertTrue(self.input_dp_id in output_data_product_provenance[output_data_product_id[0]]['parents'])
self.assertTrue(output_data_product_provenance[output_data_product_id[0]]['parents'][self.input_dp_id]['data_process_definition_id'] == dataprocessdef_id)
# NEW SA - 4 | Data processing shall include the appropriate data product algorithm name and version number in
# the metadata of each output data product created by the data product algorithm.
output_data_product_obj,_ = self.rrclient.find_objects(subject=dataprocess_id,
object_type=RT.DataProduct,
predicate=PRED.hasOutputProduct,
id_only=False)
self.assertTrue(output_data_product_obj[0].name != None)
self.assertTrue(output_data_product_obj[0]._rev != None)
# retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(subject=dataprocess_id, predicate=PRED.hasSubscription, object_type=RT.Subscription, id_only=False)
log.debug('test_transform_worker subscription_obj: %s', subscription_objs[0])
# create a queue to catch the published granules
self.subscription_id = self.pubsub_client.create_subscription(name='parsed_subscription', stream_ids=[self.stream_id], exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription, self.subscription_id)
self.pubsub_client.activate_subscription(self.subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, self.subscription_id)
stream_route = self.pubsub_client.read_stream_route(self.stream_id)
self.publisher = StandaloneStreamPublisher(stream_id=self.stream_id, stream_route=stream_route )
for n in range(1, 101):
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher.publish(rdt.to_granule())
# validate that the output granule is received and the updated value is correct
self.assertTrue(self.granule_verified.wait(self.wait_time))
# validate that the data process loaded into worker event is received (L4-CI-SA-RQ-182)
self.assertTrue(self.worker_assigned_event_verified.wait(self.wait_time))
# validate that the data process create (with data product ids) event is received (NEW SA -42)
self.assertTrue(self.dp_created_event_verified.wait(self.wait_time))
# validate that the data process heartbeat event is received (for every hundred granules processed) (L4-CI-SA-RQ-182)
#this takes a while so set wait limit to large value
self.assertTrue(self.heartbeat_event_verified.wait(200))
# validate that the code from the transform function can be retrieve via inspect_data_process_definition
src = self.dataprocessclient.inspect_data_process_definition(dataprocessdef_id)
self.assertIn( 'def add_arrays(a, b)', src)
# now delete the DPD and DP then verify that the resources are retired so that information required for provenance are still available
self.dataprocessclient.delete_data_process(dataprocess_id)
self.dataprocessclient.delete_data_process_definition(dataprocessdef_id)
in_dp_objs, _ = self.rrclient.find_objects(subject=dataprocess_id, predicate=PRED.hasInputProduct, object_type=RT.DataProduct, id_only=True)
self.assertTrue(in_dp_objs is not None)
dpd_objs, _ = self.rrclient.find_subjects(subject_type=RT.DataProcessDefinition, predicate=PRED.hasDataProcess, object=dataprocess_id, id_only=True)
self.assertTrue(dpd_objs is not None)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_transform_worker_with_instrumentdevice(self):
# test that a data process (type: data-product-in / data-product-out) can be defined and launched.
# verify that the output granule fields are correctly populated
# test that the input and output data products are linked to facilitate provenance
self.data_process_objs = []
self._output_stream_ids = []
self.event_verified = Event()
# Create CTD Parsed as the initial data product
# create a stream definition for the data from the ctd simulator
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
self.stream_def_id = self.pubsub_client.create_stream_definition(name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
# create the DataProduct that is the input to the data processes
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product', description='input test stream',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
log.debug('new ctd_parsed_data_product_id = %s' % self.input_dp_id)
# only ever need one device for testing purposes.
instDevice_obj,_ = self.rrclient.find_resources(restype=RT.InstrumentDevice, name='test_ctd_device')
if instDevice_obj:
instDevice_id = instDevice_obj[0]._id
else:
instDevice_obj = IonObject(RT.InstrumentDevice, name='test_ctd_device', description="test_ctd_device", 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=self.input_dp_id)
# create the DPD, DataProcess and output DataProduct
dataprocessdef_id, dataprocess_id, dataproduct_id = self.create_data_process()
self.addCleanup(self.dataprocessclient.delete_data_process, dataprocess_id)
self.addCleanup(self.dataprocessclient.delete_data_process_definition, dataprocessdef_id)
# Test for provenance. Get Data product produced by the data processes
output_data_product_id,_ = self.rrclient.find_objects(subject=dataprocess_id,
object_type=RT.DataProduct,
predicate=PRED.hasOutputProduct,
id_only=True)
output_data_product_provenance = self.dataproductclient.get_data_product_provenance(output_data_product_id[0])
# Do a basic check to see if there were 3 entries in the provenance graph. Parent and Child and the
# DataProcessDefinition creating the child from the parent.
self.assertTrue(len(output_data_product_provenance) == 3)
self.assertTrue(self.input_dp_id in output_data_product_provenance[output_data_product_id[0]]['parents'])
self.assertTrue(instDevice_id in output_data_product_provenance[self.input_dp_id]['parents'])
self.assertTrue(output_data_product_provenance[instDevice_id]['type'] == 'InstrumentDevice')
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_transform_worker_with_platformdevice(self):
# test that a data process (type: data-product-in / data-product-out) can be defined and launched.
# verify that the output granule fields are correctly populated
# test that the input and output data products are linked to facilitate provenance
self.data_process_objs = []
self._output_stream_ids = []
self.event_verified = Event()
# Create CTD Parsed as the initial data product
# create a stream definition for the data from the ctd simulator
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name('ctd_parsed_param_dict', id_only=True)
self.stream_def_id = self.pubsub_client.create_stream_definition(name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
# create the DataProduct that is the input to the data processes
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product', description='input test stream',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
log.debug('new ctd_parsed_data_product_id = %s' % self.input_dp_id)
# only ever need one device for testing purposes.
platform_device_obj,_ = self.rrclient.find_resources(restype=RT.PlatformDevice, name='TestPlatform')
if platform_device_obj:
platform_device_id = platform_device_obj[0]._id
else:
platform_device_obj = IonObject(RT.PlatformDevice, name='TestPlatform', description="TestPlatform", serial_number="12345" )
platform_device_id = self.imsclient.create_platform_device(platform_device=platform_device_obj)
self.damsclient.assign_data_product(input_resource_id=platform_device_id, data_product_id=self.input_dp_id)
# create the DPD, DataProcess and output DataProduct
dataprocessdef_id, dataprocess_id, dataproduct_id = self.create_data_process()
self.addCleanup(self.dataprocessclient.delete_data_process, dataprocess_id)
self.addCleanup(self.dataprocessclient.delete_data_process_definition, dataprocessdef_id)
# Test for provenance. Get Data product produced by the data processes
output_data_product_id,_ = self.rrclient.find_objects(subject=dataprocess_id,
object_type=RT.DataProduct,
predicate=PRED.hasOutputProduct,
id_only=True)
output_data_product_provenance = self.dataproductclient.get_data_product_provenance(output_data_product_id[0])
# Do a basic check to see if there were 3 entries in the provenance graph. Parent and Child and the
# DataProcessDefinition creating the child from the parent.
self.assertTrue(len(output_data_product_provenance) == 3)
self.assertTrue(self.input_dp_id in output_data_product_provenance[output_data_product_id[0]]['parents'])
self.assertTrue(platform_device_id in output_data_product_provenance[self.input_dp_id]['parents'])
self.assertTrue(output_data_product_provenance[platform_device_id]['type'] == 'PlatformDevice')
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_event_transform_worker(self):
self.data_process_objs = []
self._output_stream_ids = []
self.event_verified = Event()
# test that a data process (type: data-product-in / event-out) can be defined and launched.
# verify that event fields are correctly populated
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition, self.stream_def_id)
# create the DataProduct
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product', description='input test stream',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
# create the DPD and two DPs
self.event_data_process_id = self.create_event_data_processes()
# retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(subject=self.event_data_process_id, predicate=PRED.hasSubscription, object_type=RT.Subscription, id_only=False)
log.debug('test_event_transform_worker subscription_obj: %s', subscription_objs[0])
# create a queue to catch the published granules
self.subscription_id = self.pubsub_client.create_subscription(name='parsed_subscription', stream_ids=[self.stream_id], exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription, self.subscription_id)
self.pubsub_client.activate_subscription(self.subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, self.subscription_id)
stream_route = self.pubsub_client.read_stream_route(self.stream_id)
self.publisher = StandaloneStreamPublisher(stream_id=self.stream_id, stream_route=stream_route )
self.start_event_transform_listener()
self.data_modified = Event()
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher.publish(rdt.to_granule())
self.assertTrue(self.event_verified.wait(self.wait_time))
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_bad_argument_map(self):
self._output_stream_ids = []
# test that a data process (type: data-product-in / data-product-out) parameter mapping it validated during
# data process creation and that the correct exception is raised for both input and output.
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition, self.stream_def_id)
# create the DataProduct that is the input to the data processes
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product', description='input test stream',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# two data processes using one transform and one DPD
dp1_func_output_dp_id = self.create_output_data_product()
# Set up DPD and DP #2 - array add function
tf_obj = IonObject(RT.TransformFunction,
name='add_array_func',
description='adds values in an array',
function='add_arrays',
module="ion_example.add_arrays",
arguments=['arr1', 'arr2'],
function_type=TransformFunctionType.TRANSFORM,
uri='http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(RT.DataProcessDefinition,
name='add_arrays',
description='adds the values of two arrays',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS
)
add_array_dpd_id = self.dataprocessclient.create_data_process_definition(data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(self.stream_def_id, add_array_dpd_id, binding='add_array_func' )
# create the data process with invalid argument map
argument_map = {"arr1": "foo", "arr2": "bar"}
output_param = "salinity"
with self.assertRaises(BadRequest) as cm:
dp1_data_process_id = self.dataprocessclient.create_data_process(data_process_definition_id=add_array_dpd_id, inputs=[self.input_dp_id],
outputs=[dp1_func_output_dp_id], argument_map=argument_map, out_param_name=output_param)
ex = cm.exception
log.debug(' exception raised: %s', cm)
self.assertEqual(ex.message, "Input data product does not contain the parameters defined in argument map")
# create the data process with invalid output parameter name
argument_map = {"arr1": "conductivity", "arr2": "pressure"}
output_param = "foo"
with self.assertRaises(BadRequest) as cm:
dp1_data_process_id = self.dataprocessclient.create_data_process(data_process_definition_id=add_array_dpd_id, inputs=[self.input_dp_id],
outputs=[dp1_func_output_dp_id], argument_map=argument_map, out_param_name=output_param)
ex = cm.exception
log.debug(' exception raised: %s', cm)
self.assertEqual(ex.message, "Output data product does not contain the output parameter name provided")
def create_event_data_processes(self):
# two data processes using one transform and one DPD
argument_map= {"a": "salinity"}
# set up DPD and DP #2 - array add function
tf_obj = IonObject(RT.TransformFunction,
name='validate_salinity_array',
description='validate_salinity_array',
function='validate_salinity_array',
module="ion.processes.data.transforms.test.test_transform_worker",
arguments=['a'],
function_type=TransformFunctionType.TRANSFORM
)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(RT.DataProcessDefinition,
name='validate_salinity_array',
description='validate_salinity_array',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS,
)
add_array_dpd_id = self.dataprocessclient.create_data_process_definition(data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(self.stream_def_id, add_array_dpd_id, binding='validate_salinity_array' )
# create the data process
dp1_data_process_id = self.dataprocessclient.create_data_process(data_process_definition_id=add_array_dpd_id, inputs=[self.input_dp_id],
outputs=None, argument_map=argument_map)
self.damsclient.register_process(dp1_data_process_id)
self.addCleanup(self.dataprocessclient.delete_data_process, dp1_data_process_id)
return dp1_data_process_id
def create_data_process(self):
# two data processes using one transform and one DPD
dp1_func_output_dp_id = self.create_output_data_product()
argument_map = {"arr1": "conductivity", "arr2": "pressure"}
output_param = "salinity"
# set up DPD and DP #2 - array add function
tf_obj = IonObject(RT.TransformFunction,
name='add_array_func',
description='adds values in an array',
function='add_arrays',
module="ion_example.add_arrays",
arguments=['arr1', 'arr2'],
function_type=TransformFunctionType.TRANSFORM,
uri='http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(RT.DataProcessDefinition,
name='add_arrays',
description='adds the values of two arrays',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS,
version_label='1.0a'
)
add_array_dpd_id = self.dataprocessclient.create_data_process_definition(data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(self.stream_def_id, add_array_dpd_id, binding='add_array_func' )
# create the data process
dp1_data_process_id = self.dataprocessclient.create_data_process(data_process_definition_id=add_array_dpd_id, inputs=[self.input_dp_id],
outputs=[dp1_func_output_dp_id], argument_map=argument_map, out_param_name=output_param)
self.damsclient.register_process(dp1_data_process_id)
#self.addCleanup(self.dataprocessclient.delete_data_process, dp1_data_process_id)
# add an attachment object to this DPD to test new SA-21
import msgpack
attachment_content = 'foo bar'
attachment_obj = IonObject( RT.Attachment,
name='test_attachment',
attachment_type=AttachmentType.ASCII,
content_type='text/plain',
content=msgpack.packb(attachment_content))
att_id = self.rrclient.create_attachment(add_array_dpd_id, attachment_obj)
self.addCleanup(self.rrclient.delete_attachment, att_id)
return add_array_dpd_id, dp1_data_process_id, dp1_func_output_dp_id
def create_output_data_product(self):
dp1_outgoing_stream_id = self.pubsub_client.create_stream_definition(name='dp1_stream', parameter_dictionary_id=self.parameter_dict_id)
dp1_output_dp_obj = IonObject( RT.DataProduct,
name='data_process1_data_product',
description='output of add array func',
temporal_domain = self.time_dom.dump(),
spatial_domain = self.spatial_dom.dump())
dp1_func_output_dp_id = self.dataproductclient.create_data_product(dp1_output_dp_obj, dp1_outgoing_stream_id)
self.addCleanup(self.dataproductclient.delete_data_product, dp1_func_output_dp_id)
# retrieve the id of the OUTPUT stream from the out Data Product and add to granule logger
stream_ids, _ = self.rrclient.find_objects(dp1_func_output_dp_id, PRED.hasStream, None, True)
self._output_stream_ids.append(stream_ids[0])
subscription_id = self.pubsub_client.create_subscription('validator', data_product_ids=[dp1_func_output_dp_id])
self.addCleanup(self.pubsub_client.delete_subscription, subscription_id)
def on_granule(msg, route, stream_id):
log.debug('recv_packet stream_id: %s route: %s msg: %s', stream_id, route, msg)
self.validate_output_granule(msg, route, stream_id)
self.granule_verified.set()
validator = StandaloneStreamSubscriber('validator', callback=on_granule)
validator.start()
self.addCleanup(validator.stop)
self.pubsub_client.activate_subscription(subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, subscription_id)
return dp1_func_output_dp_id
def validate_event(self, *args, **kwargs):
"""
This method is a callback function for receiving DataProcessStatusEvent.
"""
data_process_event = args[0]
log.debug("DataProcessStatusEvent: %s" , str(data_process_event.__dict__))
# if data process already created, check origin
if self.dp_list:
self.assertIn( data_process_event.origin, self.dp_list)
# if this is a heartbeat event then 100 granules have been processed
if 'data process status update.' in data_process_event.description:
self.heartbeat_event_verified.set()
else:
# else check that this is the assign event
if 'Data process assigned to transform worker' in data_process_event.description:
self.worker_assigned_event_verified.set()
elif 'Data process created for data product' in data_process_event.description:
self.dp_created_event_verified.set()
def validate_output_granule(self, msg, route, stream_id):
self.assertIn( stream_id, self._output_stream_ids)
rdt = RecordDictionaryTool.load_from_granule(msg)
log.debug('validate_output_granule rdt: %s', rdt)
sal_val = rdt['salinity']
np.testing.assert_array_equal(sal_val, np.array([3]))
def start_event_listener(self):
es = EventSubscriber(event_type=OT.DataProcessStatusEvent, callback=self.validate_event)
es.start()
self.addCleanup(es.stop)
def validate_transform_event(self, *args, **kwargs):
"""
This method is a callback function for receiving DataProcessStatusEvent.
"""
status_alert_event = args[0]
np.testing.assert_array_equal(status_alert_event.origin, self.stream_id )
np.testing.assert_array_equal(status_alert_event.values, np.array([self.event_data_process_id]))
log.debug("DeviceStatusAlertEvent: %s" , str(status_alert_event.__dict__))
self.event_verified.set()
def start_event_transform_listener(self):
es = EventSubscriber(event_type=OT.DeviceStatusAlertEvent, callback=self.validate_transform_event)
es.start()
self.addCleanup(es.stop)
def test_download(self):
egg_url = 'http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
egg_path = TransformWorker.download_egg(egg_url)
import pkg_resources
pkg_resources.working_set.add_entry(egg_path)
from ion_example.add_arrays import add_arrays
a = add_arrays(1,2)
self.assertEquals(a,3)
class TestDataProcessManagementPrime(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dataset_management = DatasetManagementServiceClient()
self.resource_registry = self.container.resource_registry
self.pubsub_management = PubsubManagementServiceClient()
self.data_process_management = DataProcessManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.validators = 0
def lc_preload(self):
config = DotDict()
config.op = 'load'
config.scenario = 'BASE,LC_TEST'
config.categories = 'ParameterFunctions,ParameterDefs,ParameterDictionary'
config.path = 'res/preload/r2_ioc'
self.container.spawn_process('preload','ion.processes.bootstrap.ion_loader','IONLoader', config)
def ctd_plain_input_data_product(self):
available_fields = [
'internal_timestamp',
'temp',
'preferred_timestamp',
'time',
'port_timestamp',
'quality_flag',
'lat',
'conductivity',
'driver_timestamp',
'lon',
'pressure']
return self.make_data_product('ctd_parsed_param_dict', 'ctd plain test', available_fields)
def ctd_plain_salinity(self):
available_fields = [
'internal_timestamp',
'preferred_timestamp',
'time',
'port_timestamp',
'quality_flag',
'lat',
'driver_timestamp',
'lon',
'salinity']
return self.make_data_product('ctd_parsed_param_dict', 'salinity', available_fields)
def ctd_plain_density(self):
available_fields = [
'internal_timestamp',
'preferred_timestamp',
'time',
'port_timestamp',
'quality_flag',
'lat',
'driver_timestamp',
'lon',
'density']
return self.make_data_product('ctd_parsed_param_dict', 'density', available_fields)
def ctd_instrument_data_product(self):
available_fields = [
'internal_timestamp',
'temp',
'preferred_timestamp',
'time',
'port_timestamp',
'quality_flag',
'lat',
'conductivity',
'driver_timestamp',
'lon',
'pressure']
return self.make_data_product('ctd_LC_TEST', 'ctd instrument', available_fields)
def make_data_product(self, pdict_name, dp_name, available_fields=[]):
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(pdict_name, id_only=True)
stream_def_id = self.pubsub_management.create_stream_definition('%s stream_def' % dp_name, parameter_dictionary_id=pdict_id, available_fields=available_fields or None)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
tdom, sdom = time_series_domain()
tdom = tdom.dump()
sdom = sdom.dump()
dp_obj = DataProduct(name=dp_name)
dp_obj.temporal_domain = tdom
dp_obj.spatial_domain = sdom
data_product_id = self.data_product_management.create_data_product(dp_obj, stream_definition_id=stream_def_id)
self.addCleanup(self.data_product_management.delete_data_product, data_product_id)
return data_product_id
def google_dt_data_product(self):
return self.make_data_product('google_dt', 'visual')
def ctd_derived_data_product(self):
return self.make_data_product('ctd_LC_TEST', 'ctd derived products')
def publish_to_plain_data_product(self, data_product_id):
stream_ids, _ = self.resource_registry.find_objects(subject=data_product_id, predicate=PRED.hasStream, id_only=True)
self.assertTrue(len(stream_ids))
stream_id = stream_ids.pop()
route = self.pubsub_management.read_stream_route(stream_id)
stream_definition = self.pubsub_management.read_stream_definition(stream_id=stream_id)
stream_def_id = stream_definition._id
publisher = StandaloneStreamPublisher(stream_id, route)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
now = time.time()
ntp_now = now + 2208988800 # Do not use in production, this is a loose translation
rdt['internal_timestamp'] = [ntp_now]
rdt['temp'] = [20.0]
rdt['preferred_timestamp'] = ['driver_timestamp']
rdt['time'] = [ntp_now]
rdt['port_timestamp'] = [ntp_now]
rdt['quality_flag'] = [None]
rdt['lat'] = [45]
rdt['conductivity'] = [4.2914]
rdt['driver_timestamp'] = [ntp_now]
rdt['lon'] = [-71]
rdt['pressure'] = [3.068]
granule = rdt.to_granule()
publisher.publish(granule)
def publish_to_data_product(self, data_product_id):
stream_ids, _ = self.resource_registry.find_objects(subject=data_product_id, predicate=PRED.hasStream, id_only=True)
self.assertTrue(len(stream_ids))
stream_id = stream_ids.pop()
route = self.pubsub_management.read_stream_route(stream_id)
stream_definition = self.pubsub_management.read_stream_definition(stream_id=stream_id)
stream_def_id = stream_definition._id
publisher = StandaloneStreamPublisher(stream_id, route)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
now = time.time()
ntp_now = now + 2208988800 # Do not use in production, this is a loose translation
rdt['internal_timestamp'] = [ntp_now]
rdt['temp'] = [300000]
rdt['preferred_timestamp'] = ['driver_timestamp']
rdt['time'] = [ntp_now]
rdt['port_timestamp'] = [ntp_now]
rdt['quality_flag'] = [None]
rdt['lat'] = [45]
rdt['conductivity'] = [4341400]
rdt['driver_timestamp'] = [ntp_now]
rdt['lon'] = [-71]
rdt['pressure'] = [256.8]
granule = rdt.to_granule()
publisher.publish(granule)
def setup_subscriber(self, data_product_id, callback):
stream_ids, _ = self.resource_registry.find_objects(subject=data_product_id, predicate=PRED.hasStream, id_only=True)
self.assertTrue(len(stream_ids))
stream_id = stream_ids.pop()
sub_id = self.pubsub_management.create_subscription('validator_%s'%self.validators, stream_ids=[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('validator_%s' % self.validators, callback=callback)
subscriber.start()
self.addCleanup(subscriber.stop)
self.validators+=1
return subscriber
def create_density_transform_function(self):
tf = TransformFunction(name='ctdbp_l2_density', module='ion.processes.data.transforms.ctdbp.ctdbp_L2_density', cls='CTDBP_DensityTransformAlgorithm')
tf_id = self.data_process_management.create_transform_function(tf)
self.addCleanup(self.data_process_management.delete_transform_function, tf_id)
return tf_id
def create_salinity_transform_function(self):
tf = TransformFunction(name='ctdbp_l2_salinity', module='ion.processes.data.transforms.ctdbp.ctdbp_L2_salinity', cls='CTDBP_SalinityTransformAlgorithm')
tf_id = self.data_process_management.create_transform_function(tf)
self.addCleanup(self.data_process_management.delete_transform_function, tf_id)
return tf_id
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_data_process_prime(self):
self.lc_preload()
instrument_data_product_id = self.ctd_instrument_data_product()
derived_data_product_id = self.ctd_derived_data_product()
data_process_id = self.data_process_management.create_data_process2(in_data_product_ids=[instrument_data_product_id], out_data_product_ids=[derived_data_product_id])
self.addCleanup(self.data_process_management.delete_data_process2, data_process_id)
self.data_process_management.activate_data_process2(data_process_id)
self.addCleanup(self.data_process_management.deactivate_data_process2, data_process_id)
validated = Event()
def validation(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
np.testing.assert_array_almost_equal(rdt['conductivity_L1'], np.array([42.914]))
np.testing.assert_array_almost_equal(rdt['temp_L1'], np.array([20.]))
np.testing.assert_array_almost_equal(rdt['pressure_L1'], np.array([3.068]))
np.testing.assert_array_almost_equal(rdt['density'], np.array([1021.7144739593881]))
np.testing.assert_array_almost_equal(rdt['salinity'], np.array([30.935132729668283]))
validated.set()
self.setup_subscriber(derived_data_product_id, callback=validation)
self.publish_to_data_product(instrument_data_product_id)
self.assertTrue(validated.wait(10))
def test_older_transform(self):
input_data_product_id = self.ctd_plain_input_data_product()
conductivity_data_product_id = self.make_data_product('ctd_parsed_param_dict', 'conductivity_product', ['time', 'conductivity'])
conductivity_stream_def_id = self.get_named_stream_def('conductivity_product stream_def')
temperature_data_product_id = self.make_data_product('ctd_parsed_param_dict', 'temperature_product', ['time', 'temp'])
temperature_stream_def_id = self.get_named_stream_def('temperature_product stream_def')
pressure_data_product_id = self.make_data_product('ctd_parsed_param_dict', 'pressure_product', ['time', 'pressure'])
pressure_stream_def_id = self.get_named_stream_def('pressure_product stream_def')
dpd = DataProcessDefinition(name='ctdL0')
dpd.data_process_type = DataProcessTypeEnum.TRANSFORM
dpd.module = 'ion.processes.data.transforms.ctd.ctd_L0_all'
dpd.class_name = 'ctd_L0_all'
data_process_definition_id = self.data_process_management.create_data_process_definition(dpd)
self.addCleanup(self.data_process_management.delete_data_process_definition, data_process_definition_id)
self.data_process_management.assign_stream_definition_to_data_process_definition(conductivity_stream_def_id, data_process_definition_id, binding='conductivity')
self.data_process_management.assign_stream_definition_to_data_process_definition(temperature_stream_def_id, data_process_definition_id, binding='temperature')
self.data_process_management.assign_stream_definition_to_data_process_definition(pressure_stream_def_id, data_process_definition_id, binding='pressure')
data_process_id = self.data_process_management.create_data_process2(data_process_definition_id=data_process_definition_id, in_data_product_ids=[input_data_product_id], out_data_product_ids=[conductivity_data_product_id, temperature_data_product_id, pressure_data_product_id])
self.addCleanup(self.data_process_management.delete_data_process2, data_process_id)
self.data_process_management.activate_data_process2(data_process_id)
self.addCleanup(self.data_process_management.deactivate_data_process2, data_process_id)
conductivity_validated = Event()
def validate_conductivity(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
np.testing.assert_array_almost_equal(rdt['conductivity'], np.array([4.2914]))
conductivity_validated.set()
self.setup_subscriber(conductivity_data_product_id, callback=validate_conductivity)
temperature_validated = Event()
def validate_temperature(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
np.testing.assert_array_almost_equal(rdt['temp'], np.array([20.0]))
temperature_validated.set()
self.setup_subscriber(temperature_data_product_id, callback=validate_temperature)
pressure_validated = Event()
def validate_pressure(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
np.testing.assert_array_almost_equal(rdt['pressure'], np.array([3.068]))
pressure_validated.set()
self.setup_subscriber(pressure_data_product_id, callback=validate_pressure)
self.publish_to_plain_data_product(input_data_product_id)
self.assertTrue(conductivity_validated.wait(10))
self.assertTrue(temperature_validated.wait(10))
self.assertTrue(pressure_validated.wait(10))
def get_named_stream_def(self, name):
stream_def_ids, _ = self.resource_registry.find_resources(name=name, restype=RT.StreamDefinition, id_only=True)
return stream_def_ids[0]
def test_actors(self):
input_data_product_id = self.ctd_plain_input_data_product()
output_data_product_id = self.ctd_plain_density()
actor = self.create_density_transform_function()
route = {input_data_product_id: {output_data_product_id: actor}}
config = DotDict()
config.process.routes = route
config.process.params.lat = 45.
config.process.params.lon = -71.
data_process_id = self.data_process_management.create_data_process2(in_data_product_ids=[input_data_product_id], out_data_product_ids=[output_data_product_id], configuration=config)
self.addCleanup(self.data_process_management.delete_data_process2, data_process_id)
self.data_process_management.activate_data_process2(data_process_id)
self.addCleanup(self.data_process_management.deactivate_data_process2, data_process_id)
validated = Event()
def validation(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
# The value I use is a double, the value coming back is only a float32 so there's some data loss but it should be precise to the 4th digit
np.testing.assert_array_almost_equal(rdt['density'], np.array([1021.6839775385847]), decimal=4)
validated.set()
self.setup_subscriber(output_data_product_id, callback=validation)
self.publish_to_plain_data_product(input_data_product_id)
self.assertTrue(validated.wait(10))
def test_multi_in_out(self):
input1 = self.ctd_plain_input_data_product()
input2 = self.make_data_product('ctd_parsed_param_dict', 'input2')
density_dp_id = self.ctd_plain_density()
salinity_dp_id = self.ctd_plain_salinity()
density_actor = self.create_density_transform_function()
salinity_actor = self.create_salinity_transform_function()
routes = {
input1 : {
density_dp_id : density_actor,
salinity_dp_id : salinity_actor
},
input2 : {
density_dp_id : density_actor
}
}
config = DotDict()
config.process.routes = routes
config.process.params.lat = 45.
config.process.params.lon = -71.
data_process_id = self.data_process_management.create_data_process2(in_data_product_ids=[input1, input2], out_data_product_ids=[density_dp_id, salinity_dp_id], configuration=config)
self.addCleanup(self.data_process_management.delete_data_process2, data_process_id)
self.data_process_management.activate_data_process2(data_process_id)
self.addCleanup(self.data_process_management.deactivate_data_process2, data_process_id)
density_validated = Event()
salinity_validated = Event()
def density_validation(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
np.testing.assert_array_almost_equal(rdt['density'], np.array([1021.6839775385847]), decimal=4)
density_validated.set()
def salinity_validation(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
np.testing.assert_array_almost_equal(rdt['salinity'], np.array([30.93513240786831]), decimal=4)
salinity_validated.set()
self.setup_subscriber(density_dp_id, callback=density_validation)
self.setup_subscriber(salinity_dp_id, callback=salinity_validation)
self.publish_to_plain_data_product(input1)
self.assertTrue(density_validated.wait(10))
self.assertTrue(salinity_validated.wait(10))
density_validated.clear()
salinity_validated.clear()
self.publish_to_plain_data_product(input2)
self.assertTrue(density_validated.wait(10))
self.assertFalse(salinity_validated.wait(0.75))
density_validated.clear()
salinity_validated.clear()
def test_visual_transform(self):
input_data_product_id = self.ctd_plain_input_data_product()
output_data_product_id = self.google_dt_data_product()
dpd = DataProcessDefinition(name='visual transform')
dpd.data_process_type = DataProcessTypeEnum.TRANSFORM
dpd.module = 'ion.processes.data.transforms.viz.google_dt'
dpd.class_name = 'VizTransformGoogleDT'
#--------------------------------------------------------------------------------
# Walk before we base jump
#--------------------------------------------------------------------------------
data_process_definition_id = self.data_process_management.create_data_process_definition(dpd)
self.addCleanup(self.data_process_management.delete_data_process_definition, data_process_definition_id)
data_process_id = self.data_process_management.create_data_process2(data_process_definition_id=data_process_definition_id, in_data_product_ids=[input_data_product_id], out_data_product_ids=[output_data_product_id])
self.addCleanup(self.data_process_management.delete_data_process2,data_process_id)
self.data_process_management.activate_data_process2(data_process_id)
self.addCleanup(self.data_process_management.deactivate_data_process2, data_process_id)
validated = Event()
def validation(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
self.assertTrue(rdt['google_dt_components'] is not None)
validated.set()
self.setup_subscriber(output_data_product_id, callback=validation)
self.publish_to_plain_data_product(input_data_product_id)
self.assertTrue(validated.wait(10))
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)
class TestTransformPrime(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml') # Because hey why not?!
self.dataset_management = DatasetManagementServiceClient()
self.data_process_management = DataProcessManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
def setup_streams(self):
in_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('sbe37_L0_test', id_only=True)
out_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('sbe37_L1_test', id_only=True)
in_stream_def_id = self.pubsub_management.create_stream_definition('L0 SBE37', parameter_dictionary_id=in_pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, in_stream_def_id)
out_stream_def_id = self.pubsub_management.create_stream_definition('L1 SBE37', parameter_dictionary_id=out_pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, out_stream_def_id)
in_stream_id, in_route = self.pubsub_management.create_stream('L0 input', stream_definition_id=in_stream_def_id, exchange_point='test')
self.addCleanup(self.pubsub_management.delete_stream, in_stream_id)
out_stream_id, out_route = self.pubsub_management.create_stream('L0 output', stream_definition_id=out_stream_def_id, exchange_point='test')
self.addCleanup(self.pubsub_management.delete_stream, out_stream_id)
return [(in_stream_id, in_stream_def_id), (out_stream_id, out_stream_def_id)]
def setup_advanced_streams(self):
in_pdict_id = out_pdict_id = self.dataset_management.read_parameter_dictionary_by_name('sbe37_LC_TEST', id_only=True)
in_stream_def_id = self.pubsub_management.create_stream_definition('sbe37_instrument', parameter_dictionary_id=in_pdict_id, available_fields=['time', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0', 'lat', 'lon'])
self.addCleanup(self.pubsub_management.delete_stream_definition, in_stream_def_id)
out_stream_def_id = self.pubsub_management.create_stream_definition('sbe37_l2', parameter_dictionary_id=out_pdict_id, available_fields=['time', 'rho','PRACSAL_L2'])
self.addCleanup(self.pubsub_management.delete_stream_definition, out_stream_def_id)
in_stream_id, in_route = self.pubsub_management.create_stream('instrument stream', stream_definition_id=in_stream_def_id, exchange_point='test')
self.addCleanup(self.pubsub_management.delete_stream, in_stream_id)
out_stream_id, out_route = self.pubsub_management.create_stream('data product stream', stream_definition_id=out_stream_def_id, exchange_point='test')
self.addCleanup(self.pubsub_management.delete_stream, out_stream_id)
return [(in_stream_id, in_stream_def_id), (out_stream_id, out_stream_def_id)]
def preload(self):
config = DotDict()
config.op = 'load'
config.scenario = 'BASE,LC_TEST'
config.categories = 'ParameterFunctions,ParameterDefs,ParameterDictionary'
config.path = 'res/preload/r2_ioc'
self.container.spawn_process('preload','ion.processes.bootstrap.ion_loader','IONLoader', config)
def setup_advanced_transform(self):
self.preload()
queue_name = 'transform_prime'
stream_info = self.setup_advanced_streams()
in_stream_id, in_stream_def_id = stream_info[0]
out_stream_id, out_stream_def_id = stream_info[1]
routes = {}
routes[(in_stream_id, out_stream_id)]= None
config = DotDict()
config.process.queue_name = queue_name
config.process.routes = routes
config.process.publish_streams = {out_stream_id:out_stream_id}
sub_id = self.pubsub_management.create_subscription(queue_name, stream_ids=[in_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)
self.container.spawn_process('transform_prime', 'ion.processes.data.transforms.transform_prime','TransformPrime', config)
listen_sub_id = self.pubsub_management.create_subscription('listener', stream_ids=[out_stream_id])
self.addCleanup(self.pubsub_management.delete_subscription, listen_sub_id)
self.pubsub_management.activate_subscription(listen_sub_id)
self.addCleanup(self.pubsub_management.deactivate_subscription, listen_sub_id)
return [(in_stream_id, in_stream_def_id), (out_stream_id, out_stream_def_id)]
def setup_transform(self):
self.preload()
queue_name = 'transform_prime'
stream_info = self.setup_streams()
in_stream_id, in_stream_def_id = stream_info[0]
out_stream_id, out_stream_def_id = stream_info[1]
routes = {}
routes[(in_stream_id, out_stream_id)]= None
config = DotDict()
config.process.queue_name = queue_name
config.process.routes = routes
config.process.publish_streams = {out_stream_id:out_stream_id}
sub_id = self.pubsub_management.create_subscription(queue_name, stream_ids=[in_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)
self.container.spawn_process('transform_prime', 'ion.processes.data.transforms.transform_prime','TransformPrime', config)
listen_sub_id = self.pubsub_management.create_subscription('listener', stream_ids=[out_stream_id])
self.addCleanup(self.pubsub_management.delete_subscription, listen_sub_id)
self.pubsub_management.activate_subscription(listen_sub_id)
self.addCleanup(self.pubsub_management.deactivate_subscription, listen_sub_id)
return [(in_stream_id, in_stream_def_id), (out_stream_id, out_stream_def_id)]
def setup_validator(self, validator):
listener = StandaloneStreamSubscriber('listener', validator)
listener.start()
self.addCleanup(listener.stop)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_execute_advanced_transform(self):
# Runs a transform across L0-L2 with stream definitions including available fields
streams = self.setup_advanced_transform()
in_stream_id, in_stream_def_id = streams[0]
out_stream_id, out_stream_defs_id = streams[1]
validation_event = Event()
def validator(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
if not np.allclose(rdt['rho'], np.array([1001.0055034])):
return
validation_event.set()
self.setup_validator(validator)
in_route = self.pubsub_management.read_stream_route(in_stream_id)
publisher = StandaloneStreamPublisher(in_stream_id, in_route)
outbound_rdt = RecordDictionaryTool(stream_definition_id=in_stream_def_id)
outbound_rdt['time'] = [0]
outbound_rdt['TEMPWAT_L0'] = [280000]
outbound_rdt['CONDWAT_L0'] = [100000]
outbound_rdt['PRESWAT_L0'] = [2789]
outbound_rdt['lat'] = [45]
outbound_rdt['lon'] = [-71]
outbound_granule = outbound_rdt.to_granule()
publisher.publish(outbound_granule)
self.assertTrue(validation_event.wait(2))
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_execute_transform(self):
streams = self.setup_transform()
in_stream_id, in_stream_def_id = streams[0]
out_stream_id, out_stream_def_id = streams[1]
validation_event = Event()
def validator(msg, route, stream_id):
rdt = RecordDictionaryTool.load_from_granule(msg)
if not np.allclose(rdt['TEMPWAT_L1'], np.array([18.])):
return
if not np.allclose(rdt['CONDWAT_L1'], np.array([0.5])):
return
if not np.allclose(rdt['PRESWAT_L1'], np.array([0.04536611])):
return
validation_event.set()
self.setup_validator(validator)
in_route = self.pubsub_management.read_stream_route(in_stream_id)
publisher = StandaloneStreamPublisher(in_stream_id, in_route)
outbound_rdt = RecordDictionaryTool(stream_definition_id=in_stream_def_id)
outbound_rdt['time'] = [0]
outbound_rdt['TEMPWAT_L0'] = [280000]
outbound_rdt['CONDWAT_L0'] = [100000]
outbound_rdt['PRESWAT_L0'] = [2789]
outbound_rdt['lat'] = [45]
outbound_rdt['lon'] = [-71]
outbound_granule = outbound_rdt.to_granule()
publisher.publish(outbound_granule)
self.assertTrue(validation_event.wait(2))
class PubsubManagementIntTest(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.pubsub_management = PubsubManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
self.pdicts = {}
self.queue_cleanup = list()
self.exchange_cleanup = list()
self.context_ids = set()
def tearDown(self):
for queue in self.queue_cleanup:
xn = self.container.ex_manager.create_xn_queue(queue)
xn.delete()
for exchange in self.exchange_cleanup:
xp = self.container.ex_manager.create_xp(exchange)
xp.delete()
self.cleanup_contexts()
def test_stream_def_crud(self):
# Test Creation
pdict = DatasetManagementService.get_parameter_dictionary_by_name('ctd_parsed_param_dict')
stream_definition_id = self.pubsub_management.create_stream_definition('ctd parsed', parameter_dictionary_id=pdict.identifier)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_definition_id)
# Make sure there is an assoc
self.assertTrue(self.resource_registry.find_associations(subject=stream_definition_id, predicate=PRED.hasParameterDictionary, object=pdict.identifier, id_only=True))
# Test Reading
stream_definition = self.pubsub_management.read_stream_definition(stream_definition_id)
self.assertTrue(PubsubManagementService._compare_pdicts(pdict.dump(), stream_definition.parameter_dictionary))
# Test comparisons
in_stream_definition_id = self.pubsub_management.create_stream_definition('L0 products', parameter_dictionary_id=pdict.identifier, available_fields=['time','temp','conductivity','pressure'])
self.addCleanup(self.pubsub_management.delete_stream_definition, in_stream_definition_id)
out_stream_definition_id = in_stream_definition_id
self.assertTrue(self.pubsub_management.compare_stream_definition(in_stream_definition_id, out_stream_definition_id))
self.assertTrue(self.pubsub_management.compatible_stream_definitions(in_stream_definition_id, out_stream_definition_id))
out_stream_definition_id = self.pubsub_management.create_stream_definition('L2 Products', parameter_dictionary_id=pdict.identifier, available_fields=['time','salinity','density'])
self.addCleanup(self.pubsub_management.delete_stream_definition, out_stream_definition_id)
self.assertFalse(self.pubsub_management.compare_stream_definition(in_stream_definition_id, out_stream_definition_id))
self.assertTrue(self.pubsub_management.compatible_stream_definitions(in_stream_definition_id, out_stream_definition_id))
@unittest.skip('Needs to be refactored for cleanup')
def test_validate_stream_defs(self):
self.addCleanup(self.cleanup_contexts)
#test no input
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0'])
outgoing_pdict_id = self._get_pdict(['DENSITY', 'PRACSAL', 'TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
available_fields_in = []
available_fields_out = []
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_0', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_0', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertFalse(result)
#test input with no output
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0'])
outgoing_pdict_id = self._get_pdict(['DENSITY', 'PRACSAL', 'TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
available_fields_in = ['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0']
available_fields_out = []
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_1', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_1', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertTrue(result)
#test available field missing parameter context definition -- missing PRESWAT_L0
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0'])
outgoing_pdict_id = self._get_pdict(['DENSITY', 'PRACSAL', 'TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
available_fields_in = ['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0']
available_fields_out = ['DENSITY']
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_2', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_2', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertFalse(result)
#test l1 from l0
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0'])
outgoing_pdict_id = self._get_pdict(['TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
available_fields_in = ['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0']
available_fields_out = ['TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1']
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_3', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_3', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertTrue(result)
#test l2 from l0
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0'])
outgoing_pdict_id = self._get_pdict(['TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1', 'DENSITY', 'PRACSAL'])
available_fields_in = ['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0']
available_fields_out = ['DENSITY', 'PRACSAL']
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_4', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_4', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertTrue(result)
#test Ln from L0
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0'])
outgoing_pdict_id = self._get_pdict(['DENSITY','PRACSAL','TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
available_fields_in = ['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0']
available_fields_out = ['DENSITY', 'PRACSAL', 'TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1']
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_5', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_5', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertTrue(result)
#test L2 from L1
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON', 'TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
outgoing_pdict_id = self._get_pdict(['DENSITY','PRACSAL','TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
available_fields_in = ['TIME', 'LAT', 'LON', 'TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1']
available_fields_out = ['DENSITY', 'PRACSAL']
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_6', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_6', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertTrue(result)
#test L1 from L0 missing L0
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON'])
outgoing_pdict_id = self._get_pdict(['TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
available_fields_in = ['TIME', 'LAT', 'LON']
available_fields_out = ['DENSITY', 'PRACSAL']
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_7', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_7', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertFalse(result)
#test L2 from L0 missing L0
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON'])
outgoing_pdict_id = self._get_pdict(['DENSITY', 'PRACSAL', 'TEMPWAT_L1', 'CONDWAT_L1', 'PRESWAT_L1'])
available_fields_in = ['TIME', 'LAT', 'LON']
available_fields_out = ['DENSITY', 'PRACSAL']
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_8', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_8', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertFalse(result)
#test L2 from L0 missing L1
incoming_pdict_id = self._get_pdict(['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0'])
outgoing_pdict_id = self._get_pdict(['DENSITY', 'PRACSAL'])
available_fields_in = ['TIME', 'LAT', 'LON', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0']
available_fields_out = ['DENSITY', 'PRACSAL']
incoming_stream_def_id = self.pubsub_management.create_stream_definition('in_sd_9', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
self.addCleanup(self.pubsub_management.delete_stream_definition, incoming_stream_def_id)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('out_sd_9', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
self.addCleanup(self.pubsub_management.delete_stream_definition, outgoing_stream_def_id)
result = self.pubsub_management.validate_stream_defs(incoming_stream_def_id, outgoing_stream_def_id)
self.assertFalse(result)
def publish_on_stream(self, stream_id, msg):
stream = self.pubsub_management.read_stream(stream_id)
stream_route = stream.stream_route
publisher = StandaloneStreamPublisher(stream_id=stream_id, stream_route=stream_route)
publisher.publish(msg)
def test_stream_crud(self):
stream_def_id = self.pubsub_management.create_stream_definition('test_definition', stream_type='stream')
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
topic_id = self.pubsub_management.create_topic(name='test_topic', exchange_point='test_exchange')
self.addCleanup(self.pubsub_management.delete_topic, topic_id)
self.exchange_cleanup.append('test_exchange')
topic2_id = self.pubsub_management.create_topic(name='another_topic', exchange_point='outside')
self.addCleanup(self.pubsub_management.delete_topic, topic2_id)
stream_id, route = self.pubsub_management.create_stream(name='test_stream', topic_ids=[topic_id, topic2_id], exchange_point='test_exchange', stream_definition_id=stream_def_id)
topics, assocs = self.resource_registry.find_objects(subject=stream_id, predicate=PRED.hasTopic, id_only=True)
self.assertEquals(topics,[topic_id])
defs, assocs = self.resource_registry.find_objects(subject=stream_id, predicate=PRED.hasStreamDefinition, id_only=True)
self.assertTrue(len(defs))
stream = self.pubsub_management.read_stream(stream_id)
self.assertEquals(stream.name,'test_stream')
self.pubsub_management.delete_stream(stream_id)
with self.assertRaises(NotFound):
self.pubsub_management.read_stream(stream_id)
defs, assocs = self.resource_registry.find_objects(subject=stream_id, predicate=PRED.hasStreamDefinition, id_only=True)
self.assertFalse(len(defs))
topics, assocs = self.resource_registry.find_objects(subject=stream_id, predicate=PRED.hasTopic, id_only=True)
self.assertFalse(len(topics))
def test_data_product_subscription(self):
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 parsed', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
tdom, sdom = time_series_domain()
dp = DataProduct(name='ctd parsed')
dp.spatial_domain = sdom.dump()
dp.temporal_domain = tdom.dump()
data_product_id = self.data_product_management.create_data_product(data_product=dp, stream_definition_id=stream_def_id)
self.addCleanup(self.data_product_management.delete_data_product, data_product_id)
subscription_id = self.pubsub_management.create_subscription('validator', data_product_ids=[data_product_id])
self.addCleanup(self.pubsub_management.delete_subscription, subscription_id)
validated = Event()
def validation(msg, route, stream_id):
validated.set()
stream_ids, _ = self.resource_registry.find_objects(subject=data_product_id, predicate=PRED.hasStream, id_only=True)
dp_stream_id = stream_ids.pop()
validator = StandaloneStreamSubscriber('validator', callback=validation)
validator.start()
self.addCleanup(validator.stop)
self.pubsub_management.activate_subscription(subscription_id)
self.addCleanup(self.pubsub_management.deactivate_subscription, subscription_id)
route = self.pubsub_management.read_stream_route(dp_stream_id)
publisher = StandaloneStreamPublisher(dp_stream_id, route)
publisher.publish('hi')
self.assertTrue(validated.wait(10))
def test_subscription_crud(self):
stream_def_id = self.pubsub_management.create_stream_definition('test_definition', stream_type='stream')
stream_id, route = self.pubsub_management.create_stream(name='test_stream', exchange_point='test_exchange', stream_definition_id=stream_def_id)
subscription_id = self.pubsub_management.create_subscription(name='test subscription', stream_ids=[stream_id], exchange_name='test_queue')
self.exchange_cleanup.append('test_exchange')
subs, assocs = self.resource_registry.find_objects(subject=subscription_id,predicate=PRED.hasStream,id_only=True)
self.assertEquals(subs,[stream_id])
res, _ = self.resource_registry.find_resources(restype=RT.ExchangeName, name='test_queue', id_only=True)
self.assertEquals(len(res),1)
subs, assocs = self.resource_registry.find_subjects(object=subscription_id, predicate=PRED.hasSubscription, id_only=True)
self.assertEquals(subs[0], res[0])
subscription = self.pubsub_management.read_subscription(subscription_id)
self.assertEquals(subscription.exchange_name, 'test_queue')
self.pubsub_management.delete_subscription(subscription_id)
subs, assocs = self.resource_registry.find_objects(subject=subscription_id,predicate=PRED.hasStream,id_only=True)
self.assertFalse(len(subs))
subs, assocs = self.resource_registry.find_subjects(object=subscription_id, predicate=PRED.hasSubscription, id_only=True)
self.assertFalse(len(subs))
self.pubsub_management.delete_stream(stream_id)
self.pubsub_management.delete_stream_definition(stream_def_id)
def test_move_before_activate(self):
stream_id, route = self.pubsub_management.create_stream(name='test_stream', exchange_point='test_xp')
#--------------------------------------------------------------------------------
# Test moving before activate
#--------------------------------------------------------------------------------
subscription_id = self.pubsub_management.create_subscription('first_queue', stream_ids=[stream_id])
xn_ids, _ = self.resource_registry.find_resources(restype=RT.ExchangeName, name='first_queue', id_only=True)
subjects, _ = self.resource_registry.find_subjects(object=subscription_id, predicate=PRED.hasSubscription, id_only=True)
self.assertEquals(xn_ids[0], subjects[0])
self.pubsub_management.move_subscription(subscription_id, exchange_name='second_queue')
xn_ids, _ = self.resource_registry.find_resources(restype=RT.ExchangeName, name='second_queue', id_only=True)
subjects, _ = self.resource_registry.find_subjects(object=subscription_id, predicate=PRED.hasSubscription, id_only=True)
self.assertEquals(len(subjects),1)
self.assertEquals(subjects[0], xn_ids[0])
self.pubsub_management.delete_subscription(subscription_id)
self.pubsub_management.delete_stream(stream_id)
def test_move_activated_subscription(self):
stream_id, route = self.pubsub_management.create_stream(name='test_stream', exchange_point='test_xp')
#--------------------------------------------------------------------------------
# Test moving after activate
#--------------------------------------------------------------------------------
subscription_id = self.pubsub_management.create_subscription('first_queue', stream_ids=[stream_id])
self.pubsub_management.activate_subscription(subscription_id)
xn_ids, _ = self.resource_registry.find_resources(restype=RT.ExchangeName, name='first_queue', id_only=True)
subjects, _ = self.resource_registry.find_subjects(object=subscription_id, predicate=PRED.hasSubscription, id_only=True)
self.assertEquals(xn_ids[0], subjects[0])
self.verified = Event()
def verify(m,r,s):
self.assertEquals(m,'verified')
self.verified.set()
subscriber = StandaloneStreamSubscriber('second_queue', verify)
subscriber.start()
self.pubsub_management.move_subscription(subscription_id, exchange_name='second_queue')
xn_ids, _ = self.resource_registry.find_resources(restype=RT.ExchangeName, name='second_queue', id_only=True)
subjects, _ = self.resource_registry.find_subjects(object=subscription_id, predicate=PRED.hasSubscription, id_only=True)
self.assertEquals(len(subjects),1)
self.assertEquals(subjects[0], xn_ids[0])
publisher = StandaloneStreamPublisher(stream_id, route)
publisher.publish('verified')
self.assertTrue(self.verified.wait(2))
self.pubsub_management.deactivate_subscription(subscription_id)
self.pubsub_management.delete_subscription(subscription_id)
self.pubsub_management.delete_stream(stream_id)
def test_queue_cleanup(self):
stream_id, route = self.pubsub_management.create_stream('test_stream','xp1')
xn_objs, _ = self.resource_registry.find_resources(restype=RT.ExchangeName, name='queue1')
for xn_obj in xn_objs:
xn = self.container.ex_manager.create_xn_queue(xn_obj.name)
xn.delete()
subscription_id = self.pubsub_management.create_subscription('queue1',stream_ids=[stream_id])
xn_ids, _ = self.resource_registry.find_resources(restype=RT.ExchangeName, name='queue1')
self.assertEquals(len(xn_ids),1)
self.pubsub_management.delete_subscription(subscription_id)
xn_ids, _ = self.resource_registry.find_resources(restype=RT.ExchangeName, name='queue1')
self.assertEquals(len(xn_ids),0)
def test_activation_and_deactivation(self):
stream_id, route = self.pubsub_management.create_stream('stream1','xp1')
subscription_id = self.pubsub_management.create_subscription('sub1', stream_ids=[stream_id])
self.check1 = Event()
def verifier(m,r,s):
self.check1.set()
subscriber = StandaloneStreamSubscriber('sub1',verifier)
subscriber.start()
publisher = StandaloneStreamPublisher(stream_id, route)
publisher.publish('should not receive')
self.assertFalse(self.check1.wait(0.25))
self.pubsub_management.activate_subscription(subscription_id)
publisher.publish('should receive')
self.assertTrue(self.check1.wait(2))
self.check1.clear()
self.assertFalse(self.check1.is_set())
self.pubsub_management.deactivate_subscription(subscription_id)
publisher.publish('should not receive')
self.assertFalse(self.check1.wait(0.5))
self.pubsub_management.activate_subscription(subscription_id)
publisher.publish('should receive')
self.assertTrue(self.check1.wait(2))
subscriber.stop()
self.pubsub_management.deactivate_subscription(subscription_id)
self.pubsub_management.delete_subscription(subscription_id)
self.pubsub_management.delete_stream(stream_id)
def test_topic_crud(self):
topic_id = self.pubsub_management.create_topic(name='test_topic', exchange_point='test_xp')
self.exchange_cleanup.append('test_xp')
topic = self.pubsub_management.read_topic(topic_id)
self.assertEquals(topic.name,'test_topic')
self.assertEquals(topic.exchange_point, 'test_xp')
self.pubsub_management.delete_topic(topic_id)
with self.assertRaises(NotFound):
self.pubsub_management.read_topic(topic_id)
def test_full_pubsub(self):
self.sub1_sat = Event()
self.sub2_sat = Event()
def subscriber1(m,r,s):
self.sub1_sat.set()
def subscriber2(m,r,s):
self.sub2_sat.set()
sub1 = StandaloneStreamSubscriber('sub1', subscriber1)
sub1.start()
self.addCleanup(sub1.stop)
sub2 = StandaloneStreamSubscriber('sub2', subscriber2)
sub2.start()
self.addCleanup(sub2.stop)
log_topic = self.pubsub_management.create_topic('instrument_logs', exchange_point='instruments')
self.addCleanup(self.pubsub_management.delete_topic, log_topic)
science_topic = self.pubsub_management.create_topic('science_data', exchange_point='instruments')
self.addCleanup(self.pubsub_management.delete_topic, science_topic)
events_topic = self.pubsub_management.create_topic('notifications', exchange_point='events')
self.addCleanup(self.pubsub_management.delete_topic, events_topic)
log_stream, route = self.pubsub_management.create_stream('instrument1-logs', topic_ids=[log_topic], exchange_point='instruments')
self.addCleanup(self.pubsub_management.delete_stream, log_stream)
ctd_stream, route = self.pubsub_management.create_stream('instrument1-ctd', topic_ids=[science_topic], exchange_point='instruments')
self.addCleanup(self.pubsub_management.delete_stream, ctd_stream)
event_stream, route = self.pubsub_management.create_stream('notifications', topic_ids=[events_topic], exchange_point='events')
self.addCleanup(self.pubsub_management.delete_stream, event_stream)
raw_stream, route = self.pubsub_management.create_stream('temp', exchange_point='global.data')
self.addCleanup(self.pubsub_management.delete_stream, raw_stream)
subscription1 = self.pubsub_management.create_subscription('subscription1', stream_ids=[log_stream,event_stream], exchange_name='sub1')
self.addCleanup(self.pubsub_management.delete_subscription, subscription1)
subscription2 = self.pubsub_management.create_subscription('subscription2', exchange_points=['global.data'], stream_ids=[ctd_stream], exchange_name='sub2')
self.addCleanup(self.pubsub_management.delete_subscription, subscription2)
self.pubsub_management.activate_subscription(subscription1)
self.addCleanup(self.pubsub_management.deactivate_subscription, subscription1)
self.pubsub_management.activate_subscription(subscription2)
self.addCleanup(self.pubsub_management.deactivate_subscription, subscription2)
self.publish_on_stream(log_stream, 1)
self.assertTrue(self.sub1_sat.wait(4))
self.assertFalse(self.sub2_sat.is_set())
self.publish_on_stream(raw_stream,1)
self.assertTrue(self.sub1_sat.wait(4))
def test_topic_craziness(self):
self.msg_queue = Queue()
def subscriber1(m,r,s):
self.msg_queue.put(m)
sub1 = StandaloneStreamSubscriber('sub1', subscriber1)
sub1.start()
self.addCleanup(sub1.stop)
topic1 = self.pubsub_management.create_topic('topic1', exchange_point='xp1')
self.addCleanup(self.pubsub_management.delete_topic, topic1)
topic2 = self.pubsub_management.create_topic('topic2', exchange_point='xp1', parent_topic_id=topic1)
self.addCleanup(self.pubsub_management.delete_topic, topic2)
topic3 = self.pubsub_management.create_topic('topic3', exchange_point='xp1', parent_topic_id=topic1)
self.addCleanup(self.pubsub_management.delete_topic, topic3)
topic4 = self.pubsub_management.create_topic('topic4', exchange_point='xp1', parent_topic_id=topic2)
self.addCleanup(self.pubsub_management.delete_topic, topic4)
topic5 = self.pubsub_management.create_topic('topic5', exchange_point='xp1', parent_topic_id=topic2)
self.addCleanup(self.pubsub_management.delete_topic, topic5)
topic6 = self.pubsub_management.create_topic('topic6', exchange_point='xp1', parent_topic_id=topic3)
self.addCleanup(self.pubsub_management.delete_topic, topic6)
topic7 = self.pubsub_management.create_topic('topic7', exchange_point='xp1', parent_topic_id=topic3)
self.addCleanup(self.pubsub_management.delete_topic, topic7)
# Tree 2
topic8 = self.pubsub_management.create_topic('topic8', exchange_point='xp2')
self.addCleanup(self.pubsub_management.delete_topic, topic8)
topic9 = self.pubsub_management.create_topic('topic9', exchange_point='xp2', parent_topic_id=topic8)
self.addCleanup(self.pubsub_management.delete_topic, topic9)
topic10 = self.pubsub_management.create_topic('topic10', exchange_point='xp2', parent_topic_id=topic9)
self.addCleanup(self.pubsub_management.delete_topic, topic10)
topic11 = self.pubsub_management.create_topic('topic11', exchange_point='xp2', parent_topic_id=topic9)
self.addCleanup(self.pubsub_management.delete_topic, topic11)
topic12 = self.pubsub_management.create_topic('topic12', exchange_point='xp2', parent_topic_id=topic11)
self.addCleanup(self.pubsub_management.delete_topic, topic12)
topic13 = self.pubsub_management.create_topic('topic13', exchange_point='xp2', parent_topic_id=topic11)
self.addCleanup(self.pubsub_management.delete_topic, topic13)
self.exchange_cleanup.extend(['xp1','xp2'])
stream1_id, route = self.pubsub_management.create_stream('stream1', topic_ids=[topic7, topic4, topic5], exchange_point='xp1')
self.addCleanup(self.pubsub_management.delete_stream, stream1_id)
stream2_id, route = self.pubsub_management.create_stream('stream2', topic_ids=[topic8], exchange_point='xp2')
self.addCleanup(self.pubsub_management.delete_stream, stream2_id)
stream3_id, route = self.pubsub_management.create_stream('stream3', topic_ids=[topic10,topic13], exchange_point='xp2')
self.addCleanup(self.pubsub_management.delete_stream, stream3_id)
stream4_id, route = self.pubsub_management.create_stream('stream4', topic_ids=[topic9], exchange_point='xp2')
self.addCleanup(self.pubsub_management.delete_stream, stream4_id)
stream5_id, route = self.pubsub_management.create_stream('stream5', topic_ids=[topic11], exchange_point='xp2')
self.addCleanup(self.pubsub_management.delete_stream, stream5_id)
subscription1 = self.pubsub_management.create_subscription('sub1', topic_ids=[topic1])
self.addCleanup(self.pubsub_management.delete_subscription, subscription1)
subscription2 = self.pubsub_management.create_subscription('sub2', topic_ids=[topic8], exchange_name='sub1')
self.addCleanup(self.pubsub_management.delete_subscription, subscription2)
subscription3 = self.pubsub_management.create_subscription('sub3', topic_ids=[topic9], exchange_name='sub1')
self.addCleanup(self.pubsub_management.delete_subscription, subscription3)
subscription4 = self.pubsub_management.create_subscription('sub4', topic_ids=[topic10,topic13, topic11], exchange_name='sub1')
self.addCleanup(self.pubsub_management.delete_subscription, subscription4)
#--------------------------------------------------------------------------------
self.pubsub_management.activate_subscription(subscription1)
self.publish_on_stream(stream1_id,1)
self.assertEquals(self.msg_queue.get(timeout=10), 1)
with self.assertRaises(Empty):
self.msg_queue.get(timeout=0.1)
self.pubsub_management.deactivate_subscription(subscription1)
#--------------------------------------------------------------------------------
self.pubsub_management.activate_subscription(subscription2)
self.publish_on_stream(stream2_id,2)
self.assertEquals(self.msg_queue.get(timeout=10), 2)
with self.assertRaises(Empty):
self.msg_queue.get(timeout=0.1)
self.pubsub_management.deactivate_subscription(subscription2)
#--------------------------------------------------------------------------------
self.pubsub_management.activate_subscription(subscription3)
self.publish_on_stream(stream2_id, 3)
with self.assertRaises(Empty):
self.msg_queue.get(timeout=0.3)
self.publish_on_stream(stream3_id, 4)
self.assertEquals(self.msg_queue.get(timeout=10),4)
self.pubsub_management.deactivate_subscription(subscription3)
#--------------------------------------------------------------------------------
self.pubsub_management.activate_subscription(subscription4)
self.publish_on_stream(stream4_id, 5)
with self.assertRaises(Empty):
self.msg_queue.get(timeout=0.3)
self.publish_on_stream(stream5_id, 6)
self.assertEquals(self.msg_queue.get(timeout=10),6)
with self.assertRaises(Empty):
self.msg_queue.get(timeout=0.3)
self.pubsub_management.deactivate_subscription(subscription4)
#--------------------------------------------------------------------------------
def cleanup_contexts(self):
for context_id in self.context_ids:
self.dataset_management.delete_parameter_context(context_id)
def add_context_to_cleanup(self, context_id):
self.context_ids.add(context_id)
def _get_pdict(self, filter_values):
t_ctxt = ParameterContext('TIME', param_type=QuantityType(value_encoding=np.dtype('int64')))
t_ctxt.uom = 'seconds since 01-01-1900'
t_ctxt_id = self.dataset_management.create_parameter_context(name='TIME', parameter_context=t_ctxt.dump(), parameter_type='quantity<int64>', units=t_ctxt.uom)
self.add_context_to_cleanup(t_ctxt_id)
lat_ctxt = ParameterContext('LAT', param_type=ConstantType(QuantityType(value_encoding=np.dtype('float32'))), fill_value=-9999)
lat_ctxt.axis = AxisTypeEnum.LAT
lat_ctxt.uom = 'degree_north'
lat_ctxt_id = self.dataset_management.create_parameter_context(name='LAT', parameter_context=lat_ctxt.dump(), parameter_type='quantity<float32>', units=lat_ctxt.uom)
self.add_context_to_cleanup(lat_ctxt_id)
lon_ctxt = ParameterContext('LON', param_type=ConstantType(QuantityType(value_encoding=np.dtype('float32'))), fill_value=-9999)
lon_ctxt.axis = AxisTypeEnum.LON
lon_ctxt.uom = 'degree_east'
lon_ctxt_id = self.dataset_management.create_parameter_context(name='LON', parameter_context=lon_ctxt.dump(), parameter_type='quantity<float32>', units=lon_ctxt.uom)
self.add_context_to_cleanup(lon_ctxt_id)
# Independent Parameters
# Temperature - values expected to be the decimal results of conversion from hex
temp_ctxt = ParameterContext('TEMPWAT_L0', param_type=QuantityType(value_encoding=np.dtype('float32')), fill_value=-9999)
temp_ctxt.uom = 'deg_C'
temp_ctxt_id = self.dataset_management.create_parameter_context(name='TEMPWAT_L0', parameter_context=temp_ctxt.dump(), parameter_type='quantity<float32>', units=temp_ctxt.uom)
self.add_context_to_cleanup(temp_ctxt_id)
# Conductivity - values expected to be the decimal results of conversion from hex
cond_ctxt = ParameterContext('CONDWAT_L0', param_type=QuantityType(value_encoding=np.dtype('float32')), fill_value=-9999)
cond_ctxt.uom = 'S m-1'
cond_ctxt_id = self.dataset_management.create_parameter_context(name='CONDWAT_L0', parameter_context=cond_ctxt.dump(), parameter_type='quantity<float32>', units=cond_ctxt.uom)
self.add_context_to_cleanup(cond_ctxt_id)
# Pressure - values expected to be the decimal results of conversion from hex
press_ctxt = ParameterContext('PRESWAT_L0', param_type=QuantityType(value_encoding=np.dtype('float32')), fill_value=-9999)
press_ctxt.uom = 'dbar'
press_ctxt_id = self.dataset_management.create_parameter_context(name='PRESWAT_L0', parameter_context=press_ctxt.dump(), parameter_type='quantity<float32>', units=press_ctxt.uom)
self.add_context_to_cleanup(press_ctxt_id)
# Dependent Parameters
# TEMPWAT_L1 = (TEMPWAT_L0 / 10000) - 10
tl1_func = '(T / 10000) - 10'
tl1_pmap = {'T': 'TEMPWAT_L0'}
expr = NumexprFunction('TEMPWAT_L1', tl1_func, ['T'], param_map=tl1_pmap)
tempL1_ctxt = ParameterContext('TEMPWAT_L1', param_type=ParameterFunctionType(function=expr), variability=VariabilityEnum.TEMPORAL)
tempL1_ctxt.uom = 'deg_C'
tempL1_ctxt_id = self.dataset_management.create_parameter_context(name=tempL1_ctxt.name, parameter_context=tempL1_ctxt.dump(), parameter_type='pfunc', units=tempL1_ctxt.uom)
self.add_context_to_cleanup(tempL1_ctxt_id)
# CONDWAT_L1 = (CONDWAT_L0 / 100000) - 0.5
cl1_func = '(C / 100000) - 0.5'
cl1_pmap = {'C': 'CONDWAT_L0'}
expr = NumexprFunction('CONDWAT_L1', cl1_func, ['C'], param_map=cl1_pmap)
condL1_ctxt = ParameterContext('CONDWAT_L1', param_type=ParameterFunctionType(function=expr), variability=VariabilityEnum.TEMPORAL)
condL1_ctxt.uom = 'S m-1'
condL1_ctxt_id = self.dataset_management.create_parameter_context(name=condL1_ctxt.name, parameter_context=condL1_ctxt.dump(), parameter_type='pfunc', units=condL1_ctxt.uom)
self.add_context_to_cleanup(condL1_ctxt_id)
# Equation uses p_range, which is a calibration coefficient - Fixing to 679.34040721
# PRESWAT_L1 = (PRESWAT_L0 * p_range / (0.85 * 65536)) - (0.05 * p_range)
pl1_func = '(P * p_range / (0.85 * 65536)) - (0.05 * p_range)'
pl1_pmap = {'P': 'PRESWAT_L0', 'p_range': 679.34040721}
expr = NumexprFunction('PRESWAT_L1', pl1_func, ['P', 'p_range'], param_map=pl1_pmap)
presL1_ctxt = ParameterContext('PRESWAT_L1', param_type=ParameterFunctionType(function=expr), variability=VariabilityEnum.TEMPORAL)
presL1_ctxt.uom = 'S m-1'
presL1_ctxt_id = self.dataset_management.create_parameter_context(name=presL1_ctxt.name, parameter_context=presL1_ctxt.dump(), parameter_type='pfunc', units=presL1_ctxt.uom)
self.add_context_to_cleanup(presL1_ctxt_id)
# Density & practical salinity calucluated using the Gibbs Seawater library - available via python-gsw project:
# https://code.google.com/p/python-gsw/ & http://pypi.python.org/pypi/gsw/3.0.1
# PRACSAL = gsw.SP_from_C((CONDWAT_L1 * 10), TEMPWAT_L1, PRESWAT_L1)
owner = 'gsw'
sal_func = 'SP_from_C'
sal_arglist = ['C', 't', 'p']
sal_pmap = {'C': NumexprFunction('CONDWAT_L1*10', 'C*10', ['C'], param_map={'C': 'CONDWAT_L1'}), 't': 'TEMPWAT_L1', 'p': 'PRESWAT_L1'}
sal_kwargmap = None
expr = PythonFunction('PRACSAL', owner, sal_func, sal_arglist, sal_kwargmap, sal_pmap)
sal_ctxt = ParameterContext('PRACSAL', param_type=ParameterFunctionType(expr), variability=VariabilityEnum.TEMPORAL)
sal_ctxt.uom = 'g kg-1'
sal_ctxt_id = self.dataset_management.create_parameter_context(name=sal_ctxt.name, parameter_context=sal_ctxt.dump(), parameter_type='pfunc', units=sal_ctxt.uom)
self.add_context_to_cleanup(sal_ctxt_id)
# absolute_salinity = gsw.SA_from_SP(PRACSAL, PRESWAT_L1, longitude, latitude)
# conservative_temperature = gsw.CT_from_t(absolute_salinity, TEMPWAT_L1, PRESWAT_L1)
# DENSITY = gsw.rho(absolute_salinity, conservative_temperature, PRESWAT_L1)
owner = 'gsw'
abs_sal_expr = PythonFunction('abs_sal', owner, 'SA_from_SP', ['PRACSAL', 'PRESWAT_L1', 'LON','LAT'])
cons_temp_expr = PythonFunction('cons_temp', owner, 'CT_from_t', [abs_sal_expr, 'TEMPWAT_L1', 'PRESWAT_L1'])
dens_expr = PythonFunction('DENSITY', owner, 'rho', [abs_sal_expr, cons_temp_expr, 'PRESWAT_L1'])
dens_ctxt = ParameterContext('DENSITY', param_type=ParameterFunctionType(dens_expr), variability=VariabilityEnum.TEMPORAL)
dens_ctxt.uom = 'kg m-3'
dens_ctxt_id = self.dataset_management.create_parameter_context(name=dens_ctxt.name, parameter_context=dens_ctxt.dump(), parameter_type='pfunc', units=dens_ctxt.uom)
self.add_context_to_cleanup(dens_ctxt_id)
ids = [t_ctxt_id, lat_ctxt_id, lon_ctxt_id, temp_ctxt_id, cond_ctxt_id, press_ctxt_id, tempL1_ctxt_id, condL1_ctxt_id, presL1_ctxt_id, sal_ctxt_id, dens_ctxt_id]
contexts = [t_ctxt, lat_ctxt, lon_ctxt, temp_ctxt, cond_ctxt, press_ctxt, tempL1_ctxt, condL1_ctxt, presL1_ctxt, sal_ctxt, dens_ctxt]
context_ids = [ids[i] for i,ctxt in enumerate(contexts) if ctxt.name in filter_values]
pdict_name = '_'.join([ctxt.name for ctxt in contexts if ctxt.name in filter_values])
try:
self.pdicts[pdict_name]
return self.pdicts[pdict_name]
except KeyError:
pdict_id = self.dataset_management.create_parameter_dictionary(pdict_name, parameter_context_ids=context_ids, temporal_context='time')
self.addCleanup(self.dataset_management.delete_parameter_dictionary, pdict_id)
self.pdicts[pdict_name] = pdict_id
return pdict_id
class TestTransformWorker(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dataset_management_client = DatasetManagementServiceClient(node=self.container.node)
self.pubsub_client = PubsubManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.time_dom, self.spatial_dom = time_series_domain()
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_transform_worker(self):
self.loggerpids = []
self.data_process_objs = []
self._output_stream_ids = []
self.start_transform_worker()
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition, self.stream_def_id)
# create the DataProduct
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product', description='input test stream',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
#retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
#create a queue to catch the published granules
self.subscription_id = self.pubsub_client.create_subscription(name='parsed_subscription', stream_ids=[self.stream_id], exchange_name='parsed_subscription')
self.addCleanup(self.pubsub_client.delete_subscription, self.subscription_id)
self.pubsub_client.activate_subscription(self.subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, self.subscription_id)
stream_route = self.pubsub_client.read_stream_route(self.stream_id)
self.publisher = StandaloneStreamPublisher(stream_id=self.stream_id, stream_route=stream_route )
self.start_event_listener()
self.dp_list = self.create_data_processes()
self.data_modified = Event()
self.data_modified.wait(5)
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher.publish(rdt.to_granule())
self.data_modified.wait(5)
# Cleanup processes
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
def create_data_processes(self):
#two data processes using one transform and one DPD
dp1_func_output_dp_id, dp2_func_output_dp_id = self.create_output_data_products()
configuration = { 'argument_map':{'arr1':'conductivity', 'arr2':'pressure'}, 'output_param' : 'salinity' }
# Set up DPD and DP #2 - array add function
tf_obj = IonObject(RT.TransformFunction,
name='add_array_func',
description='adds values in an array',
function='add_arrays',
module="ion_example.add_arrays",
arguments=['arr1', 'arr2'],
function_type=TransformFunctionType.TRANSFORM
)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(RT.DataProcessDefinition,
name='add_arrays',
description='adds the values of two arrays',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS,
)
self.add_array_dpd_id = self.dataprocessclient.create_data_process_definition_new(data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(self.stream_def_id, self.add_array_dpd_id, binding='add_array_func' )
# Create the data process
dp1_data_process_id = self.dataprocessclient.create_data_process_new(data_process_definition_id=self.add_array_dpd_id, in_data_product_ids=[self.input_dp_id],
out_data_product_ids=[dp1_func_output_dp_id], configuration=configuration)
# Create the data process
dp2_func_data_process_id = self.dataprocessclient.create_data_process_new(data_process_definition_id=self.add_array_dpd_id, in_data_product_ids=[self.input_dp_id],
out_data_product_ids=[dp2_func_output_dp_id], configuration=configuration)
return [dp1_data_process_id, dp2_func_data_process_id]
def create_output_data_products(self):
dp1_outgoing_stream_id = self.pubsub_client.create_stream_definition(name='dp1_stream', parameter_dictionary_id=self.parameter_dict_id)
dp1_output_dp_obj = IonObject( RT.DataProduct,
name='data_process1_data_product',
description='output of add array func',
temporal_domain = self.time_dom.dump(),
spatial_domain = self.spatial_dom.dump())
dp1_func_output_dp_id = self.dataproductclient.create_data_product(dp1_output_dp_obj, dp1_outgoing_stream_id)
self.addCleanup(self.dataproductclient.delete_data_product, dp1_func_output_dp_id)
# Retrieve the id of the OUTPUT stream from the out Data Product and add to granule logger
stream_ids, _ = self.rrclient.find_objects(dp1_func_output_dp_id, PRED.hasStream, None, True)
self._output_stream_ids.append(stream_ids[0])
dp2_func_outgoing_stream_id = self.pubsub_client.create_stream_definition(name='dp2_stream', parameter_dictionary_id=self.parameter_dict_id)
dp2_func_output_dp_obj = IonObject( RT.DataProduct,
name='data_process2_data_product',
description='output of add array func',
temporal_domain = self.time_dom.dump(),
spatial_domain = self.spatial_dom.dump())
dp2_func_output_dp_id = self.dataproductclient.create_data_product(dp2_func_output_dp_obj, dp2_func_outgoing_stream_id)
self.addCleanup(self.dataproductclient.delete_data_product, dp2_func_output_dp_id)
# Retrieve the id of the OUTPUT stream from the out Data Product and add to granule logger
stream_ids, _ = self.rrclient.find_objects(dp2_func_output_dp_id, PRED.hasStream, None, True)
self._output_stream_ids.append(stream_ids[0])
subscription_id = self.pubsub_client.create_subscription('validator', data_product_ids=[dp1_func_output_dp_id, dp2_func_output_dp_id])
self.addCleanup(self.pubsub_client.delete_subscription, subscription_id)
def on_granule(msg, route, stream_id):
log.debug('recv_packet stream_id: %s route: %s msg: %s', stream_id, route, msg)
self.validate_output_granule(msg, route, stream_id)
validator = StandaloneStreamSubscriber('validator', callback=on_granule)
validator.start()
self.addCleanup(validator.stop)
self.pubsub_client.activate_subscription(subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, subscription_id)
return dp1_func_output_dp_id, dp2_func_output_dp_id
def validate_event(self, *args, **kwargs):
"""
This method is a callback function for receiving DataProcessStatusEvent.
"""
data_process_event = args[0]
log.debug("DataProcessStatusEvent: %s" , str(data_process_event.__dict__))
self.assertTrue( data_process_event.origin in self.dp_list)
def validate_output_granule(self, msg, route, stream_id):
self.assertTrue( stream_id in self._output_stream_ids)
rdt = RecordDictionaryTool.load_from_granule(msg)
log.debug('validate_output_granule rdt: %s', rdt)
sal_val = rdt['salinity']
#self.assertTrue( sal_val == 3)
np.testing.assert_array_equal(sal_val, np.array([3]))
def start_event_listener(self):
es = EventSubscriber(event_type=OT.DataProcessStatusEvent, callback=self.validate_event)
es.start()
self.addCleanup(es.stop)
def start_transform_worker(self):
config = DotDict()
config.process.queue_name = 'parsed_subscription'
self.container.spawn_process(
name='transform_worker',
module='ion.processes.data.transforms.transform_worker',
cls='TransformWorker',
config=config
)
def test_download(self):
egg_url = 'http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
egg_path = TransformWorker.download_egg(egg_url)
import pkg_resources
pkg_resources.working_set.add_entry(egg_path)
from ion_example.add_arrays import add_arrays
a = add_arrays(1,2)
self.assertEquals(a,3)
class TestGranulePublish(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.pubsubclient = PubsubManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
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.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
#overriding trigger function here to use new granule
def test_granule_publish(self):
log.debug("test_granule_publish ")
self.loggerpids = []
#retrieve the param dict from the repository
pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
stream_definition_id = self.pubsubclient.create_stream_definition(
'parsed stream', parameter_dictionary_id=pdict_id)
tdom, sdom = time_series_domain()
dp_obj = IonObject(RT.DataProduct,
name=str(uuid.uuid4()),
description='ctd stream test',
temporal_domain=tdom.dump(),
spatial_domain=sdom.dump())
data_product_id1 = self.dpclient.create_data_product(
data_product=dp_obj, stream_definition_id=stream_definition_id)
# Retrieve the id of the output stream of the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id1,
PRED.hasStream, None, True)
log.debug('test_granule_publish: Data product streams1 = %s',
stream_ids)
pid = self.create_logger('ctd_parsed', stream_ids[0])
self.loggerpids.append(pid)
rdt = RecordDictionaryTool(stream_definition_id=stream_definition_id)
#create the publisher from the stream route
stream_route = self.pubsubclient.read_stream_route(stream_ids[0])
publisher = StandaloneStreamPublisher(stream_ids[0], stream_route)
# this is one sample from the ctd driver
tomato = {
"driver_timestamp":
3555971105.1268806,
"instrument_id":
"ABC-123",
"pkt_format_id":
"JSON_Data",
"pkt_version":
1,
"preferred_timestamp":
"driver_timestamp",
"quality_flag":
"ok",
"stream_name":
"parsed",
"values": [{
"value": 22.9304,
"value_id": "temp"
}, {
"value": 51.57381,
"value_id": "conductivity"
}, {
"value": 915.551,
"value_id": "pressure"
}]
}
for value in tomato['values']:
log.debug(
"test_granule_publish: Looping tomato values key: %s val: %s ",
str(value['value']), str(value['value_id']))
if value['value_id'] in rdt:
rdt[value['value_id']] = numpy.array([value['value']])
log.debug(
"test_granule_publish: Added data item %s val: %s ",
str(value['value']), str(value['value_id']))
g = rdt.to_granule()
publisher.publish(g)
gevent.sleep(3)
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
#--------------------------------------------------------------------------------
# Cleanup data products
#--------------------------------------------------------------------------------
dp_ids, _ = self.rrclient.find_resources(restype=RT.DataProduct,
id_only=True)
for dp_id in dp_ids:
self.dataproductclient.delete_data_product(dp_id)
class TestTransformWorkerSubscriptions(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dataset_management_client = DatasetManagementServiceClient(node=self.container.node)
self.pubsub_client = PubsubManagementServiceClient(node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.time_dom, self.spatial_dom = time_series_domain()
self.wait_time = CFG.get_safe('endpoint.receive.timeout', 10)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_multi_subscriptions(self):
self.dp_list = []
self.event1_verified = Event()
self.event2_verified = Event()
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition, self.stream_def_id)
# create the DataProduct
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product_one', description='input test stream one',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_one_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product_two', description='input test stream two',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_two_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
#retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(self.input_dp_one_id, PRED.hasStream, RT.Stream, True)
self.stream_one_id = stream_ids[0]
stream_ids, assoc_ids = self.rrclient.find_objects(self.input_dp_two_id, PRED.hasStream, RT.Stream, True)
self.stream_two_id = stream_ids[0]
dpd_id = self.create_data_process_definition()
dp1_func_output_dp_id, dp2_func_output_dp_id = self.create_output_data_products()
first_dp_id = self.create_data_process_one(dpd_id, dp1_func_output_dp_id)
second_dp_id = self.create_data_process_two(dpd_id, self.input_dp_two_id, dp2_func_output_dp_id)
#retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(subject=first_dp_id, predicate=PRED.hasSubscription, object_type=RT.Subscription, id_only=False)
log.debug('test_transform_worker subscription_obj: %s', subscription_objs[0])
#create subscription to stream ONE, create data process and publish granule on stream ONE
#create a queue to catch the published granules of stream ONE
self.subscription_one_id = self.pubsub_client.create_subscription(name='parsed_subscription_one', stream_ids=[self.stream_one_id], exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription, self.subscription_one_id)
self.pubsub_client.activate_subscription(self.subscription_one_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, self.subscription_one_id)
stream_route_one = self.pubsub_client.read_stream_route(self.stream_one_id)
self.publisher_one = StandaloneStreamPublisher(stream_id=self.stream_one_id, stream_route=stream_route_one )
self.start_event_listener()
#data process 1 adds conductivity + pressure and puts the result in salinity
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher_one.publish(msg=rdt.to_granule(), stream_id=self.stream_one_id)
#retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(subject=second_dp_id, predicate=PRED.hasSubscription, object_type=RT.Subscription, id_only=False)
log.debug('test_transform_worker subscription_obj: %s', subscription_objs[0])
#create subscription to stream ONE and TWO, move TW subscription, create data process and publish granule on stream TWO
#create a queue to catch the published granules of stream TWO
self.subscription_two_id = self.pubsub_client.create_subscription(name='parsed_subscription_one_two', stream_ids=[self.stream_two_id], exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription, self.subscription_two_id)
self.pubsub_client.activate_subscription(self.subscription_two_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, self.subscription_two_id)
stream_route_two = self.pubsub_client.read_stream_route(self.stream_two_id)
self.publisher_two = StandaloneStreamPublisher(stream_id=self.stream_two_id, stream_route=stream_route_two )
#data process 1 adds conductivity + pressure and puts the result in salinity
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher_one.publish(msg=rdt.to_granule(), stream_id=self.stream_one_id)
#data process 2 adds salinity + pressure and puts the result in conductivity
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [22]
rdt['pressure'] = [4]
rdt['salinity'] = [1]
self.publisher_two.publish(msg=rdt.to_granule(), stream_id=self.stream_two_id)
self.assertTrue(self.event2_verified.wait(self.wait_time))
self.assertTrue(self.event1_verified.wait(self.wait_time))
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False), 'Skip test while in CEI LAUNCH mode')
def test_two_transforms_inline(self):
self.dp_list = []
self.event1_verified = Event()
self.event2_verified = Event()
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition, self.stream_def_id)
# create the DataProduct
input_dp_obj = IonObject( RT.DataProduct, name='input_data_product_one', description='input test stream one',
temporal_domain = self.time_dom.dump(), spatial_domain = self.spatial_dom.dump())
self.input_dp_one_id = self.dataproductclient.create_data_product(data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
dpd_id = self.create_data_process_definition()
dp1_func_output_dp_id, dp2_func_output_dp_id = self.create_output_data_products()
first_dp_id = self.create_data_process_one(dpd_id, dp1_func_output_dp_id)
second_dp_id = self.create_data_process_two(dpd_id, dp1_func_output_dp_id, dp2_func_output_dp_id)
#retrieve subscription from data process one
subscription_objs, _ = self.rrclient.find_objects(subject=first_dp_id, predicate=PRED.hasSubscription, object_type=RT.Subscription, id_only=False)
log.debug('test_transform_worker subscription_obj: %s', subscription_objs[0])
#retrieve the Stream for these data product
stream_ids, assoc_ids = self.rrclient.find_objects(self.input_dp_one_id, PRED.hasStream, RT.Stream, True)
self.stream_one_id = stream_ids[0]
#the input to data process two is the output from data process one
stream_ids, assoc_ids = self.rrclient.find_objects(dp1_func_output_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_two_id = stream_ids[0]
# Run provenance on the output dataproduct of the second data process to see all the links
# are as expected
output_data_product_provenance = self.dataproductclient.get_data_product_provenance(dp2_func_output_dp_id)
# Do a basic check to see if there were 2 entries in the provenance graph. Parent and Child.
self.assertTrue(len(output_data_product_provenance) == 3)
# confirm that the linking from the output dataproduct to input dataproduct is correct
self.assertTrue(dp1_func_output_dp_id in output_data_product_provenance[dp2_func_output_dp_id]['parents'])
self.assertTrue(self.input_dp_one_id in output_data_product_provenance[dp1_func_output_dp_id]['parents'])
#create subscription to stream ONE, create data process and publish granule on stream ONE
#create a queue to catch the published granules of stream ONE
subscription_id = self.pubsub_client.create_subscription(name='parsed_subscription', stream_ids=[self.stream_one_id, self.stream_two_id], exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription, subscription_id)
self.pubsub_client.activate_subscription(subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, subscription_id)
stream_route_one = self.pubsub_client.read_stream_route(self.stream_one_id)
self.publisher_one = StandaloneStreamPublisher(stream_id=self.stream_one_id, stream_route=stream_route_one )
#retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(subject=second_dp_id, predicate=PRED.hasSubscription, object_type=RT.Subscription, id_only=False)
log.debug('test_transform_worker subscription_obj: %s', subscription_objs[0])
#data process 1 adds conductivity + pressure and puts the result in salinity
#data process 2 adds salinity + pressure and puts the result in conductivity
self.start_event_listener()
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher_one.publish(msg=rdt.to_granule(), stream_id=self.stream_one_id)
self.assertTrue(self.event2_verified.wait(self.wait_time))
self.assertTrue(self.event1_verified.wait(self.wait_time))
def create_data_process_definition(self):
#two data processes using one transform and one DPD
# Set up DPD and DP #2 - array add function
tf_obj = IonObject(RT.TransformFunction,
name='add_array_func',
description='adds values in an array',
function='add_arrays',
module="ion_example.add_arrays",
arguments=['arr1', 'arr2'],
function_type=TransformFunctionType.TRANSFORM,
uri='http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(RT.DataProcessDefinition,
name='add_arrays',
description='adds the values of two arrays',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS,
)
add_array_dpd_id = self.dataprocessclient.create_data_process_definition(data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(self.stream_def_id, add_array_dpd_id, binding='add_array_func' )
return add_array_dpd_id
def create_data_process_one(self, data_process_definition_id, output_dataproduct):
# Create the data process
#data process 1 adds conductivity + pressure and puts the result in salinity
argument_map = {"arr1":"conductivity", "arr2":"pressure"}
output_param = "salinity"
dp1_data_process_id = self.dataprocessclient.create_data_process(
data_process_definition_id=data_process_definition_id,
inputs=[self.input_dp_one_id],
outputs=[output_dataproduct],
argument_map=argument_map,
out_param_name=output_param)
self.damsclient.register_process(dp1_data_process_id)
self.addCleanup(self.dataprocessclient.delete_data_process, dp1_data_process_id)
self.dp_list.append(dp1_data_process_id)
return dp1_data_process_id
def create_data_process_two(self, data_process_definition_id, input_dataproduct, output_dataproduct):
# Create the data process
#data process 2 adds salinity + pressure and puts the result in conductivity
argument_map = {'arr1':'salinity', 'arr2':'pressure'}
output_param = 'conductivity'
dp2_func_data_process_id = self.dataprocessclient.create_data_process(
data_process_definition_id=data_process_definition_id,
inputs=[input_dataproduct],
outputs=[output_dataproduct],
argument_map=argument_map,
out_param_name=output_param)
self.damsclient.register_process(dp2_func_data_process_id)
self.addCleanup(self.dataprocessclient.delete_data_process, dp2_func_data_process_id)
self.dp_list.append(dp2_func_data_process_id)
return dp2_func_data_process_id
def create_output_data_products(self):
dp1_outgoing_stream_id = self.pubsub_client.create_stream_definition(name='dp1_stream', parameter_dictionary_id=self.parameter_dict_id)
dp1_output_dp_obj = IonObject( RT.DataProduct,
name='data_process1_data_product',
description='output of add array func',
temporal_domain = self.time_dom.dump(),
spatial_domain = self.spatial_dom.dump())
dp1_func_output_dp_id = self.dataproductclient.create_data_product(dp1_output_dp_obj, dp1_outgoing_stream_id)
self.addCleanup(self.dataproductclient.delete_data_product, dp1_func_output_dp_id)
# Retrieve the id of the OUTPUT stream from the out Data Product and add to granule logger
stream_ids, _ = self.rrclient.find_objects(dp1_func_output_dp_id, PRED.hasStream, None, True)
self._output_stream_one_id = stream_ids[0]
dp2_func_outgoing_stream_id = self.pubsub_client.create_stream_definition(name='dp2_stream', parameter_dictionary_id=self.parameter_dict_id)
dp2_func_output_dp_obj = IonObject( RT.DataProduct,
name='data_process2_data_product',
description='output of add array func',
temporal_domain = self.time_dom.dump(),
spatial_domain = self.spatial_dom.dump())
dp2_func_output_dp_id = self.dataproductclient.create_data_product(dp2_func_output_dp_obj, dp2_func_outgoing_stream_id)
self.addCleanup(self.dataproductclient.delete_data_product, dp2_func_output_dp_id)
# Retrieve the id of the OUTPUT stream from the out Data Product and add to granule logger
stream_ids, _ = self.rrclient.find_objects(dp2_func_output_dp_id, PRED.hasStream, None, True)
self._output_stream_two_id = stream_ids[0]
subscription_id = self.pubsub_client.create_subscription('validator', data_product_ids=[dp1_func_output_dp_id, dp2_func_output_dp_id])
self.addCleanup(self.pubsub_client.delete_subscription, subscription_id)
def on_granule(msg, route, stream_id):
log.debug('recv_packet stream_id: %s route: %s msg: %s', stream_id, route, msg)
self.validate_output_granule(msg, route, stream_id)
validator = StandaloneStreamSubscriber('validator', callback=on_granule)
validator.start()
self.addCleanup(validator.stop)
self.pubsub_client.activate_subscription(subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription, subscription_id)
return dp1_func_output_dp_id, dp2_func_output_dp_id
def validate_event(self, *args, **kwargs):
"""
This method is a callback function for receiving DataProcessStatusEvent.
"""
data_process_event = args[0]
log.debug("DataProcessStatusEvent: %s" , str(data_process_event.__dict__))
#if data process already created, check origin
if not 'data process assigned to transform worker' in data_process_event.description:
self.assertIn( data_process_event.origin, self.dp_list)
def validate_output_granule(self, msg, route, stream_id):
self.assertTrue( stream_id in [self._output_stream_one_id, self._output_stream_two_id])
rdt = RecordDictionaryTool.load_from_granule(msg)
log.debug('validate_output_granule stream_id: %s', stream_id)
if stream_id == self._output_stream_one_id:
sal_val = rdt['salinity']
log.debug('validate_output_granule sal_val: %s', sal_val)
np.testing.assert_array_equal(sal_val, np.array([3]))
self.event1_verified.set()
else:
cond_val = rdt['conductivity']
log.debug('validate_output_granule cond_val: %s', cond_val)
np.testing.assert_array_equal(cond_val, np.array([5]))
self.event2_verified.set()
def start_event_listener(self):
es = EventSubscriber(event_type=OT.DataProcessStatusEvent, callback=self.validate_event)
es.start()
self.addCleanup(es.stop)
class ExternalDatasetAgentTestBase(object):
# Agent parameters.
EDA_RESOURCE_ID = '123xyz'
EDA_NAME = 'ExampleEDA'
EDA_MOD = 'ion.agents.data.external_dataset_agent'
EDA_CLS = 'ExternalDatasetAgent'
"""
Test cases for instrument agent class. Functions in this class provide
instrument agent integration tests and provide a tutorial on use of
the agent setup and interface.
"""
def setUp(self):
"""
Initialize test members.
"""
#log.warn('Starting the container')
# Start container.
self._start_container()
# Bring up services in a deploy file
#log.warn('Starting the rel')
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
# Create a pubsub client to create streams.
# log.warn('Init a pubsub client')
self._pubsub_client = PubsubManagementServiceClient(node=self.container.node)
# log.warn('Init a ContainerAgentClient')
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)
# TODO: Finish dealing with the resources and whatnot
# TODO: DVR_CONFIG and (potentially) stream_config could both be reconfigured in self._setup_resources()
self._setup_resources()
#TG: Setup/configure the granule logger to log granules as they're published
# Create agent config.
agent_config = {
'driver_config': self.DVR_CONFIG,
'stream_config': {},
'agent': {'resource_id': self.EDA_RESOURCE_ID},
'test_mode': True
}
# Start instrument agent.
self._ia_pid = None
log.debug('TestInstrumentAgent.setup(): starting EDA.')
self._ia_pid = self._container_client.spawn_process(
name=self.EDA_NAME,
module=self.EDA_MOD,
cls=self.EDA_CLS,
config=agent_config
)
log.info('Agent pid=%s.', str(self._ia_pid))
# Start a resource agent client to talk with the instrument agent.
self._ia_client = None
self._ia_client = ResourceAgentClient(self.EDA_RESOURCE_ID, process=FakeProcess())
log.info('Got ia client %s.', str(self._ia_client))
########################################
# Private "setup" functions
########################################
def _setup_resources(self):
raise NotImplementedError('_setup_resources must be implemented in the subclass')
def create_stream_and_logger(self, name, stream_id='', pdict=None):
stream_def_id = ''
if not stream_id or stream_id is '':
if pdict:
stream_def_id = self._pubsub_client.create_stream_definition(parameter_dictionary=pdict.dump(), stream_type='stream')
stream_id, route = self._pubsub_client.create_stream(name=name, exchange_point='science_data', stream_definition_id=stream_def_id)
else:
route = self._pubsub_client.read_stream_route(stream_id=stream_id)
stream_def = self._pubsub_client.read_stream_definition(stream_id=stream_id)
stream_def_id = stream_def._id
pid = self._container_client.spawn_process(
name=name + '_logger',
module='ion.processes.data.stream_granule_logger',
cls='StreamGranuleLogger',
config={'process': {'stream_id': stream_id}}
)
log.info('Started StreamGranuleLogger \'{0}\' subscribed to stream_id={1}'.format(pid, stream_id))
return stream_id, route, stream_def_id
def _start_finished_event_subscriber(self):
def consume_event(*args, **kwargs):
if args[0].description == 'TestingFinished':
log.debug('TestingFinished event received')
self._finished_events_received.append(args[0])
if self._finished_count and self._finished_count == len(self._finished_events_received):
log.debug('Finishing test...')
self._async_finished_result.set(len(self._finished_events_received))
log.debug('Called self._async_finished_result.set({0})'.format(len(self._finished_events_received)))
self._finished_event_subscriber = EventSubscriber(event_type='DeviceEvent', callback=consume_event)
self._finished_event_subscriber.start()
def _stop_finished_event_subscriber(self):
if self._finished_event_subscriber:
self._finished_event_subscriber.stop()
self._finished_event_subscriber = None
########################################
# Custom assertion functions
########################################
def assertListsEqual(self, lst1, lst2):
lst1.sort()
lst2.sort()
return lst1 == lst2
def assertSampleDict(self, val):
"""
Verify the value is a sample dictionary for the sbe37.
"""
#{'p': [-6.945], 'c': [0.08707], 't': [20.002], 'time': [1333752198.450622]}
self.assertTrue(isinstance(val, dict))
self.assertTrue('c' in val)
self.assertTrue('t' in val)
self.assertTrue('p' in val)
self.assertTrue('time' in val)
c = val['c'][0]
t = val['t'][0]
p = val['p'][0]
time = val['time'][0]
self.assertTrue(isinstance(c, float))
self.assertTrue(isinstance(t, float))
self.assertTrue(isinstance(p, float))
self.assertTrue(isinstance(time, float))
def assertParamDict(self, pd, all_params=False):
"""
Verify all device parameters exist and are correct type.
"""
if all_params:
self.assertEqual(set(pd.keys()), set(PARAMS.keys()))
for (key, type_val) in PARAMS.iteritems():
if type_val == list or type_val == tuple:
self.assertTrue(isinstance(pd[key], (list, tuple)))
else:
self.assertTrue(isinstance(pd[key], type_val))
else:
for (key, val) in pd.iteritems():
self.assertTrue(key in PARAMS)
self.assertTrue(isinstance(val, PARAMS[key]))
def assertParamVals(self, params, correct_params):
"""
Verify parameters take the correct values.
"""
self.assertEqual(set(params.keys()), set(correct_params.keys()))
for (key, val) in params.iteritems():
correct_val = correct_params[key]
if isinstance(val, float):
# Verify to 5% of the larger value.
max_val = max(abs(val), abs(correct_val))
self.assertAlmostEqual(val, correct_val, delta=max_val * .01)
elif isinstance(val, (list, tuple)):
# list of tuple.
self.assertEqual(list(val), list(correct_val))
else:
# int, bool, str.
self.assertEqual(val, correct_val)
########################################
# Test functions
########################################
def test_acquire_data_while_streaming(self):
# Test instrument driver execute interface to start and stop streaming mode.
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
params = {
'POLLING_INTERVAL': 3
}
self._ia_client.set_resource(params)
self._finished_count = 1
cmd = AgentCommand(command=DriverEvent.START_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.STREAMING)
config = get_safe(self.DVR_CONFIG, 'dh_cfg', {})
log.info('Send a constrained request for data: constraints = HIST_CONSTRAINTS_1')
config['stream_id'], config['stream_route'], _ = self.create_stream_and_logger(name='stream_id_for_historical_1')
config['constraints'] = self.HIST_CONSTRAINTS_1
cmd = AgentCommand(command=DriverEvent.ACQUIRE_SAMPLE, args=[config])
self._ia_client.execute_resource(cmd)
cmd = AgentCommand(command=DriverEvent.STOP_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
finished = self._async_finished_result.get(timeout=120)
self.assertEqual(finished, self._finished_count)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
def test_acquire_data(self):
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
log.warn('Send an unconstrained request for data (\'new data\')')
cmd = AgentCommand(command=DriverEvent.ACQUIRE_SAMPLE)
self._ia_client.execute_resource(command=cmd)
state = self._ia_client.get_agent_state()
log.info(state)
self.assertEqual(state, ResourceAgentState.COMMAND)
self._finished_count = 2
config_mods = {}
log.info('Send a constrained request for data: constraints = HIST_CONSTRAINTS_1')
config_mods['stream_id'], config_mods['stream_route'], _ = self.create_stream_and_logger(name='stream_id_for_historical_1')
config_mods['constraints'] = self.HIST_CONSTRAINTS_1
cmd = AgentCommand(command=DriverEvent.ACQUIRE_SAMPLE, args=[config_mods])
self._ia_client.execute_resource(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
log.info('Send a second constrained request for data: constraints = HIST_CONSTRAINTS_2')
config_mods['stream_id'], config_mods['stream_route'], _ = self.create_stream_and_logger(name='stream_id_for_historical_2')
config_mods['constraints'] = self.HIST_CONSTRAINTS_2
cmd = AgentCommand(command=DriverEvent.ACQUIRE_SAMPLE, args=[config_mods])
self._ia_client.execute_resource(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
finished = self._async_finished_result.get(timeout=120)
self.assertEqual(finished, self._finished_count)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
def test_streaming(self):
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
params = {
'POLLING_INTERVAL': 3
}
self._ia_client.set_resource(params)
self._finished_count = 3
cmd = AgentCommand(command=DriverEvent.START_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.STREAMING)
#Assert that data was received
# self._async_finished_result.get(timeout=600)
# self.assertTrue(len(self._finished_events_received) >= 3)
cmd = AgentCommand(command=DriverEvent.STOP_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
def test_command(self):
# Test instrument driver get and set interface.
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
# Retrieve all resource parameters.
reply = self._ia_client.get_resource(params=['DRIVER_PARAMETER_ALL'])
self.assertParamDict(reply, True)
## Retrieve a subset of resource parameters.
params = [
'POLLING_INTERVAL'
]
reply = self._ia_client.get_resource(params=params)
self.assertParamDict(reply)
orig_params = reply
# Set a subset of resource parameters.
new_params = {
'POLLING_INTERVAL': (orig_params['POLLING_INTERVAL'] * 2),
}
self._ia_client.set_resource(params=new_params)
check_new_params = self._ia_client.get_resource(params)
self.assertParamVals(check_new_params, new_params)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
def test_get_set_resource(self):
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
# Get a couple parameters
retval = self._ia_client.get_resource(['POLLING_INTERVAL', 'PATCHABLE_CONFIG_KEYS'])
log.debug('Retrieved parameters from agent: {0}'.format(retval))
self.assertTrue(isinstance(retval, dict))
self.assertEqual(type(retval['POLLING_INTERVAL']), int)
self.assertEqual(type(retval['PATCHABLE_CONFIG_KEYS']), list)
# Attempt to get a parameter that doesn't exist
log.debug('Try getting a non-existent parameter \'BAD_PARAM\'')
with self.assertRaises(ServerError):
self._ia_client.get_resource(['BAD_PARAM'])
# Set the polling_interval to a new value, then get it to make sure it set properly
self._ia_client.set_resource({'POLLING_INTERVAL': 10})
retval = self._ia_client.get_resource(['POLLING_INTERVAL'])
log.debug('Retrieved parameters from agent: {0}'.format(retval))
self.assertTrue(isinstance(retval, dict))
self.assertEqual(retval['POLLING_INTERVAL'], 10)
# Attempt to set a parameter that doesn't exist
log.debug('Try setting a non-existent parameter \'BAD_PARAM\'')
with self.assertRaises(ServerError):
self._ia_client.set_resource({'BAD_PARAM': 'bad_val'})
# Attempt to set one parameter that does exist, and one that doesn't
with self.assertRaises(ServerError):
self._ia_client.set_resource({'POLLING_INTERVAL': 20, 'BAD_PARAM': 'bad_val'})
retval = self._ia_client.get_resource(['POLLING_INTERVAL'])
log.debug('Retrieved parameters from agent: {0}'.format(retval))
self.assertTrue(isinstance(retval, dict))
self.assertEqual(retval['POLLING_INTERVAL'], 20)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
def test_initialize(self):
# Test agent initialize command. This causes creation of driver process and transition to inactive.
# We start in uninitialized state.
# In this state there is no driver process.
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
# Initialize the agent.
# The agent is spawned with a driver config, but you can pass one in
# optinally with the initialize command. This validates the driver
# config, launches a driver process and connects to it via messaging.
# If successful, we switch to the inactive state.
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
# Reset the agent. This causes the driver messaging to be stopped,
# the driver process to end and switches us back to uninitialized.
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
def test_states(self):
# Test agent state transitions.
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.PAUSE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.STOPPED)
cmd = AgentCommand(command=ResourceAgentEvent.RESUME)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.CLEAR)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.PAUSE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.STOPPED)
cmd = AgentCommand(command=ResourceAgentEvent.CLEAR)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=DriverEvent.START_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.STREAMING)
cmd = AgentCommand(command=DriverEvent.STOP_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
def test_capabilities(self):
"""
Test the ability to retrieve agent and resource parameter and command
capabilities in various system states.
"""
# Test the ability to retrieve agent and resource parameter and command capabilities.
acmds = self._ia_client.get_capabilities(['AGT_CMD'])
log.debug('Agent Commands: {0}'.format(acmds))
# acmds = [item[1] for item in acmds]
self.assertListsEqual(acmds, AGT_CMDS.keys())
apars = self._ia_client.get_capabilities(['AGT_PAR'])
log.debug('Agent Parameters: {0}'.format(apars))
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
rcmds = self._ia_client.get_capabilities(['RES_CMD'])
log.debug('Resource Commands: {0}'.format(rcmds))
# rcmds = [item[1] for item in rcmds]
self.assertListsEqual(rcmds, CMDS.keys())
rpars = self._ia_client.get_capabilities(['RES_PAR'])
log.debug('Resource Parameters: {0}'.format(rpars))
# rpars = [item[1] for item in rpars]
self.assertListsEqual(rpars, PARAMS.keys())
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
def test_errors(self):
# Test illegal behavior and replies.
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
# Can't go active in unitialized state.
# Status 660 is state error.
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
with self.assertRaises(Conflict):
self._ia_client.execute_agent(cmd)
# Can't command driver in this state.
cmd = AgentCommand(command=DriverEvent.ACQUIRE_SAMPLE)
with self.assertRaises(Conflict):
self._ia_client.execute_resource(cmd)
#self.assertEqual(reply.status, 660)
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.INACTIVE)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.IDLE)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.COMMAND)
# 404 unknown agent command.
cmd = AgentCommand(command='kiss_edward')
with self.assertRaises(BadRequest):
self._ia_client.execute_agent(cmd)
# 670 unknown driver command.
cmd = AgentCommand(command='acquire_sample_please')
with self.assertRaises(ServerError):
self._ia_client.execute_resource(cmd)
# 630 Parameter error.
#self.assertRaises(InstParameterError, self._ia_client.get_param, 'bogus bogus')
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
state = self._ia_client.get_agent_state()
self.assertEqual(state, ResourceAgentState.UNINITIALIZED)
class TestGranulePublish(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.pubsubclient = PubsubManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(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.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
#overriding trigger function here to use new granule
def test_granule_publish(self):
log.debug("test_granule_publish ")
self.loggerpids = []
#retrieve the param dict from the repository
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('ctd_parsed_param_dict',id_only=True)
stream_definition_id = self.pubsubclient.create_stream_definition('parsed stream', parameter_dictionary_id=pdict_id)
tdom, sdom = time_series_domain()
dp_obj = IonObject(RT.DataProduct,
name='the parsed data',
description='ctd stream test',
temporal_domain = tdom.dump(),
spatial_domain = sdom.dump())
data_product_id1 = self.dpclient.create_data_product(data_product=dp_obj, stream_definition_id=stream_definition_id)
# Retrieve the id of the output stream of the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id1, PRED.hasStream, None, True)
log.debug( 'test_granule_publish: Data product streams1 = %s', stream_ids)
pid = self.create_logger('ctd_parsed', stream_ids[0] )
self.loggerpids.append(pid)
rdt = RecordDictionaryTool(stream_definition_id=stream_definition_id)
#create the publisher from the stream route
stream_route = self.pubsubclient.read_stream_route(stream_ids[0])
publisher = StandaloneStreamPublisher(stream_ids[0], stream_route)
# this is one sample from the ctd driver
tomato = {"driver_timestamp": 3555971105.1268806, "instrument_id": "ABC-123", "pkt_format_id": "JSON_Data", "pkt_version": 1, "preferred_timestamp": "driver_timestamp", "quality_flag": "ok", "stream_name": "parsed", "values": [{"value": 22.9304, "value_id": "temp"}, {"value": 51.57381, "value_id": "conductivity"}, {"value": 915.551, "value_id": "pressure"}]}
for value in tomato['values']:
log.debug("test_granule_publish: Looping tomato values key: %s val: %s ", str(value['value']), str(value['value_id']))
if value['value_id'] in rdt:
rdt[value['value_id']] = numpy.array( [ value['value'] ] )
log.debug("test_granule_publish: Added data item %s val: %s ", str(value['value']), str(value['value_id']) )
g = rdt.to_granule()
publisher.publish(g)
time.sleep(3)
for pid in self.loggerpids:
self.processdispatchclient.cancel_process(pid)
class TestOmsLaunch(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.omsclient = ObservatoryManagementServiceClient(
node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(
node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.dpclient = DataProductManagementServiceClient(
node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
# Use the network definition provided by RSN OMS directly.
rsn_oms = CIOMSClientFactory.create_instance(DVR_CONFIG['oms_uri'])
self._network_definition = RsnOmsUtil.build_network_definition(rsn_oms)
# get serialized version for the configuration:
self._network_definition_ser = NetworkUtil.serialize_network_definition(
self._network_definition)
if log.isEnabledFor(logging.DEBUG):
log.debug("NetworkDefinition serialization:\n%s",
self._network_definition_ser)
self.platformModel_id = None
self.all_platforms = {}
self.agent_streamconfig_map = {}
self._async_data_result = AsyncResult()
self._data_subscribers = []
self._samples_received = []
self.addCleanup(self._stop_data_subscribers)
self._async_event_result = AsyncResult()
self._event_subscribers = []
self._events_received = []
self.addCleanup(self._stop_event_subscribers)
self._start_event_subscriber()
self._set_up_DataProduct_obj()
self._set_up_PlatformModel_obj()
def _set_up_DataProduct_obj(self):
# Create data product object to be used for each of the platform log streams
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
self.pdict_id = self.dataset_management.read_parameter_dictionary_by_name(
'platform_eng_parsed', id_only=True)
self.platform_eng_stream_def_id = self.pubsubcli.create_stream_definition(
name='platform_eng', parameter_dictionary_id=self.pdict_id)
self.dp_obj = IonObject(RT.DataProduct,
name='platform_eng data',
description='platform_eng test',
temporal_domain=tdom,
spatial_domain=sdom)
def _set_up_PlatformModel_obj(self):
# Create PlatformModel
platformModel_obj = IonObject(RT.PlatformModel,
name='RSNPlatformModel',
description="RSNPlatformModel")
try:
self.platformModel_id = self.imsclient.create_platform_model(
platformModel_obj)
except BadRequest as ex:
self.fail("failed to create new PLatformModel: %s" % ex)
log.debug('new PlatformModel id = %s', self.platformModel_id)
def _traverse(self, pnode, platform_id, parent_platform_objs=None):
"""
Recursive routine that repeatedly calls _prepare_platform to build
the object dictionary for each platform.
@param pnode PlatformNode
@param platform_id ID of the platform to be visited
@param parent_platform_objs dict of objects associated to parent
platform, if any.
@retval the dict returned by _prepare_platform at this level.
"""
log.info("Starting _traverse for %r", platform_id)
plat_objs = self._prepare_platform(pnode, platform_id,
parent_platform_objs)
self.all_platforms[platform_id] = plat_objs
# now, traverse the children:
for sub_pnode in pnode.subplatforms.itervalues():
subplatform_id = sub_pnode.platform_id
self._traverse(sub_pnode, subplatform_id, plat_objs)
return plat_objs
def _prepare_platform(self, pnode, platform_id, parent_platform_objs):
"""
This routine generalizes the manual construction originally done in
test_oms_launch.py. It is called by the recursive _traverse method so
all platforms starting from a given base platform are prepared.
Note: For simplicity in this test, sites are organized in the same
hierarchical way as the platforms themselves.
@param pnode PlatformNode
@param platform_id ID of the platform to be visited
@param parent_platform_objs dict of objects associated to parent
platform, if any.
@retval a dict of associated objects similar to those in
test_oms_launch
"""
site__obj = IonObject(RT.PlatformSite,
name='%s_PlatformSite' % platform_id,
description='%s_PlatformSite platform site' %
platform_id)
site_id = self.omsclient.create_platform_site(site__obj)
if parent_platform_objs:
# establish hasSite association with the parent
self.rrclient.create_association(
subject=parent_platform_objs['site_id'],
predicate=PRED.hasSite,
object=site_id)
# prepare platform attributes and ports:
monitor_attribute_objs, monitor_attribute_dicts = self._prepare_platform_attributes(
pnode, platform_id)
port_objs, port_dicts = self._prepare_platform_ports(
pnode, platform_id)
device__obj = IonObject(
RT.PlatformDevice,
name='%s_PlatformDevice' % platform_id,
description='%s_PlatformDevice platform device' % platform_id,
# ports=port_objs,
# platform_monitor_attributes = monitor_attribute_objs
)
device__dict = dict(
ports=port_dicts,
platform_monitor_attributes=monitor_attribute_dicts)
self.device_id = self.imsclient.create_platform_device(device__obj)
self.imsclient.assign_platform_model_to_platform_device(
self.platformModel_id, self.device_id)
self.rrclient.create_association(subject=site_id,
predicate=PRED.hasDevice,
object=self.device_id)
self.damsclient.register_instrument(instrument_id=self.device_id)
if parent_platform_objs:
# establish hasDevice association with the parent
self.rrclient.create_association(
subject=parent_platform_objs['device_id'],
predicate=PRED.hasDevice,
object=self.device_id)
agent__obj = IonObject(RT.PlatformAgent,
name='%s_PlatformAgent' % platform_id,
description='%s_PlatformAgent platform agent' %
platform_id)
agent_id = self.imsclient.create_platform_agent(agent__obj)
if parent_platform_objs:
# add this platform_id to parent's children:
parent_platform_objs['children'].append(platform_id)
self.imsclient.assign_platform_model_to_platform_agent(
self.platformModel_id, agent_id)
# agent_instance_obj = IonObject(RT.PlatformAgentInstance,
# name='%s_PlatformAgentInstance' % platform_id,
# description="%s_PlatformAgentInstance" % platform_id)
#
# agent_instance_id = self.imsclient.create_platform_agent_instance(
# agent_instance_obj, agent_id, device_id)
plat_objs = {
'platform_id': platform_id,
'site__obj': site__obj,
'site_id': site_id,
'device__obj': device__obj,
'device_id': self.device_id,
'agent__obj': agent__obj,
'agent_id': agent_id,
# 'agent_instance_obj': agent_instance_obj,
# 'agent_instance_id': agent_instance_id,
'children': []
}
log.info("plat_objs for platform_id %r = %s", platform_id,
str(plat_objs))
stream_config = self._create_stream_config(plat_objs)
self.agent_streamconfig_map[platform_id] = stream_config
# self.agent_streamconfig_map[platform_id] = None
# self._start_data_subscriber(agent_instance_id, stream_config)
return plat_objs
def _prepare_platform_attributes(self, pnode, platform_id):
"""
Returns the list of PlatformMonitorAttributes objects corresponding to
the attributes associated to the given platform.
"""
# TODO complete the clean-up of this method
ret_infos = dict((n, a.defn) for (n, a) in pnode.attrs.iteritems())
monitor_attribute_objs = []
monitor_attribute_dicts = []
for attrName, attrDfn in ret_infos.iteritems():
log.debug("platform_id=%r: preparing attribute=%r", platform_id,
attrName)
monitor_rate = attrDfn['monitorCycleSeconds']
units = attrDfn['units']
plat_attr_obj = IonObject(OT.PlatformMonitorAttributes,
id=attrName,
monitor_rate=monitor_rate,
units=units)
plat_attr_dict = dict(id=attrName,
monitor_rate=monitor_rate,
units=units)
monitor_attribute_objs.append(plat_attr_obj)
monitor_attribute_dicts.append(plat_attr_dict)
return monitor_attribute_objs, monitor_attribute_dicts
def _prepare_platform_ports(self, pnode, platform_id):
"""
Returns the list of PlatformPort objects corresponding to the ports
associated to the given platform.
"""
# TODO complete the clean-up of this method
port_objs = []
port_dicts = []
for port_id, network in pnode.ports.iteritems():
log.debug("platform_id=%r: preparing port=%r network=%s",
platform_id, port_id, network)
#
# Note: the name "IP" address has been changed to "network" address
# in the CI-OMS interface spec.
#
plat_port_obj = IonObject(OT.PlatformPort,
port_id=port_id,
ip_address=network)
plat_port_dict = dict(port_id=port_id, network=network)
port_objs.append(plat_port_obj)
port_dicts.append(plat_port_dict)
return port_objs, port_dicts
def _create_stream_config(self, plat_objs):
platform_id = plat_objs['platform_id']
device_id = plat_objs['device_id']
#create the log data product
self.dp_obj.name = '%s platform_eng data' % platform_id
self.data_product_id = self.dpclient.create_data_product(
data_product=self.dp_obj,
stream_definition_id=self.platform_eng_stream_def_id)
self.damsclient.assign_data_product(
input_resource_id=self.device_id,
data_product_id=self.data_product_id)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(self.data_product_id,
PRED.hasStream, None, True)
stream_config = self._build_stream_config(stream_ids[0])
return stream_config
def _build_stream_config(self, stream_id=''):
platform_eng_dictionary = DatasetManagementService.get_parameter_dictionary_by_name(
'platform_eng_parsed')
#get the streamroute object from pubsub by passing the stream_id
stream_def_ids, _ = self.rrclient.find_objects(
stream_id, PRED.hasStreamDefinition, RT.StreamDefinition, True)
stream_route = self.pubsubcli.read_stream_route(stream_id=stream_id)
stream_config = {
'routing_key': stream_route.routing_key,
'stream_id': stream_id,
'stream_definition_ref': stream_def_ids[0],
'exchange_point': stream_route.exchange_point,
'parameter_dictionary': platform_eng_dictionary.dump()
}
return stream_config
def _set_platform_agent_instances(self):
"""
Once most of the objs/defs associated with all platforms are in
place, this method creates and associates the PlatformAgentInstance
elements.
"""
self.platform_configs = {}
for platform_id, plat_objs in self.all_platforms.iteritems():
PLATFORM_CONFIG = {
'platform_id': platform_id,
'agent_streamconfig_map': None, #self.agent_streamconfig_map,
'driver_config': DVR_CONFIG,
'network_definition': self._network_definition_ser
}
self.platform_configs[platform_id] = {
'platform_id': platform_id,
'agent_streamconfig_map': self.agent_streamconfig_map,
'driver_config': DVR_CONFIG,
'network_definition': self._network_definition_ser
}
agent_config = {
'platform_config': PLATFORM_CONFIG,
}
self.stream_id = self.agent_streamconfig_map[platform_id][
'stream_id']
# import pprint
# print '============== platform id within unit test: %s ===========' % platform_id
# pprint.pprint(agent_config)
#agent_config['platform_config']['agent_streamconfig_map'] = None
agent_instance_obj = IonObject(
RT.PlatformAgentInstance,
name='%s_PlatformAgentInstance' % platform_id,
description="%s_PlatformAgentInstance" % platform_id,
agent_config=agent_config)
agent_id = plat_objs['agent_id']
device_id = plat_objs['device_id']
agent_instance_id = self.imsclient.create_platform_agent_instance(
agent_instance_obj, agent_id, self.device_id)
plat_objs['agent_instance_obj'] = agent_instance_obj
plat_objs['agent_instance_id'] = agent_instance_id
stream_config = self.agent_streamconfig_map[platform_id]
self._start_data_subscriber(agent_instance_id, stream_config)
def _start_data_subscriber(self, stream_name, stream_config):
"""
Starts data subscriber for the given stream_name and stream_config
"""
def consume_data(message, stream_route, stream_id):
# A callback for processing subscribed-to data.
log.info('Subscriber received data message: %s.', str(message))
self._samples_received.append(message)
self._async_data_result.set()
log.info('_start_data_subscriber stream_name=%r', stream_name)
stream_id = self.stream_id #stream_config['stream_id']
# Create subscription for the stream
exchange_name = '%s_queue' % stream_name
self.container.ex_manager.create_xn_queue(exchange_name).purge()
sub = StandaloneStreamSubscriber(exchange_name, consume_data)
sub.start()
self._data_subscribers.append(sub)
sub_id = self.pubsubcli.create_subscription(name=exchange_name,
stream_ids=[stream_id])
self.pubsubcli.activate_subscription(sub_id)
sub.subscription_id = sub_id
def _stop_data_subscribers(self):
"""
Stop the data subscribers on cleanup.
"""
try:
for sub in self._data_subscribers:
if hasattr(sub, 'subscription_id'):
try:
self.pubsubcli.deactivate_subscription(
sub.subscription_id)
except:
pass
self.pubsubcli.delete_subscription(sub.subscription_id)
sub.stop()
finally:
self._data_subscribers = []
def _start_event_subscriber(self,
event_type="DeviceEvent",
sub_type="platform_event"):
"""
Starts event subscriber for events of given event_type ("DeviceEvent"
by default) and given sub_type ("platform_event" by default).
"""
def consume_event(evt, *args, **kwargs):
# A callback for consuming events.
log.info('Event subscriber received evt: %s.', str(evt))
self._events_received.append(evt)
self._async_event_result.set(evt)
sub = EventSubscriber(event_type=event_type,
sub_type=sub_type,
callback=consume_event)
sub.start()
log.info("registered event subscriber for event_type=%r, sub_type=%r",
event_type, sub_type)
self._event_subscribers.append(sub)
sub._ready_event.wait(timeout=EVENT_TIMEOUT)
def _stop_event_subscribers(self):
"""
Stops the event subscribers on cleanup.
"""
try:
for sub in self._event_subscribers:
if hasattr(sub, 'subscription_id'):
try:
self.pubsubcli.deactivate_subscription(
sub.subscription_id)
except:
pass
self.pubsubcli.delete_subscription(sub.subscription_id)
sub.stop()
finally:
self._event_subscribers = []
@skip("IMS does't net implement topology")
def test_hierarchy(self):
self._create_launch_verify(BASE_PLATFORM_ID)
@skip("Needs alignment with recent IMS changes")
def test_single_platform(self):
self._create_launch_verify('LJ01D')
def _create_launch_verify(self, base_platform_id):
# and trigger the traversal of the branch rooted at that base platform
# to create corresponding ION objects and configuration dictionaries:
pnode = self._network_definition.pnodes[base_platform_id]
base_platform_objs = self._traverse(pnode, base_platform_id)
# now that most of the topology information is there, add the
# PlatformAgentInstance elements
self._set_platform_agent_instances()
base_platform_config = self.platform_configs[base_platform_id]
log.info("base_platform_id = %r", base_platform_id)
#-------------------------------------------------------------------------------------
# Create Data Process Definition and Data Process for the eng stream monitor process
#-------------------------------------------------------------------------------------
dpd_obj = IonObject(
RT.DataProcessDefinition,
name='DemoStreamAlertTransform',
description='For testing EventTriggeredTransform_B',
module='ion.processes.data.transforms.event_alert_transform',
class_name='DemoStreamAlertTransform')
self.platform_dprocdef_id = self.dataprocessclient.create_data_process_definition(
dpd_obj)
#THERE SHOULD BE NO STREAMDEF REQUIRED HERE.
platform_streamdef_id = self.pubsubcli.create_stream_definition(
name='platform_eng_parsed', parameter_dictionary_id=self.pdict_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(
platform_streamdef_id, self.platform_dprocdef_id, binding='output')
config = {
'process': {
'timer_interval': 5,
'queue_name': 'a_queue',
'variable_name': 'input_voltage',
'time_field_name': 'preferred_timestamp',
'valid_values': [-100, 100],
'timer_origin': 'Interval Timer'
}
}
platform_data_process_id = self.dataprocessclient.create_data_process(
self.platform_dprocdef_id, [self.data_product_id], {}, config)
self.dataprocessclient.activate_data_process(platform_data_process_id)
self.addCleanup(self.dataprocessclient.delete_data_process,
platform_data_process_id)
#-------------------------------
# Launch Base Platform AgentInstance, connect to the resource agent client
#-------------------------------
agent_instance_id = base_platform_objs['agent_instance_id']
log.debug(
"about to call imsclient.start_platform_agent_instance with id=%s",
agent_instance_id)
pid = self.imsclient.start_platform_agent_instance(
platform_agent_instance_id=agent_instance_id)
log.debug("start_platform_agent_instance returned pid=%s", pid)
#wait for start
instance_obj = self.imsclient.read_platform_agent_instance(
agent_instance_id)
gate = ProcessStateGate(self.processdispatchclient.read_process,
instance_obj.agent_process_id,
ProcessStateEnum.RUNNING)
self.assertTrue(
gate. await (90),
"The platform agent instance did not spawn in 90 seconds")
agent_instance_obj = self.imsclient.read_instrument_agent_instance(
agent_instance_id)
log.debug(
'test_oms_create_and_launch: Platform agent instance obj: %s',
str(agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._pa_client = ResourceAgentClient(
'paclient',
name=agent_instance_obj.agent_process_id,
process=FakeProcess())
log.debug(" test_oms_create_and_launch:: got pa client %s",
str(self._pa_client))
log.debug("base_platform_config =\n%s", base_platform_config)
# ping_agent can be issued before INITIALIZE
retval = self._pa_client.ping_agent(timeout=TIMEOUT)
log.debug('Base Platform ping_agent = %s', str(retval))
# issue INITIALIZE command to the base platform, which will launch the
# creation of the whole platform hierarchy rooted at base_platform_config['platform_id']
# cmd = AgentCommand(command=PlatformAgentEvent.INITIALIZE, kwargs=dict(plat_config=base_platform_config))
cmd = AgentCommand(command=PlatformAgentEvent.INITIALIZE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug('Base Platform INITIALIZE = %s', str(retval))
# GO_ACTIVE
cmd = AgentCommand(command=PlatformAgentEvent.GO_ACTIVE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug('Base Platform GO_ACTIVE = %s', str(retval))
# RUN:
cmd = AgentCommand(command=PlatformAgentEvent.RUN)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug('Base Platform RUN = %s', str(retval))
# START_MONITORING:
cmd = AgentCommand(command=PlatformAgentEvent.START_MONITORING)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug('Base Platform START_MONITORING = %s', str(retval))
# wait for data sample
# just wait for at least one -- see consume_data above
log.info("waiting for reception of a data sample...")
self._async_data_result.get(timeout=DATA_TIMEOUT)
self.assertTrue(len(self._samples_received) >= 1)
log.info("waiting a bit more for reception of more data samples...")
sleep(15)
log.info("Got data samples: %d", len(self._samples_received))
# wait for event
# just wait for at least one event -- see consume_event above
log.info("waiting for reception of an event...")
self._async_event_result.get(timeout=EVENT_TIMEOUT)
log.info("Received events: %s", len(self._events_received))
#get the extended platfrom which wil include platform aggreate status fields
extended_platform = self.imsclient.get_platform_device_extension(
self.device_id)
# log.debug( 'test_single_platform extended_platform: %s', str(extended_platform) )
# log.debug( 'test_single_platform power_status_roll_up: %s', str(extended_platform.computed.power_status_roll_up.value) )
# log.debug( 'test_single_platform comms_status_roll_up: %s', str(extended_platform.computed.communications_status_roll_up.value) )
# STOP_MONITORING:
cmd = AgentCommand(command=PlatformAgentEvent.STOP_MONITORING)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug('Base Platform STOP_MONITORING = %s', str(retval))
# GO_INACTIVE
cmd = AgentCommand(command=PlatformAgentEvent.GO_INACTIVE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug('Base Platform GO_INACTIVE = %s', str(retval))
# RESET: Resets the base platform agent, which includes termination of
# its sub-platforms processes:
cmd = AgentCommand(command=PlatformAgentEvent.RESET)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug('Base Platform RESET = %s', str(retval))
#-------------------------------
# Stop Base Platform AgentInstance
#-------------------------------
self.imsclient.stop_platform_agent_instance(
platform_agent_instance_id=agent_instance_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.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 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)
class TestPreloadThenLoadDataset(IonIntegrationTestCase):
""" Uses the preload system to define the ExternalDataset and related resources,
then invokes services to perform the load
"""
def setUp(self):
# Start container
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
config = dict(op="load", scenario="NOSE", attachments="res/preload/r2_ioc/attachments")
self.container.spawn_process("Loader", "ion.processes.bootstrap.ion_loader", "IONLoader", config=config)
self.pubsub = PubsubManagementServiceClient()
self.dams = DataAcquisitionManagementServiceClient()
@unittest.skip("depricated test, now in mi repo")
def test_use_case(self):
# setUp() has already started the container and performed the preload
# self.assert_dataset_loaded('Test External CTD Dataset') # make sure we have the ExternalDataset resources
self.assert_dataset_loaded('Unit Test SMB37') # association changed -- now use device name
self.do_listen_for_incoming() # listen for any data being received from the dataset
self.do_read_dataset() # call services to load dataset
self.assert_data_received() # check that data was received as expected
self.do_shutdown()
def assert_dataset_loaded(self, name):
rr = self.container.resource_registry
# self.external_dataset = self.find_object_by_name(name, RT.ExternalDataset)
devs, _ = rr.find_resources(RT.InstrumentDevice, name=name, id_only=False)
self.assertEquals(len(devs), 1)
self.device = devs[0]
obj,_ = rr.find_objects(subject=self.device._id, predicate=PRED.hasAgentInstance, object_type=RT.ExternalDatasetAgentInstance)
self.agent_instance = obj[0]
obj,_ = rr.find_objects(object_type=RT.ExternalDatasetAgent, predicate=PRED.hasAgentDefinition, subject=self.agent_instance._id)
self.agent = obj[0]
driver_cfg = self.agent_instance.driver_config
#stream_definition_id = driver_cfg['dh_cfg']['stream_def'] if 'dh_cfg' in driver_cfg else driver_cfg['stream_def']
#self.stream_definition = rr.read(stream_definition_id)
self.data_product = rr.read_object(subject=self.device._id, predicate=PRED.hasOutputProduct, object_type=RT.DataProduct)
self.dataset_id = rr.read_object(subject=self.data_product._id, predicate=PRED.hasDataset, object_type=RT.Dataset, id_only=True)
ids,_ = rr.find_objects(subject=self.data_product._id, predicate=PRED.hasStream, object_type=RT.Stream, id_only=True)
self.stream_id = ids[0]
self.route = self.pubsub.read_stream_route(self.stream_id)
def do_listen_for_incoming(self):
subscription_id = self.pubsub.create_subscription('validator', data_product_ids=[self.data_product._id])
self.addCleanup(self.pubsub.delete_subscription, subscription_id)
self.granule_capture = []
self.granule_count = 0
def on_granule(msg, route, stream_id):
self.granule_count += 1
if self.granule_count < 5:
self.granule_capture.append(msg)
validator = StandaloneStreamSubscriber('validator', callback=on_granule)
validator.start()
self.addCleanup(validator.stop)
self.pubsub.activate_subscription(subscription_id)
self.addCleanup(self.pubsub.deactivate_subscription, subscription_id)
self.dataset_modified = Event()
def cb2(*args, **kwargs):
self.dataset_modified.set()
# TODO: event isn't using the ExternalDataset, but a different ID for a Dataset
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb2, origin=self.dataset_id)
es.start()
self.addCleanup(es.stop)
def do_read_dataset(self):
self.dams.start_external_dataset_agent_instance(self.agent_instance._id)
#
# should i wait for process (above) to start
# before launching client (below)?
#
self.client = None
end = time.time() + MAX_AGENT_START_TIME
while not self.client and time.time() < end:
try:
self.client = ResourceAgentClient(self.device._id, process=FakeProcess())
except NotFound:
time.sleep(2)
if not self.client:
self.fail(msg='external dataset agent process did not start in %d seconds' % MAX_AGENT_START_TIME)
self.client.execute_agent(AgentCommand(command=ResourceAgentEvent.INITIALIZE))
self.client.execute_agent(AgentCommand(command=ResourceAgentEvent.GO_ACTIVE))
self.client.execute_agent(AgentCommand(command=ResourceAgentEvent.RUN))
self.client.execute_resource(command=AgentCommand(command=DriverEvent.START_AUTOSAMPLE))
def assert_data_received(self):
#let it go for up to 120 seconds, then stop the agent and reset it
if not self.dataset_modified.is_set():
self.dataset_modified.wait(30)
self.assertTrue(self.granule_count > 2, msg='granule count = %d'%self.granule_count)
rdt = RecordDictionaryTool.load_from_granule(self.granule_capture[0])
self.assertAlmostEqual(0, rdt['oxygen'][0], delta=0.01)
self.assertAlmostEqual(309.77, rdt['pressure'][0], delta=0.01)
self.assertAlmostEqual(37.9848, rdt['conductivity'][0], delta=0.01)
self.assertAlmostEqual(9.5163, rdt['temp'][0], delta=0.01)
self.assertAlmostEqual(3527207897.0, rdt['time'][0], delta=1)
def do_shutdown(self):
self.dams.stop_external_dataset_agent_instance(self.agent_instance._id)
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 BulkIngestBase(object):
"""
awkward, non-obvious test class! subclasses will implement data-specific methods and
this test class will parse sample file and assert data was read.
test_data_ingest: create resources and call...
start_agent: starts agent and then call...
start_listener: starts listeners for data, including one that when granule is received calls...
get_retrieve_client: asserts that callback had some data
See replacement TestPreloadThenLoadDataset. A little more declarative and straight-forward, but much slower (requires preload).
"""
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 build_param_contexts(self):
raise NotImplementedError("build_param_contexts must be implemented in child classes")
def create_external_dataset(self):
raise NotImplementedError("create_external_dataset must be implemented in child classes")
def get_dvr_config(self):
raise NotImplementedError("get_dvr_config must be implemented in child classes")
def get_retrieve_client(self, dataset_id=""):
raise NotImplementedError("get_retrieve_client must be implemented in child classes")
def test_data_ingest(self):
self.pdict_id = self.create_parameter_dict(self.name)
self.stream_def_id = self.create_stream_def(self.name, self.pdict_id)
self.data_product_id = self.create_data_product(self.name, self.description, self.stream_def_id)
self.dataset_id = self.get_dataset_id(self.data_product_id)
self.stream_id, self.route = self.get_stream_id_and_route(self.data_product_id)
self.external_dataset_id = self.create_external_dataset()
self.data_producer_id = self.register_external_dataset(self.external_dataset_id)
self.start_agent()
def create_parameter_dict(self, name=""):
return self.dataset_management.create_parameter_dictionary(
name=name, parameter_context_ids=self.context_ids, temporal_context="time"
)
def create_stream_def(self, name="", pdict_id=""):
return self.pubsub_management.create_stream_definition(name=name, parameter_dictionary_id=pdict_id)
def create_data_product(self, name="", description="", stream_def_id=""):
tdom, sdom = time_series_domain()
tdom = tdom.dump()
sdom = sdom.dump()
dp_obj = DataProduct(
name=name,
description=description,
processing_level_code="Parsed_Canonical",
temporal_domain=tdom,
spatial_domain=sdom,
)
data_product_id = self.data_product_management.create_data_product(
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 register_external_dataset(self, external_dataset_id=""):
return self.data_acquisition_management.register_external_data_set(external_dataset_id=external_dataset_id)
def get_dataset_id(self, data_product_id=""):
dataset_ids, assocs = self.resource_registry.find_objects(
subject=data_product_id, predicate="hasDataset", id_only=True
)
return dataset_ids[0]
def get_stream_id_and_route(self, data_product_id):
stream_ids, _ = self.resource_registry.find_objects(data_product_id, PRED.hasStream, RT.Stream, id_only=True)
stream_id = stream_ids[0]
route = self.pubsub_management.read_stream_route(stream_id)
# self.create_logger(self.name, stream_id)
return stream_id, route
def start_agent(self):
agent_config = {
"driver_config": self.get_dvr_config(),
"stream_config": {},
"agent": {"resource_id": self.external_dataset_id},
"test_mode": True,
}
self._ia_pid = self.container.spawn_process(
name=self.EDA_NAME, module=self.EDA_MOD, cls=self.EDA_CLS, config=agent_config
)
self._ia_client = ResourceAgentClient(self.external_dataset_id, process=FakeProcess())
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=DriverEvent.START_AUTOSAMPLE)
self._ia_client.execute_resource(command=cmd)
self.start_listener(self.dataset_id)
def stop_agent(self):
cmd = AgentCommand(command=DriverEvent.STOP_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
self.container.terminate_process(self._ia_pid)
def start_listener(self, dataset_id=""):
dataset_modified = Event()
# callback to use retrieve to get data from the coverage
def cb(*args, **kwargs):
self.get_retrieve_client(dataset_id=dataset_id)
# callback to keep execution going once dataset has been fully ingested
def cb2(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb, origin=dataset_id)
es.start()
es2 = EventSubscriber(
event_type=OT.DeviceCommonLifecycleEvent, callback=cb2, origin="BaseDataHandler._acquire_sample"
)
es2.start()
self.addCleanup(es.stop)
self.addCleanup(es2.stop)
# let it go for up to 120 seconds, then stop the agent and reset it
dataset_modified.wait(120)
self.stop_agent()
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.process_dispatch_client.create_process_definition(
process_definition=producer_definition
)
configuration = {"process": {"stream_id": stream_id}}
pid = self.process_dispatch_client.schedule_process(
process_definition_id=logger_procdef_id, configuration=configuration
)
return pid
class CtdbpTransformsIntTest(IonIntegrationTestCase):
def setUp(self):
super(CtdbpTransformsIntTest, self).setUp()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.pubsub = PubsubManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.data_process_management = DataProcessManagementServiceClient()
self.dataproduct_management = DataProductManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
# This is for the time values inside the packets going into the transform
self.i = 0
# Cleanup of queue created by the subscriber
def _get_new_ctd_packet(self, stream_definition_id, length):
rdt = RecordDictionaryTool(stream_definition_id=stream_definition_id)
rdt['time'] = numpy.arange(self.i, self.i+length)
for field in rdt:
if isinstance(rdt._pdict.get_context(field).param_type, QuantityType):
rdt[field] = numpy.array([random.uniform(0.0,75.0) for i in xrange(length)])
g = rdt.to_granule()
self.i+=length
return g
def _create_input_param_dict_for_test(self, parameter_dict_name = ''):
pdict = ParameterDictionary()
t_ctxt = ParameterContext('time', param_type=QuantityType(value_encoding=numpy.dtype('float64')))
t_ctxt.axis = AxisTypeEnum.TIME
t_ctxt.uom = 'seconds since 01-01-1900'
pdict.add_context(t_ctxt)
cond_ctxt = ParameterContext('conductivity', param_type=QuantityType(value_encoding=numpy.dtype('float32')))
cond_ctxt.uom = ''
pdict.add_context(cond_ctxt)
pres_ctxt = ParameterContext('pressure', param_type=QuantityType(value_encoding=numpy.dtype('float32')))
pres_ctxt.uom = ''
pdict.add_context(pres_ctxt)
temp_ctxt = ParameterContext('temperature', param_type=QuantityType(value_encoding=numpy.dtype('float32')))
temp_ctxt.uom = ''
pdict.add_context(temp_ctxt)
dens_ctxt = ParameterContext('density', param_type=QuantityType(value_encoding=numpy.dtype('float32')))
dens_ctxt.uom = ''
pdict.add_context(dens_ctxt)
sal_ctxt = ParameterContext('salinity', param_type=QuantityType(value_encoding=numpy.dtype('float32')))
sal_ctxt.uom = ''
pdict.add_context(sal_ctxt)
#create temp streamdef so the data product can create the stream
pc_list = []
for pc_k, pc in pdict.iteritems():
ctxt_id = self.dataset_management.create_parameter_context(pc_k, pc[1].dump())
pc_list.append(ctxt_id)
self.addCleanup(self.dataset_management.delete_parameter_context,ctxt_id)
pdict_id = self.dataset_management.create_parameter_dictionary(parameter_dict_name, pc_list)
self.addCleanup(self.dataset_management.delete_parameter_dictionary, pdict_id)
return pdict_id
def test_ctdbp_L0_all(self):
"""
Test packets processed by the ctdbp_L0_all transform
"""
#----------- Data Process Definition --------------------------------
dpd_obj = IonObject(RT.DataProcessDefinition,
name='CTDBP_L0_all',
description='Take parsed stream and put the C, T and P into three separate L0 streams.',
module='ion.processes.data.transforms.ctdbp.ctdbp_L0',
class_name='CTDBP_L0_all')
dprocdef_id = self.data_process_management.create_data_process_definition(dpd_obj)
self.addCleanup(self.data_process_management.delete_data_process_definition, dprocdef_id)
log.debug("created data process definition: id = %s", dprocdef_id)
#----------- Data Products --------------------------------
# Construct temporal and spatial Coordinate Reference System objects
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
input_param_dict = self._create_input_param_dict_for_test(parameter_dict_name = 'fictitious_ctdp_param_dict')
# Get the stream definition for the stream using the parameter dictionary
# input_param_dict = self.dataset_management.read_parameter_dictionary_by_name('ctdbp_cdef_sample', id_only=True)
input_stream_def_dict = self.pubsub.create_stream_definition(name='parsed', parameter_dictionary_id=input_param_dict)
self.addCleanup(self.pubsub.delete_stream_definition, input_stream_def_dict)
log.debug("Got the parsed parameter dictionary: id: %s", input_param_dict)
log.debug("Got the stream def for parsed input: %s", input_stream_def_dict)
# Input data product
parsed_stream_dp_obj = IonObject(RT.DataProduct,
name='parsed_stream',
description='Parsed stream input to CTBP L0 transform',
temporal_domain = tdom,
spatial_domain = sdom)
input_dp_id = self.dataproduct_management.create_data_product(data_product=parsed_stream_dp_obj,
stream_definition_id=input_stream_def_dict
)
self.addCleanup(self.dataproduct_management.delete_data_product, input_dp_id)
# output data product
L0_stream_dp_obj = IonObject(RT.DataProduct,
name='L0_stream',
description='L0_stream output of CTBP L0 transform',
temporal_domain = tdom,
spatial_domain = sdom)
L0_stream_dp_id = self.dataproduct_management.create_data_product(data_product=L0_stream_dp_obj,
stream_definition_id=input_stream_def_dict
)
self.addCleanup(self.dataproduct_management.delete_data_product, L0_stream_dp_id)
# We need the key name here to be "L0_stream", since when the data process is launched, this name goes into
# the config as in config.process.publish_streams.L0_stream when the config is used to launch the data process
self.output_products = {'L0_stream' : L0_stream_dp_id}
out_stream_ids, _ = self.resource_registry.find_objects(L0_stream_dp_id, PRED.hasStream, RT.Stream, True)
self.assertTrue(len(out_stream_ids))
output_stream_id = out_stream_ids[0]
dproc_id = self.data_process_management.create_data_process( dprocdef_id, [input_dp_id], self.output_products)
self.addCleanup(self.data_process_management.delete_data_process, dproc_id)
log.debug("Created a data process for ctdbp_L0. id: %s", dproc_id)
# Activate the data process
self.data_process_management.activate_data_process(dproc_id)
self.addCleanup(self.data_process_management.deactivate_data_process, dproc_id)
#----------- Find the stream that is associated with the input data product when it was created by create_data_product() --------------------------------
stream_ids, _ = self.resource_registry.find_objects(input_dp_id, PRED.hasStream, RT.Stream, True)
self.assertTrue(len(stream_ids))
input_stream_id = stream_ids[0]
stream_route = self.pubsub.read_stream_route(input_stream_id)
log.debug("The input stream for the L0 transform: %s", input_stream_id)
#----------- Create a subscriber that will listen to the transform's output --------------------------------
ar = gevent.event.AsyncResult()
def subscriber(m,r,s):
ar.set(m)
sub = StandaloneStreamSubscriber(exchange_name='sub', callback=subscriber)
sub_id = self.pubsub.create_subscription('subscriber_to_transform',
stream_ids=[output_stream_id],
exchange_name='sub')
self.addCleanup(self.pubsub.delete_subscription, sub_id)
self.pubsub.activate_subscription(sub_id)
self.addCleanup(self.pubsub.deactivate_subscription, sub_id)
sub.start()
self.addCleanup(sub.stop)
#----------- Publish on that stream so that the transform can receive it --------------------------------
pub = StandaloneStreamPublisher(input_stream_id, stream_route)
publish_granule = self._get_new_ctd_packet(stream_definition_id=input_stream_def_dict, length = 5)
pub.publish(publish_granule)
log.debug("Published the following granule: %s", publish_granule)
granule_from_transform = ar.get(timeout=20)
log.debug("Got the following granule from the transform: %s", granule_from_transform)
# Check that the granule published by the L0 transform has the right properties
self._check_granule_from_transform(granule_from_transform)
def _check_granule_from_transform(self, granule):
"""
An internal method to check if a granule has the right properties
"""
pass
class TestPreloadThenLoadDataset(IonIntegrationTestCase):
""" replicates the TestHypm_WPF_CTD test (same handler/parser/data file)
but uses the preload system to define the ExternalDataset and related resources,
then invokes services to perform the load
"""
def setUp(self):
# Start container
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
config = dict(op="load", scenario="BETA,NOSE", attachments="res/preload/r2_ioc/attachments")
self.container.spawn_process("Loader", "ion.processes.bootstrap.ion_loader", "IONLoader", config=config)
self.pubsub = PubsubManagementServiceClient()
self.dams = DataAcquisitionManagementServiceClient()
def find_object_by_name(self, name, resource_type):
objects,_ = self.container.resource_registry.find_resources(resource_type)
self.assertTrue(len(objects) >= 1)
# filtered_objs = [obj for obj in objects if obj.name == name]
filtered_objs = []
for obj in objects:
if obj.name==name:
filtered_objs.append(obj)
self.assertEquals(len(filtered_objs), 1, msg='Found %d objects with name %s'%(len(filtered_objs),name))
return filtered_objs[0]
def test_use_case(self):
# setUp() has already started the container and performed the preload
# self.assert_dataset_loaded('Test External CTD Dataset') # make sure we have the ExternalDataset resources
self.assert_dataset_loaded('Unit Test SMB37') # association changed -- now use device name
self.do_listen_for_incoming() # listen for any data being received from the dataset
self.do_read_dataset() # call services to load dataset
self.assert_data_received() # check that data was received as expected
self.do_shutdown()
def assert_dataset_loaded(self, name):
# self.external_dataset = self.find_object_by_name(name, RT.ExternalDataset)
self.device = self.find_object_by_name(name, RT.InstrumentDevice)
rr = self.container.resource_registry
obj,_ = rr.find_objects(subject=self.device._id, predicate=PRED.hasAgentInstance, object_type=RT.ExternalDatasetAgentInstance)
self.agent_instance = obj[0]
obj,_ = rr.find_objects(object_type=RT.ExternalDatasetAgent, predicate=PRED.hasAgentDefinition, subject=self.agent_instance._id)
self.agent = obj[0]
stream_definition_id = self.agent_instance.dataset_driver_config['dh_cfg']['stream_def'] if 'dh_cfg' in self.agent_instance.dataset_driver_config else self.agent_instance.dataset_driver_config['stream_def']
self.stream_definition = rr.read(stream_definition_id)
# data_producer_id = self.agent_instance.dataset_driver_config['dh_cfg']['data_producer_id'] if 'dh_cfg' in self.agent_instance.dataset_driver_config else self.agent_instance.dataset_driver_config['data_producer_id']
# self.data_producer = rr.read(data_producer_id) #subject="", predicate="", object_type="", assoc="", id_only=False)
# self.data_product = rr.read_object(object_type=RT.DataProduct, predicate=PRED.hasOutputProduct, subject=self.external_dataset._id)
self.data_product = rr.read_object(object_type=RT.DataProduct, predicate=PRED.hasOutputProduct, subject=self.device._id)
ids,_ = rr.find_objects(self.data_product._id, PRED.hasStream, RT.Stream, id_only=True)
self.stream_id = ids[0]
self.route = self.pubsub.read_stream_route(self.stream_id)
def do_listen_for_incoming(self):
subscription_id = self.pubsub.create_subscription('validator', data_product_ids=[self.data_product._id])
self.addCleanup(self.pubsub.delete_subscription, subscription_id)
self.granule_capture = []
self.granule_count = 0
def on_granule(msg, route, stream_id):
self.granule_count += 1
if self.granule_count<5:
self.granule_capture.append(msg)
validator = StandaloneStreamSubscriber('validator', callback=on_granule)
validator.start()
self.addCleanup(validator.stop)
self.pubsub.activate_subscription(subscription_id)
self.addCleanup(self.pubsub.deactivate_subscription, subscription_id)
self.dataset_modified = Event()
def cb2(*args, **kwargs):
self.dataset_modified.set()
# TODO: event isn't using the ExternalDataset, but a different ID for a Dataset
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb2, origin=self.device._id)
es.start()
self.addCleanup(es.stop)
def do_read_dataset(self):
self.dams.start_external_dataset_agent_instance(self.agent_instance._id)
#
# should i wait for process (above) to start
# before launching client (below)?
#
self.client = ResourceAgentClient(self.device._id, process=FakeProcess())
self.client.execute_agent(AgentCommand(command=ResourceAgentEvent.INITIALIZE))
self.client.execute_agent(AgentCommand(command=ResourceAgentEvent.GO_ACTIVE))
self.client.execute_agent(AgentCommand(command=ResourceAgentEvent.RUN))
self.client.execute_resource(command=AgentCommand(command=DriverEvent.START_AUTOSAMPLE))
def assert_data_received(self):
#let it go for up to 120 seconds, then stop the agent and reset it
if not self.dataset_modified.is_set():
self.dataset_modified.wait(30)
self.assertTrue(self.granule_count>2, msg='granule count = %d'%self.granule_count)
rdt = RecordDictionaryTool.load_from_granule(self.granule_capture[0])
self.assertAlmostEqual(0, rdt['oxygen'][0], delta=0.01)
self.assertAlmostEqual(309.77, rdt['pressure'][0], delta=0.01)
self.assertAlmostEqual(37.9848, rdt['conductivity'][0], delta=0.01)
self.assertAlmostEqual(9.5163, rdt['temp'][0], delta=0.01)
self.assertAlmostEqual(1318219097, rdt['time'][0], delta=1)
def do_shutdown(self):
self.dams.stop_external_dataset_agent_instance(self.agent_instance._id)
class TestOmsLaunch(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.omsclient = ObservatoryManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
self.platformModel_id = None
# rsn_oms: to retrieve network structure and information from RSN-OMS:
# Note that OmsClientFactory will create an "embedded" RSN OMS
# simulator object by default.
self.rsn_oms = OmsClientFactory.create_instance()
self.all_platforms = {}
self.topology = {}
self.agent_device_map = {}
self.agent_streamconfig_map = {}
self._async_data_result = AsyncResult()
self._data_subscribers = []
self._samples_received = []
self.addCleanup(self._stop_data_subscribers)
self._async_event_result = AsyncResult()
self._event_subscribers = []
self._events_received = []
self.addCleanup(self._stop_event_subscribers)
self._start_event_subscriber()
self._set_up_DataProduct_obj()
self._set_up_PlatformModel_obj()
def _set_up_DataProduct_obj(self):
# Create data product object to be used for each of the platform log streams
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
pdict_id = self.dataset_management.read_parameter_dictionary_by_name('platform_eng_parsed', id_only=True)
self.platform_eng_stream_def_id = self.pubsubcli.create_stream_definition(
name='platform_eng', parameter_dictionary_id=pdict_id)
self.dp_obj = IonObject(RT.DataProduct,
name='platform_eng data',
description='platform_eng test',
temporal_domain = tdom,
spatial_domain = sdom)
def _set_up_PlatformModel_obj(self):
# Create PlatformModel
platformModel_obj = IonObject(RT.PlatformModel,
name='RSNPlatformModel',
description="RSNPlatformModel")
try:
self.platformModel_id = self.imsclient.create_platform_model(platformModel_obj)
except BadRequest as ex:
self.fail("failed to create new PLatformModel: %s" %ex)
log.debug( 'new PlatformModel id = %s', self.platformModel_id)
def _traverse(self, platform_id, parent_platform_objs=None):
"""
Recursive routine that repeatedly calls _prepare_platform to build
the object dictionary for each platform.
@param platform_id ID of the platform to be visited
@param parent_platform_objs dict of objects associated to parent
platform, if any.
@retval the dict returned by _prepare_platform at this level.
"""
log.info("Starting _traverse for %r", platform_id)
plat_objs = self._prepare_platform(platform_id, parent_platform_objs)
self.all_platforms[platform_id] = plat_objs
# now, traverse the children:
retval = self.rsn_oms.getSubplatformIDs(platform_id)
subplatform_ids = retval[platform_id]
for subplatform_id in subplatform_ids:
self._traverse(subplatform_id, plat_objs)
# note, topology indexed by platform_id
self.topology[platform_id] = plat_objs['children']
return plat_objs
def _prepare_platform(self, platform_id, parent_platform_objs):
"""
This routine generalizes the manual construction currently done in
test_oms_launch.py. It is called by the recursive _traverse method so
all platforms starting from a given base platform are prepared.
Note: For simplicity in this test, sites are organized in the same
hierarchical way as the platforms themselves.
@param platform_id ID of the platform to be visited
@param parent_platform_objs dict of objects associated to parent
platform, if any.
@retval a dict of associated objects similar to those in
test_oms_launch
"""
site__obj = IonObject(RT.PlatformSite,
name='%s_PlatformSite' % platform_id,
description='%s_PlatformSite platform site' % platform_id)
site_id = self.omsclient.create_platform_site(site__obj)
if parent_platform_objs:
# establish hasSite association with the parent
self.rrclient.create_association(
subject=parent_platform_objs['site_id'],
predicate=PRED.hasSite,
object=site_id)
# prepare platform attributes and ports:
monitor_attributes = self._prepare_platform_attributes(platform_id)
ports = self._prepare_platform_ports(platform_id)
device__obj = IonObject(RT.PlatformDevice,
name='%s_PlatformDevice' % platform_id,
description='%s_PlatformDevice platform device' % platform_id,
ports=ports,
platform_monitor_attributes = monitor_attributes)
device_id = self.imsclient.create_platform_device(device__obj)
self.imsclient.assign_platform_model_to_platform_device(self.platformModel_id, device_id)
self.rrclient.create_association(subject=site_id, predicate=PRED.hasDevice, object=device_id)
self.damsclient.register_instrument(instrument_id=device_id)
if parent_platform_objs:
# establish hasDevice association with the parent
self.rrclient.create_association(
subject=parent_platform_objs['device_id'],
predicate=PRED.hasDevice,
object=device_id)
agent__obj = IonObject(RT.PlatformAgent,
name='%s_PlatformAgent' % platform_id,
description='%s_PlatformAgent platform agent' % platform_id)
agent_id = self.imsclient.create_platform_agent(agent__obj)
if parent_platform_objs:
# add this platform_id to parent's children:
parent_platform_objs['children'].append(platform_id)
self.imsclient.assign_platform_model_to_platform_agent(self.platformModel_id, agent_id)
# agent_instance_obj = IonObject(RT.PlatformAgentInstance,
# name='%s_PlatformAgentInstance' % platform_id,
# description="%s_PlatformAgentInstance" % platform_id)
#
# agent_instance_id = self.imsclient.create_platform_agent_instance(
# agent_instance_obj, agent_id, device_id)
plat_objs = {
'platform_id': platform_id,
'site__obj': site__obj,
'site_id': site_id,
'device__obj': device__obj,
'device_id': device_id,
'agent__obj': agent__obj,
'agent_id': agent_id,
# 'agent_instance_obj': agent_instance_obj,
# 'agent_instance_id': agent_instance_id,
'children': []
}
log.info("plat_objs for platform_id %r = %s", platform_id, str(plat_objs))
self.agent_device_map[platform_id] = device__obj
stream_config = self._create_stream_config(plat_objs)
self.agent_streamconfig_map[platform_id] = stream_config
# self._start_data_subscriber(agent_instance_id, stream_config)
return plat_objs
def _prepare_platform_attributes(self, platform_id):
"""
Returns the list of PlatformMonitorAttributes objects corresponding to
the attributes associated to the given platform.
"""
result = self.rsn_oms.getPlatformAttributes(platform_id)
self.assertTrue(platform_id in result)
ret_infos = result[platform_id]
monitor_attributes = []
for attrName, attrDfn in ret_infos.iteritems():
log.debug("platform_id=%r: preparing attribute=%r", platform_id, attrName)
monitor_rate = attrDfn['monitorCycleSeconds']
units = attrDfn['units']
plat_attr_obj = IonObject(OT.PlatformMonitorAttributes,
id=attrName,
monitor_rate=monitor_rate,
units=units)
monitor_attributes.append(plat_attr_obj)
return monitor_attributes
def _prepare_platform_ports(self, platform_id):
"""
Returns the list of PlatformPort objects corresponding to the ports
associated to the given platform.
"""
result = self.rsn_oms.getPlatformPorts(platform_id)
self.assertTrue(platform_id in result)
port_dict = result[platform_id]
ports = []
for port_id, port in port_dict.iteritems():
log.debug("platform_id=%r: preparing port=%r", platform_id, port_id)
ip_address = port['comms']['ip']
plat_port_obj = IonObject(OT.PlatformPort,
port_id=port_id,
ip_address=ip_address)
ports.append(plat_port_obj)
return ports
def _create_stream_config(self, plat_objs):
platform_id = plat_objs['platform_id']
device_id = plat_objs['device_id']
#create the log data product
self.dp_obj.name = '%s platform_eng data' % platform_id
data_product_id = self.dpclient.create_data_product(data_product=self.dp_obj, stream_definition_id=self.platform_eng_stream_def_id)
self.damsclient.assign_data_product(input_resource_id=device_id, data_product_id=data_product_id)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id, PRED.hasStream, None, True)
stream_config = self._build_stream_config(stream_ids[0])
return stream_config
def _build_stream_config(self, stream_id=''):
platform_eng_dictionary = DatasetManagementService.get_parameter_dictionary_by_name('platform_eng_parsed')
#get the streamroute object from pubsub by passing the stream_id
stream_def_ids, _ = self.rrclient.find_objects(stream_id,
PRED.hasStreamDefinition,
RT.StreamDefinition,
True)
stream_route = self.pubsubcli.read_stream_route(stream_id=stream_id)
stream_config = {'routing_key' : stream_route.routing_key,
'stream_id' : stream_id,
'stream_definition_ref' : stream_def_ids[0],
'exchange_point' : stream_route.exchange_point,
'parameter_dictionary':platform_eng_dictionary.dump()}
return stream_config
def _set_platform_agent_instances(self):
"""
Once most of the objs/defs associated with all platforms are in
place, this method creates and associates the PlatformAgentInstance
elements.
"""
self.platform_configs = {}
for platform_id, plat_objs in self.all_platforms.iteritems():
PLATFORM_CONFIG = self.platform_configs[platform_id] = {
'platform_id': platform_id,
'platform_topology': self.topology,
# 'agent_device_map': self.agent_device_map,
'agent_streamconfig_map': self.agent_streamconfig_map,
'driver_config': DVR_CONFIG,
}
agent_config = {
'platform_config': PLATFORM_CONFIG,
}
agent_instance_obj = IonObject(RT.PlatformAgentInstance,
name='%s_PlatformAgentInstance' % platform_id,
description="%s_PlatformAgentInstance" % platform_id,
agent_config=agent_config)
agent_id = plat_objs['agent_id']
device_id = plat_objs['device_id']
agent_instance_id = self.imsclient.create_platform_agent_instance(
agent_instance_obj, agent_id, device_id)
plat_objs['agent_instance_obj'] = agent_instance_obj
plat_objs['agent_instance_id'] = agent_instance_id
stream_config = self.agent_streamconfig_map[platform_id]
self._start_data_subscriber(agent_instance_id, stream_config)
def _start_data_subscriber(self, stream_name, stream_config):
"""
Starts data subscriber for the given stream_name and stream_config
"""
def consume_data(message, stream_route, stream_id):
# A callback for processing subscribed-to data.
log.info('Subscriber received data message: %s.', str(message))
self._samples_received.append(message)
self._async_data_result.set()
log.info('_start_data_subscriber stream_name=%r', stream_name)
stream_id = stream_config['stream_id']
# Create subscription for the stream
exchange_name = '%s_queue' % stream_name
self.container.ex_manager.create_xn_queue(exchange_name).purge()
sub = StandaloneStreamSubscriber(exchange_name, consume_data)
sub.start()
self._data_subscribers.append(sub)
sub_id = self.pubsubcli.create_subscription(name=exchange_name, stream_ids=[stream_id])
self.pubsubcli.activate_subscription(sub_id)
sub.subscription_id = sub_id
def _stop_data_subscribers(self):
"""
Stop the data subscribers on cleanup.
"""
try:
for sub in self._data_subscribers:
if hasattr(sub, 'subscription_id'):
try:
self.pubsubcli.deactivate_subscription(sub.subscription_id)
except:
pass
self.pubsubcli.delete_subscription(sub.subscription_id)
sub.stop()
finally:
self._data_subscribers = []
def _start_event_subscriber(self, event_type="PlatformAlarmEvent", sub_type="power"):
"""
Starts event subscriber for events of given event_type ("PlatformAlarmEvent"
by default) and given sub_type ("power" by default).
"""
# TODO note: ion-definitions still using 'PlatformAlarmEvent' but we
# should probably define 'PlatformExternalEvent' or something like that.
def consume_event(evt, *args, **kwargs):
# A callback for consuming events.
log.info('Event subscriber received evt: %s.', str(evt))
self._events_received.append(evt)
self._async_event_result.set(evt)
sub = EventSubscriber(event_type=event_type,
sub_type=sub_type,
callback=consume_event)
sub.start()
log.info("registered event subscriber for event_type=%r, sub_type=%r",
event_type, sub_type)
self._event_subscribers.append(sub)
sub._ready_event.wait(timeout=EVENT_TIMEOUT)
def _stop_event_subscribers(self):
"""
Stops the event subscribers on cleanup.
"""
try:
for sub in self._event_subscribers:
if hasattr(sub, 'subscription_id'):
try:
self.pubsubcli.deactivate_subscription(sub.subscription_id)
except:
pass
self.pubsubcli.delete_subscription(sub.subscription_id)
sub.stop()
finally:
self._event_subscribers = []
def test_oms_create_and_launch(self):
# pick a base platform:
base_platform_id = BASE_PLATFORM_ID
# and trigger the traversal of the branch rooted at that base platform
# to create corresponding ION objects and configuration dictionaries:
base_platform_objs = self._traverse(base_platform_id)
# now that most of the topology information is there, add the
# PlatformAgentInstance elements
self._set_platform_agent_instances()
base_platform_config = self.platform_configs[base_platform_id]
log.info("base_platform_id = %r", base_platform_id)
log.info("topology = %s", str(self.topology))
#-------------------------------
# Launch Base Platform AgentInstance, connect to the resource agent client
#-------------------------------
agent_instance_id = base_platform_objs['agent_instance_id']
pid = self.imsclient.start_platform_agent_instance(platform_agent_instance_id=agent_instance_id)
log.debug("start_platform_agent_instance returned pid=%s", pid)
#wait for start
instance_obj = self.imsclient.read_platform_agent_instance(agent_instance_id)
gate = ProcessStateGate(self.processdispatchclient.read_process,
instance_obj.agent_process_id,
ProcessStateEnum.RUNNING)
self.assertTrue(gate.await(90), "The platform agent instance did not spawn in 90 seconds")
agent_instance_obj= self.imsclient.read_instrument_agent_instance(agent_instance_id)
log.debug('test_oms_create_and_launch: Platform agent instance obj: %s', str(agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._pa_client = ResourceAgentClient('paclient', name=agent_instance_obj.agent_process_id, process=FakeProcess())
log.debug(" test_oms_create_and_launch:: got pa client %s", str(self._pa_client))
log.debug("base_platform_config =\n%s", base_platform_config)
# ping_agent can be issued before INITIALIZE
retval = self._pa_client.ping_agent(timeout=TIMEOUT)
log.debug( 'Base Platform ping_agent = %s', str(retval) )
# issue INITIALIZE command to the base platform, which will launch the
# creation of the whole platform hierarchy rooted at base_platform_config['platform_id']
# cmd = AgentCommand(command=PlatformAgentEvent.INITIALIZE, kwargs=dict(plat_config=base_platform_config))
cmd = AgentCommand(command=PlatformAgentEvent.INITIALIZE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform INITIALIZE = %s', str(retval) )
# GO_ACTIVE
cmd = AgentCommand(command=PlatformAgentEvent.GO_ACTIVE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform GO_ACTIVE = %s', str(retval) )
# RUN: this command includes the launch of the resource monitoring greenlets
cmd = AgentCommand(command=PlatformAgentEvent.RUN)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform RUN = %s', str(retval) )
# START_EVENT_DISPATCH
kwargs = dict(params="TODO set params")
cmd = AgentCommand(command=PlatformAgentEvent.START_EVENT_DISPATCH, kwargs=kwargs)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
self.assertTrue(retval.result is not None)
# wait for data sample
# just wait for at least one -- see consume_data above
log.info("waiting for reception of a data sample...")
self._async_data_result.get(timeout=DATA_TIMEOUT)
self.assertTrue(len(self._samples_received) >= 1)
log.info("waiting a bit more for reception of more data samples...")
sleep(10)
log.info("Got data samples: %d", len(self._samples_received))
# wait for event
# just wait for at least one event -- see consume_event above
log.info("waiting for reception of an event...")
self._async_event_result.get(timeout=EVENT_TIMEOUT)
log.info("Received events: %s", len(self._events_received))
# STOP_EVENT_DISPATCH
cmd = AgentCommand(command=PlatformAgentEvent.STOP_EVENT_DISPATCH)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
self.assertTrue(retval.result is not None)
# GO_INACTIVE
cmd = AgentCommand(command=PlatformAgentEvent.GO_INACTIVE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform GO_INACTIVE = %s', str(retval) )
# RESET: Resets the base platform agent, which includes termination of
# its sub-platforms processes:
cmd = AgentCommand(command=PlatformAgentEvent.RESET)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform RESET = %s', str(retval) )
#-------------------------------
# Stop Base Platform AgentInstance
#-------------------------------
self.imsclient.stop_platform_agent_instance(platform_agent_instance_id=agent_instance_id)
class BulkIngestBase(object):
"""
awkward, non-obvious test class! subclasses will implement data-specific methods and
this test class will parse sample file and assert data was read.
test_data_ingest: create resources and call...
start_agent: starts agent and then call...
start_listener: starts listeners for data, including one that when granule is received calls...
get_retrieve_client: asserts that callback had some data
See replacement TestPreloadThenLoadDataset. A little more declarative and straight-forward, but much slower (requires preload).
"""
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 build_param_contexts(self):
raise NotImplementedError('build_param_contexts must be implemented in child classes')
def create_external_dataset(self):
raise NotImplementedError('create_external_dataset must be implemented in child classes')
def get_dvr_config(self):
raise NotImplementedError('get_dvr_config must be implemented in child classes')
def get_retrieve_client(self, dataset_id=''):
raise NotImplementedError('get_retrieve_client must be implemented in child classes')
def test_data_ingest(self):
self.pdict_id = self.create_parameter_dict(self.name)
self.stream_def_id = self.create_stream_def(self.name, self.pdict_id)
self.data_product_id = self.create_data_product(self.name, self.description, self.stream_def_id)
self.dataset_id = self.get_dataset_id(self.data_product_id)
self.stream_id, self.route = self.get_stream_id_and_route(self.data_product_id)
self.external_dataset_id = self.create_external_dataset()
self.data_producer_id = self.register_external_dataset(self.external_dataset_id)
self.start_agent()
def create_parameter_dict(self, name=''):
return self.dataset_management.create_parameter_dictionary(name=name, parameter_context_ids=self.context_ids, temporal_context='time')
def create_stream_def(self, name='', pdict_id=''):
return self.pubsub_management.create_stream_definition(name=name, parameter_dictionary_id=pdict_id)
def create_data_product(self, name='', description='', stream_def_id=''):
tdom, sdom = time_series_domain()
tdom = tdom.dump()
sdom = sdom.dump()
dp_obj = DataProduct(
name=name,
description=description,
processing_level_code='Parsed_Canonical',
temporal_domain=tdom,
spatial_domain=sdom)
data_product_id = self.data_product_management.create_data_product(data_product=dp_obj, stream_definition_id=stream_def_id)
self.data_product_management.activate_data_product_persistence(data_product_id)
self.addCleanup(self.data_product_management.suspend_data_product_persistence, data_product_id)
return data_product_id
def register_external_dataset(self, external_dataset_id=''):
return self.data_acquisition_management.register_external_data_set(external_dataset_id=external_dataset_id)
def get_dataset_id(self, data_product_id=''):
dataset_ids, assocs = self.resource_registry.find_objects(subject=data_product_id, predicate='hasDataset', id_only=True)
return dataset_ids[0]
def get_stream_id_and_route(self, data_product_id):
stream_ids, _ = self.resource_registry.find_objects(data_product_id, PRED.hasStream, RT.Stream, id_only=True)
stream_id = stream_ids[0]
route = self.pubsub_management.read_stream_route(stream_id)
#self.create_logger(self.name, stream_id)
return stream_id, route
def start_agent(self):
agent_config = {
'driver_config': self.get_dvr_config(),
'stream_config': {},
'agent': {'resource_id': self.external_dataset_id},
'test_mode': True
}
self._ia_pid = self.container.spawn_process(
name=self.EDA_NAME,
module=self.EDA_MOD,
cls=self.EDA_CLS,
config=agent_config)
self._ia_client = ResourceAgentClient(self.external_dataset_id, process=FakeProcess())
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=DriverEvent.START_AUTOSAMPLE)
self._ia_client.execute_resource(command=cmd)
self.start_listener(self.dataset_id)
def stop_agent(self):
cmd = AgentCommand(command=DriverEvent.STOP_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
self.container.terminate_process(self._ia_pid)
def start_listener(self, dataset_id=''):
dataset_modified = Event()
#callback to use retrieve to get data from the coverage
def cb(*args, **kwargs):
self.get_retrieve_client(dataset_id=dataset_id)
#callback to keep execution going once dataset has been fully ingested
def cb2(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb, origin=dataset_id)
es.start()
es2 = EventSubscriber(event_type=OT.DeviceCommonLifecycleEvent, callback=cb2, origin='BaseDataHandler._acquire_sample')
es2.start()
self.addCleanup(es.stop)
self.addCleanup(es2.stop)
#let it go for up to 120 seconds, then stop the agent and reset it
dataset_modified.wait(120)
self.stop_agent()
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.process_dispatch_client.create_process_definition(process_definition=producer_definition)
configuration = {
'process':{
'stream_id':stream_id,
}
}
pid = self.process_dispatch_client.schedule_process(process_definition_id=logger_procdef_id, configuration=configuration)
return pid
class TestPreloadThenLoadDataset(IonIntegrationTestCase):
""" Uses the preload system to define the ExternalDataset and related resources,
then invokes services to perform the load
"""
def setUp(self):
# Start container
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
config = dict(op="load",
scenario="NOSE",
attachments="res/preload/r2_ioc/attachments")
self.container.spawn_process("Loader",
"ion.processes.bootstrap.ion_loader",
"IONLoader",
config=config)
self.pubsub = PubsubManagementServiceClient()
self.dams = DataAcquisitionManagementServiceClient()
@unittest.skip("depricated test, now in mi repo")
def test_use_case(self):
# setUp() has already started the container and performed the preload
# self.assert_dataset_loaded('Test External CTD Dataset') # make sure we have the ExternalDataset resources
self.assert_dataset_loaded(
'Unit Test SMB37') # association changed -- now use device name
self.do_listen_for_incoming(
) # listen for any data being received from the dataset
self.do_read_dataset() # call services to load dataset
self.assert_data_received() # check that data was received as expected
self.do_shutdown()
def assert_dataset_loaded(self, name):
rr = self.container.resource_registry
# self.external_dataset = self.find_object_by_name(name, RT.ExternalDataset)
devs, _ = rr.find_resources(RT.InstrumentDevice,
name=name,
id_only=False)
self.assertEquals(len(devs), 1)
self.device = devs[0]
obj, _ = rr.find_objects(subject=self.device._id,
predicate=PRED.hasAgentInstance,
object_type=RT.ExternalDatasetAgentInstance)
self.agent_instance = obj[0]
obj, _ = rr.find_objects(object_type=RT.ExternalDatasetAgent,
predicate=PRED.hasAgentDefinition,
subject=self.agent_instance._id)
self.agent = obj[0]
driver_cfg = self.agent_instance.driver_config
#stream_definition_id = driver_cfg['dh_cfg']['stream_def'] if 'dh_cfg' in driver_cfg else driver_cfg['stream_def']
#self.stream_definition = rr.read(stream_definition_id)
self.data_product = rr.read_object(subject=self.device._id,
predicate=PRED.hasOutputProduct,
object_type=RT.DataProduct)
self.dataset_id = rr.read_object(subject=self.data_product._id,
predicate=PRED.hasDataset,
object_type=RT.Dataset,
id_only=True)
ids, _ = rr.find_objects(subject=self.data_product._id,
predicate=PRED.hasStream,
object_type=RT.Stream,
id_only=True)
self.stream_id = ids[0]
self.route = self.pubsub.read_stream_route(self.stream_id)
def do_listen_for_incoming(self):
subscription_id = self.pubsub.create_subscription(
'validator', data_product_ids=[self.data_product._id])
self.addCleanup(self.pubsub.delete_subscription, subscription_id)
self.granule_capture = []
self.granule_count = 0
def on_granule(msg, route, stream_id):
self.granule_count += 1
if self.granule_count < 5:
self.granule_capture.append(msg)
validator = StandaloneStreamSubscriber('validator',
callback=on_granule)
validator.start()
self.addCleanup(validator.stop)
self.pubsub.activate_subscription(subscription_id)
self.addCleanup(self.pubsub.deactivate_subscription, subscription_id)
self.dataset_modified = Event()
def cb2(*args, **kwargs):
self.dataset_modified.set()
# TODO: event isn't using the ExternalDataset, but a different ID for a Dataset
es = EventSubscriber(event_type=OT.DatasetModified,
callback=cb2,
origin=self.dataset_id)
es.start()
self.addCleanup(es.stop)
def do_read_dataset(self):
self.dams.start_external_dataset_agent_instance(
self.agent_instance._id)
#
# should i wait for process (above) to start
# before launching client (below)?
#
self.client = None
end = time.time() + MAX_AGENT_START_TIME
while not self.client and time.time() < end:
try:
self.client = ResourceAgentClient(self.device._id,
process=FakeProcess())
except NotFound:
time.sleep(2)
if not self.client:
self.fail(
msg='external dataset agent process did not start in %d seconds'
% MAX_AGENT_START_TIME)
self.client.execute_agent(
AgentCommand(command=ResourceAgentEvent.INITIALIZE))
self.client.execute_agent(
AgentCommand(command=ResourceAgentEvent.GO_ACTIVE))
self.client.execute_agent(AgentCommand(command=ResourceAgentEvent.RUN))
self.client.execute_resource(command=AgentCommand(
command=DriverEvent.START_AUTOSAMPLE))
def assert_data_received(self):
#let it go for up to 120 seconds, then stop the agent and reset it
if not self.dataset_modified.is_set():
self.dataset_modified.wait(30)
self.assertTrue(self.granule_count > 2,
msg='granule count = %d' % self.granule_count)
rdt = RecordDictionaryTool.load_from_granule(self.granule_capture[0])
self.assertAlmostEqual(0, rdt['oxygen'][0], delta=0.01)
self.assertAlmostEqual(309.77, rdt['pressure'][0], delta=0.01)
self.assertAlmostEqual(37.9848, rdt['conductivity'][0], delta=0.01)
self.assertAlmostEqual(9.5163, rdt['temp'][0], delta=0.01)
self.assertAlmostEqual(3527207897.0, rdt['time'][0], delta=1)
def do_shutdown(self):
self.dams.stop_external_dataset_agent_instance(self.agent_instance._id)
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 TestTransformWorker(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
# Instantiate a process to represent the test
process = TransformWorkerTestProcess()
self.dataset_management_client = DatasetManagementServiceClient(
node=self.container.node)
self.pubsub_client = PubsubManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceProcessClient(
node=self.container.node, process=process)
self.time_dom, self.spatial_dom = time_series_domain()
self.ph = ParameterHelper(self.dataset_management_client,
self.addCleanup)
self.wait_time = CFG.get_safe('endpoint.receive.timeout', 10)
def push_granule(self, data_product_id):
'''
Publishes and monitors that the granule arrived
'''
datasets, _ = self.rrclient.find_objects(data_product_id,
PRED.hasDataset,
id_only=True)
dataset_monitor = DatasetMonitor(datasets[0])
rdt = self.ph.rdt_for_data_product(data_product_id)
self.ph.fill_parsed_rdt(rdt)
self.ph.publish_rdt_to_data_product(data_product_id, rdt)
assert dataset_monitor.wait()
dataset_monitor.stop()
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_transform_worker(self):
# test that a data process (type: data-product-in / data-product-out) can be defined and launched.
# verify that the output granule fields are correctly populated
# test that the input and output data products are linked to facilitate provenance
self.dp_list = []
self.data_process_objs = []
self._output_stream_ids = []
self.granule_verified = Event()
self.worker_assigned_event_verified = Event()
self.dp_created_event_verified = Event()
self.heartbeat_event_verified = Event()
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(
name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(
name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition,
self.stream_def_id)
# create the DataProduct that is the input to the data processes
input_dp_obj = IonObject(RT.DataProduct,
name='input_data_product',
description='input test stream')
self.input_dp_id = self.dataproductclient.create_data_product(
data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(
self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
self.start_event_listener()
# create the DPD, DataProcess and output DataProduct
dataprocessdef_id, dataprocess_id, dataproduct_id = self.create_data_process(
)
self.dp_list.append(dataprocess_id)
# validate the repository for data product algorithms persists the new resources NEW SA-1
# create_data_process call created one of each
dpd_ids, _ = self.rrclient.find_resources(
restype=OT.DataProcessDefinition, id_only=False)
# there will be more than one becuase of the DPDs that reperesent the PFs in the data product above
self.assertTrue(dpd_ids is not None)
dp_ids, _ = self.rrclient.find_resources(restype=OT.DataProcess,
id_only=False)
# only one DP becuase the PFs that are in the code dataproduct above are not activated yet.
self.assertEquals(len(dp_ids), 1)
# validate the name and version label NEW SA - 2
dataprocessdef_obj = self.dataprocessclient.read_data_process_definition(
dataprocessdef_id)
self.assertEqual(dataprocessdef_obj.version_label, '1.0a')
self.assertEqual(dataprocessdef_obj.name, 'add_arrays')
# validate that the DPD has an attachment NEW SA - 21
attachment_ids, assoc_ids = self.rrclient.find_objects(
dataprocessdef_id, PRED.hasAttachment, RT.Attachment, True)
self.assertEqual(len(attachment_ids), 1)
attachment_obj = self.rrclient.read_attachment(attachment_ids[0])
log.debug('attachment: %s', attachment_obj)
# validate that the data process resource has input and output data products associated
# L4-CI-SA-RQ-364 and NEW SA-3
outproduct_ids, assoc_ids = self.rrclient.find_objects(
dataprocess_id, PRED.hasOutputProduct, RT.DataProduct, True)
self.assertEqual(len(outproduct_ids), 1)
inproduct_ids, assoc_ids = self.rrclient.find_objects(
dataprocess_id, PRED.hasInputProduct, RT.DataProduct, True)
self.assertEqual(len(inproduct_ids), 1)
# Test for provenance. Get Data product produced by the data processes
output_data_product_id, _ = self.rrclient.find_objects(
subject=dataprocess_id,
object_type=RT.DataProduct,
predicate=PRED.hasOutputProduct,
id_only=True)
output_data_product_provenance = self.dataproductclient.get_data_product_provenance(
output_data_product_id[0])
# Do a basic check to see if there were 3 entries in the provenance graph. Parent and Child and the
# DataProcessDefinition creating the child from the parent.
self.assertTrue(len(output_data_product_provenance) == 2)
self.assertTrue(self.input_dp_id in output_data_product_provenance[
output_data_product_id[0]]['parents'])
self.assertTrue(output_data_product_provenance[
output_data_product_id[0]]['parents'][self.input_dp_id]
['data_process_definition_id'] == dataprocessdef_id)
# NEW SA - 4 | Data processing shall include the appropriate data product algorithm name and version number in
# the metadata of each output data product created by the data product algorithm.
output_data_product_obj, _ = self.rrclient.find_objects(
subject=dataprocess_id,
object_type=RT.DataProduct,
predicate=PRED.hasOutputProduct,
id_only=False)
self.assertTrue(output_data_product_obj[0].name != None)
self.assertTrue(output_data_product_obj[0]._rev != None)
# retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(
subject=dataprocess_id,
predicate=PRED.hasSubscription,
object_type=RT.Subscription,
id_only=False)
log.debug('test_transform_worker subscription_obj: %s',
subscription_objs[0])
# create a queue to catch the published granules
self.subscription_id = self.pubsub_client.create_subscription(
name='parsed_subscription',
stream_ids=[self.stream_id],
exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription,
self.subscription_id)
self.pubsub_client.activate_subscription(self.subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription,
self.subscription_id)
stream_route = self.pubsub_client.read_stream_route(self.stream_id)
self.publisher = StandaloneStreamPublisher(stream_id=self.stream_id,
stream_route=stream_route)
for n in range(1, 101):
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher.publish(rdt.to_granule())
# validate that the output granule is received and the updated value is correct
self.assertTrue(self.granule_verified.wait(self.wait_time))
# validate that the data process loaded into worker event is received (L4-CI-SA-RQ-182)
self.assertTrue(
self.worker_assigned_event_verified.wait(self.wait_time))
# validate that the data process create (with data product ids) event is received (NEW SA -42)
self.assertTrue(self.dp_created_event_verified.wait(self.wait_time))
# validate that the data process heartbeat event is received (for every hundred granules processed) (L4-CI-SA-RQ-182)
#this takes a while so set wait limit to large value
self.assertTrue(self.heartbeat_event_verified.wait(200))
# validate that the code from the transform function can be retrieve via inspect_data_process_definition
src = self.dataprocessclient.inspect_data_process_definition(
dataprocessdef_id)
self.assertIn('def add_arrays(a, b)', src)
# now delete the DPD and DP then verify that the resources are retired so that information required for provenance are still available
self.dataprocessclient.delete_data_process(dataprocess_id)
self.dataprocessclient.delete_data_process_definition(
dataprocessdef_id)
in_dp_objs, _ = self.rrclient.find_objects(
subject=dataprocess_id,
predicate=PRED.hasInputProduct,
object_type=RT.DataProduct,
id_only=True)
self.assertTrue(in_dp_objs is not None)
dpd_objs, _ = self.rrclient.find_subjects(
subject_type=RT.DataProcessDefinition,
predicate=PRED.hasDataProcess,
object=dataprocess_id,
id_only=True)
self.assertTrue(dpd_objs is not None)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_transform_worker_with_instrumentdevice(self):
# test that a data process (type: data-product-in / data-product-out) can be defined and launched.
# verify that the output granule fields are correctly populated
# test that the input and output data products are linked to facilitate provenance
self.data_process_objs = []
self._output_stream_ids = []
self.event_verified = Event()
# Create CTD Parsed as the initial data product
# create a stream definition for the data from the ctd simulator
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
self.stream_def_id = self.pubsub_client.create_stream_definition(
name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
# create the DataProduct that is the input to the data processes
input_dp_obj = IonObject(RT.DataProduct,
name='input_data_product',
description='input test stream')
self.input_dp_id = self.dataproductclient.create_data_product(
data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(
self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
log.debug('new ctd_parsed_data_product_id = %s' % self.input_dp_id)
# only ever need one device for testing purposes.
instDevice_obj, _ = self.rrclient.find_resources(
restype=RT.InstrumentDevice, name='test_ctd_device')
if instDevice_obj:
instDevice_id = instDevice_obj[0]._id
else:
instDevice_obj = IonObject(RT.InstrumentDevice,
name='test_ctd_device',
description="test_ctd_device",
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=self.input_dp_id)
# create the DPD, DataProcess and output DataProduct
dataprocessdef_id, dataprocess_id, dataproduct_id = self.create_data_process(
)
self.addCleanup(self.dataprocessclient.delete_data_process,
dataprocess_id)
self.addCleanup(self.dataprocessclient.delete_data_process_definition,
dataprocessdef_id)
# Test for provenance. Get Data product produced by the data processes
output_data_product_id, _ = self.rrclient.find_objects(
subject=dataprocess_id,
object_type=RT.DataProduct,
predicate=PRED.hasOutputProduct,
id_only=True)
output_data_product_provenance = self.dataproductclient.get_data_product_provenance(
output_data_product_id[0])
# Do a basic check to see if there were 3 entries in the provenance graph. Parent and Child and the
# DataProcessDefinition creating the child from the parent.
self.assertTrue(len(output_data_product_provenance) == 3)
self.assertTrue(self.input_dp_id in output_data_product_provenance[
output_data_product_id[0]]['parents'])
self.assertTrue(instDevice_id in output_data_product_provenance[
self.input_dp_id]['parents'])
self.assertTrue(output_data_product_provenance[instDevice_id]['type']
== 'InstrumentDevice')
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_transform_worker_with_platformdevice(self):
# test that a data process (type: data-product-in / data-product-out) can be defined and launched.
# verify that the output granule fields are correctly populated
# test that the input and output data products are linked to facilitate provenance
self.data_process_objs = []
self._output_stream_ids = []
self.event_verified = Event()
# Create CTD Parsed as the initial data product
# create a stream definition for the data from the ctd simulator
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(
'ctd_parsed_param_dict', id_only=True)
self.stream_def_id = self.pubsub_client.create_stream_definition(
name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
# create the DataProduct that is the input to the data processes
input_dp_obj = IonObject(RT.DataProduct,
name='input_data_product',
description='input test stream')
self.input_dp_id = self.dataproductclient.create_data_product(
data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(
self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
log.debug('new ctd_parsed_data_product_id = %s' % self.input_dp_id)
# only ever need one device for testing purposes.
platform_device_obj, _ = self.rrclient.find_resources(
restype=RT.PlatformDevice, name='TestPlatform')
if platform_device_obj:
platform_device_id = platform_device_obj[0]._id
else:
platform_device_obj = IonObject(RT.PlatformDevice,
name='TestPlatform',
description="TestPlatform",
serial_number="12345")
platform_device_id = self.imsclient.create_platform_device(
platform_device=platform_device_obj)
self.damsclient.assign_data_product(
input_resource_id=platform_device_id,
data_product_id=self.input_dp_id)
# create the DPD, DataProcess and output DataProduct
dataprocessdef_id, dataprocess_id, dataproduct_id = self.create_data_process(
)
self.addCleanup(self.dataprocessclient.delete_data_process,
dataprocess_id)
self.addCleanup(self.dataprocessclient.delete_data_process_definition,
dataprocessdef_id)
# Test for provenance. Get Data product produced by the data processes
output_data_product_id, _ = self.rrclient.find_objects(
subject=dataprocess_id,
object_type=RT.DataProduct,
predicate=PRED.hasOutputProduct,
id_only=True)
output_data_product_provenance = self.dataproductclient.get_data_product_provenance(
output_data_product_id[0])
# Do a basic check to see if there were 3 entries in the provenance graph. Parent and Child and the
# DataProcessDefinition creating the child from the parent.
self.assertTrue(len(output_data_product_provenance) == 3)
self.assertTrue(self.input_dp_id in output_data_product_provenance[
output_data_product_id[0]]['parents'])
self.assertTrue(platform_device_id in output_data_product_provenance[
self.input_dp_id]['parents'])
self.assertTrue(output_data_product_provenance[platform_device_id]
['type'] == 'PlatformDevice')
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_event_transform_worker(self):
self.data_process_objs = []
self._output_stream_ids = []
self.event_verified = Event()
# test that a data process (type: data-product-in / event-out) can be defined and launched.
# verify that event fields are correctly populated
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(
name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(
name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition,
self.stream_def_id)
# create the DataProduct
input_dp_obj = IonObject(RT.DataProduct,
name='input_data_product',
description='input test stream')
self.input_dp_id = self.dataproductclient.create_data_product(
data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(
self.input_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_id = stream_ids[0]
# create the DPD and two DPs
self.event_data_process_id = self.create_event_data_processes()
# retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(
subject=self.event_data_process_id,
predicate=PRED.hasSubscription,
object_type=RT.Subscription,
id_only=False)
log.debug('test_event_transform_worker subscription_obj: %s',
subscription_objs[0])
# create a queue to catch the published granules
self.subscription_id = self.pubsub_client.create_subscription(
name='parsed_subscription',
stream_ids=[self.stream_id],
exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription,
self.subscription_id)
self.pubsub_client.activate_subscription(self.subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription,
self.subscription_id)
stream_route = self.pubsub_client.read_stream_route(self.stream_id)
self.publisher = StandaloneStreamPublisher(stream_id=self.stream_id,
stream_route=stream_route)
self.start_event_transform_listener()
self.data_modified = Event()
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher.publish(rdt.to_granule())
self.assertTrue(self.event_verified.wait(self.wait_time))
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_bad_argument_map(self):
self._output_stream_ids = []
# test that a data process (type: data-product-in / data-product-out) parameter mapping it validated during
# data process creation and that the correct exception is raised for both input and output.
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(
name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(
name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition,
self.stream_def_id)
# create the DataProduct that is the input to the data processes
input_dp_obj = IonObject(RT.DataProduct,
name='input_data_product',
description='input test stream')
self.input_dp_id = self.dataproductclient.create_data_product(
data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
# two data processes using one transform and one DPD
dp1_func_output_dp_id = self.create_output_data_product()
# Set up DPD and DP #2 - array add function
tf_obj = IonObject(
RT.TransformFunction,
name='add_array_func',
description='adds values in an array',
function='add_arrays',
module="ion_example.add_arrays",
arguments=['arr1', 'arr2'],
function_type=TransformFunctionType.TRANSFORM,
uri=
'http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(
RT.DataProcessDefinition,
name='add_arrays',
description='adds the values of two arrays',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS)
add_array_dpd_id = self.dataprocessclient.create_data_process_definition(
data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(
self.stream_def_id, add_array_dpd_id, binding='add_array_func')
# create the data process with invalid argument map
argument_map = {"arr1": "foo", "arr2": "bar"}
output_param = "salinity"
with self.assertRaises(BadRequest) as cm:
dp1_data_process_id = self.dataprocessclient.create_data_process(
data_process_definition_id=add_array_dpd_id,
inputs=[self.input_dp_id],
outputs=[dp1_func_output_dp_id],
argument_map=argument_map,
out_param_name=output_param)
ex = cm.exception
log.debug(' exception raised: %s', cm)
self.assertEqual(
ex.message,
"Input data product does not contain the parameters defined in argument map"
)
# create the data process with invalid output parameter name
argument_map = {"arr1": "conductivity", "arr2": "pressure"}
output_param = "foo"
with self.assertRaises(BadRequest) as cm:
dp1_data_process_id = self.dataprocessclient.create_data_process(
data_process_definition_id=add_array_dpd_id,
inputs=[self.input_dp_id],
outputs=[dp1_func_output_dp_id],
argument_map=argument_map,
out_param_name=output_param)
ex = cm.exception
log.debug(' exception raised: %s', cm)
self.assertEqual(
ex.message,
"Output data product does not contain the output parameter name provided"
)
def create_event_data_processes(self):
# two data processes using one transform and one DPD
argument_map = {"a": "salinity"}
# set up DPD and DP #2 - array add function
tf_obj = IonObject(
RT.TransformFunction,
name='validate_salinity_array',
description='validate_salinity_array',
function='validate_salinity_array',
module="ion.processes.data.transforms.test.test_transform_worker",
arguments=['a'],
function_type=TransformFunctionType.TRANSFORM)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(
RT.DataProcessDefinition,
name='validate_salinity_array',
description='validate_salinity_array',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS,
)
add_array_dpd_id = self.dataprocessclient.create_data_process_definition(
data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(
self.stream_def_id,
add_array_dpd_id,
binding='validate_salinity_array')
# create the data process
dp1_data_process_id = self.dataprocessclient.create_data_process(
data_process_definition_id=add_array_dpd_id,
inputs=[self.input_dp_id],
outputs=None,
argument_map=argument_map)
self.damsclient.register_process(dp1_data_process_id)
self.addCleanup(self.dataprocessclient.delete_data_process,
dp1_data_process_id)
return dp1_data_process_id
def create_data_process(self):
# two data processes using one transform and one DPD
dp1_func_output_dp_id = self.create_output_data_product()
argument_map = {"arr1": "conductivity", "arr2": "pressure"}
output_param = "salinity"
# set up DPD and DP #2 - array add function
tf_obj = IonObject(
RT.TransformFunction,
name='add_array_func',
description='adds values in an array',
function='add_arrays',
module="ion_example.add_arrays",
arguments=['arr1', 'arr2'],
function_type=TransformFunctionType.TRANSFORM,
uri=
'http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(
RT.DataProcessDefinition,
name='add_arrays',
description='adds the values of two arrays',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS,
version_label='1.0a')
add_array_dpd_id = self.dataprocessclient.create_data_process_definition(
data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(
self.stream_def_id, add_array_dpd_id, binding='add_array_func')
# create the data process
dp1_data_process_id = self.dataprocessclient.create_data_process(
data_process_definition_id=add_array_dpd_id,
inputs=[self.input_dp_id],
outputs=[dp1_func_output_dp_id],
argument_map=argument_map,
out_param_name=output_param)
self.damsclient.register_process(dp1_data_process_id)
#self.addCleanup(self.dataprocessclient.delete_data_process, dp1_data_process_id)
# add an attachment object to this DPD to test new SA-21
import msgpack
attachment_content = 'foo bar'
attachment_obj = IonObject(RT.Attachment,
name='test_attachment',
attachment_type=AttachmentType.ASCII,
content_type='text/plain',
content=msgpack.packb(attachment_content))
att_id = self.rrclient.create_attachment(add_array_dpd_id,
attachment_obj)
self.addCleanup(self.rrclient.delete_attachment, att_id)
return add_array_dpd_id, dp1_data_process_id, dp1_func_output_dp_id
def create_output_data_product(self):
dp1_outgoing_stream_id = self.pubsub_client.create_stream_definition(
name='dp1_stream', parameter_dictionary_id=self.parameter_dict_id)
dp1_output_dp_obj = IonObject(RT.DataProduct,
name='data_process1_data_product',
description='output of add array func')
dp1_func_output_dp_id = self.dataproductclient.create_data_product(
dp1_output_dp_obj, dp1_outgoing_stream_id)
self.addCleanup(self.dataproductclient.delete_data_product,
dp1_func_output_dp_id)
# retrieve the id of the OUTPUT stream from the out Data Product and add to granule logger
stream_ids, _ = self.rrclient.find_objects(dp1_func_output_dp_id,
PRED.hasStream, None, True)
self._output_stream_ids.append(stream_ids[0])
subscription_id = self.pubsub_client.create_subscription(
'validator', data_product_ids=[dp1_func_output_dp_id])
self.addCleanup(self.pubsub_client.delete_subscription,
subscription_id)
def on_granule(msg, route, stream_id):
log.debug('recv_packet stream_id: %s route: %s msg: %s',
stream_id, route, msg)
self.validate_output_granule(msg, route, stream_id)
self.granule_verified.set()
validator = StandaloneStreamSubscriber('validator',
callback=on_granule)
validator.start()
self.addCleanup(validator.stop)
self.pubsub_client.activate_subscription(subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription,
subscription_id)
return dp1_func_output_dp_id
def validate_event(self, *args, **kwargs):
"""
This method is a callback function for receiving DataProcessStatusEvent.
"""
data_process_event = args[0]
log.debug("DataProcessStatusEvent: %s",
str(data_process_event.__dict__))
# if data process already created, check origin
if self.dp_list:
self.assertIn(data_process_event.origin, self.dp_list)
# if this is a heartbeat event then 100 granules have been processed
if 'data process status update.' in data_process_event.description:
self.heartbeat_event_verified.set()
else:
# else check that this is the assign event
if 'Data process assigned to transform worker' in data_process_event.description:
self.worker_assigned_event_verified.set()
elif 'Data process created for data product' in data_process_event.description:
self.dp_created_event_verified.set()
def validate_output_granule(self, msg, route, stream_id):
self.assertIn(stream_id, self._output_stream_ids)
rdt = RecordDictionaryTool.load_from_granule(msg)
log.debug('validate_output_granule rdt: %s', rdt)
sal_val = rdt['salinity']
np.testing.assert_array_equal(sal_val, np.array([3]))
def start_event_listener(self):
es = EventSubscriber(event_type=OT.DataProcessStatusEvent,
callback=self.validate_event)
es.start()
self.addCleanup(es.stop)
def validate_transform_event(self, *args, **kwargs):
"""
This method is a callback function for receiving DataProcessStatusEvent.
"""
status_alert_event = args[0]
np.testing.assert_array_equal(status_alert_event.origin,
self.stream_id)
np.testing.assert_array_equal(status_alert_event.values,
np.array([self.event_data_process_id]))
log.debug("DeviceStatusAlertEvent: %s",
str(status_alert_event.__dict__))
self.event_verified.set()
def start_event_transform_listener(self):
es = EventSubscriber(event_type=OT.DeviceStatusAlertEvent,
callback=self.validate_transform_event)
es.start()
self.addCleanup(es.stop)
def test_download(self):
egg_url = 'http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
egg_path = TransformWorker.download_egg(egg_url)
import pkg_resources
pkg_resources.working_set.add_entry(egg_path)
from ion_example.add_arrays import add_arrays
a = add_arrays(1, 2)
self.assertEquals(a, 3)
class TestTransformPrime(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml') # Because hey why not?!
self.dataset_management = DatasetManagementServiceClient()
self.data_process_management = DataProcessManagementServiceClient()
self.pubsub_management = PubsubManagementServiceClient()
self.data_product_management = DataProductManagementServiceClient()
def _create_proc_def(self):
dpd_obj = DataProcessDefinition(
name='Optimus',
description='It\'s a transformer',
module='ion.processes.data.transforms.transform_prime',
class_name='TransformPrime')
return self.data_process_management.create_data_process_definition(dpd_obj)
def _L0_pdict(self):
t_ctxt = ParameterContext('time', param_type=QuantityType(value_encoding=np.dtype('int64')))
t_ctxt.uom = 'seconds since 01-01-1900'
t_ctxt.fill_value = -9999
t_ctxt_id = self.dataset_management.create_parameter_context(name='time', parameter_context=t_ctxt.dump(), parameter_type='quantity<int64>', unit_of_measure=t_ctxt.uom)
lat_ctxt = ParameterContext('lat', param_type=ConstantType(QuantityType(value_encoding=np.dtype('float32'))))
lat_ctxt.axis = AxisTypeEnum.LAT
lat_ctxt.uom = 'degree_north'
lat_ctxt.fill_value = -9999
lat_ctxt_id = self.dataset_management.create_parameter_context(name='lat', parameter_context=lat_ctxt.dump(), parameter_type='quantity<float32>', unit_of_measure=lat_ctxt.uom)
lon_ctxt = ParameterContext('lon', param_type=ConstantType(QuantityType(value_encoding=np.dtype('float32'))))
lon_ctxt.axis = AxisTypeEnum.LON
lon_ctxt.uom = 'degree_east'
lon_ctxt.fill_value = -9999
lon_ctxt_id = self.dataset_management.create_parameter_context(name='lon', parameter_context=lon_ctxt.dump(), parameter_type='quantity<float32>', unit_of_measure=lon_ctxt.uom)
temp_ctxt = ParameterContext('TEMPWAT_L0', param_type=QuantityType(value_encoding=np.dtype('float32')))
temp_ctxt.uom = 'deg_C'
temp_ctxt.fill_value = -9999
temp_ctxt_id = self.dataset_management.create_parameter_context(name='TEMPWAT_L0', parameter_context=temp_ctxt.dump(), parameter_type='quantity<float32>', unit_of_measure=temp_ctxt.uom)
# Conductivity - values expected to be the decimal results of conversion from hex
cond_ctxt = ParameterContext('CONDWAT_L0', param_type=QuantityType(value_encoding=np.dtype('float32')))
cond_ctxt.uom = 'S m-1'
cond_ctxt.fill_value = -9999
cond_ctxt_id = self.dataset_management.create_parameter_context(name='CONDWAT_L0', parameter_context=cond_ctxt.dump(), parameter_type='quantity<float32>', unit_of_measure=cond_ctxt.uom)
# Pressure - values expected to be the decimal results of conversion from hex
press_ctxt = ParameterContext('PRESWAT_L0', param_type=QuantityType(value_encoding=np.dtype('float32')))
press_ctxt.uom = 'dbar'
press_ctxt.fill_value = -9999
press_ctxt_id = self.dataset_management.create_parameter_context(name='PRESWAT_L0', parameter_context=press_ctxt.dump(), parameter_type='quantity<float32>', unit_of_measure=press_ctxt.uom)
context_ids = [t_ctxt_id, lat_ctxt_id, lon_ctxt_id, temp_ctxt_id, cond_ctxt_id, press_ctxt_id]
pdict_id = self.dataset_management.create_parameter_dictionary('L0 SBE37', parameter_context_ids=context_ids, temporal_context='time')
return pdict_id
def _L1_pdict(self):
pdict_id = self._L0_pdict()
param_context_ids = self.dataset_management.read_parameter_contexts(pdict_id,id_only=True)
# TEMPWAT_L1 = (TEMPWAT_L0 / 10000) - 10
tl1_func = '(TEMPWAT_L0 / 10000) - 10'
tl1_pmap = {'TEMPWAT_L0':'TEMPWAT_L0'}
func = NumexprFunction('TEMPWAT_L1', tl1_func, tl1_pmap)
tempL1_ctxt = ParameterContext('TEMPWAT_L1', param_type=ParameterFunctionType(function=func), variability=VariabilityEnum.TEMPORAL)
tempL1_ctxt.uom = 'deg_C'
tempL1_ctxt_id = self.dataset_management.create_parameter_context(name=tempL1_ctxt.name, parameter_context=tempL1_ctxt.dump(), parameter_type='pfunc', unit_of_measure=tempL1_ctxt.uom)
param_context_ids.append(tempL1_ctxt_id)
# CONDWAT_L1 = (CONDWAT_L0 / 100000) - 0.5
cl1_func = '(CONDWAT_L0 / 100000) - 0.5'
cl1_pmap = {'CONDWAT_L0':'CONDWAT_L0'}
func = NumexprFunction('CONDWAT_L1', cl1_func, cl1_pmap)
condL1_ctxt = ParameterContext('CONDWAT_L1', param_type=ParameterFunctionType(function=func), variability=VariabilityEnum.TEMPORAL)
condL1_ctxt.uom = 'S m-1'
condL1_ctxt_id = self.dataset_management.create_parameter_context(name=condL1_ctxt.name, parameter_context=condL1_ctxt.dump(), parameter_type='pfunc', unit_of_measure=condL1_ctxt.uom)
param_context_ids.append(condL1_ctxt_id)
# Equation uses p_range, which is a calibration coefficient - Fixing to 679.34040721
# PRESWAT_L1 = (PRESWAT_L0 * p_range / (0.85 * 65536)) - (0.05 * p_range)
pl1_func = '(PRESWAT_L0 * 679.34040721 / (0.85 * 65536)) - (0.05 * 679.34040721)'
pl1_pmap = {'PRESWAT_L0':'PRESWAT_L0'}
func = NumexprFunction('PRESWAT_L1', pl1_func, pl1_pmap)
presL1_ctxt = ParameterContext('PRESWAT_L1', param_type=ParameterFunctionType(function=func), variability=VariabilityEnum.TEMPORAL)
presL1_ctxt.uom = 'S m-1'
presL1_ctxt_id = self.dataset_management.create_parameter_context(name=presL1_ctxt.name, parameter_context=presL1_ctxt.dump(), parameter_type='pfunc', unit_of_measure=presL1_ctxt.uom)
param_context_ids.append(presL1_ctxt_id)
# Density & practical salinity calucluated using the Gibbs Seawater library - available via python-gsw project:
# https://code.google.com/p/python-gsw/ & http://pypi.python.org/pypi/gsw/3.0.1
# PRACSAL = gsw.SP_from_C((CONDWAT_L1 * 10), TEMPWAT_L1, PRESWAT_L1)
owner = 'gsw'
sal_func = 'SP_from_C'
sal_arglist = [NumexprFunction('CONDWAT_L1*10', 'C*10', {'C':'CONDWAT_L1'}), 'TEMPWAT_L1', 'PRESWAT_L1']
sal_kwargmap = None
func = PythonFunction('PRACSAL', owner, sal_func, sal_arglist, sal_kwargmap)
sal_ctxt = ParameterContext('PRACSAL', param_type=ParameterFunctionType(func), variability=VariabilityEnum.TEMPORAL)
sal_ctxt.uom = 'g kg-1'
sal_ctxt_id = self.dataset_management.create_parameter_context(name=sal_ctxt.name, parameter_context=sal_ctxt.dump(), parameter_type='pfunc', unit_of_measure=sal_ctxt.uom)
param_context_ids.append(sal_ctxt_id)
# absolute_salinity = gsw.SA_from_SP(PRACSAL, PRESWAT_L1, longitude, latitude)
# conservative_temperature = gsw.CT_from_t(absolute_salinity, TEMPWAT_L1, PRESWAT_L1)
# DENSITY = gsw.rho(absolute_salinity, conservative_temperature, PRESWAT_L1)
owner = 'gsw'
abs_sal_func = PythonFunction('abs_sal', owner, 'SA_from_SP', ['PRACSAL', 'PRESWAT_L1', 'lon','lat'], None)
#abs_sal_func = PythonFunction('abs_sal', owner, 'SA_from_SP', ['lon','lat'], None)
cons_temp_func = PythonFunction('cons_temp', owner, 'CT_from_t', [abs_sal_func, 'TEMPWAT_L1', 'PRESWAT_L1'], None)
dens_func = PythonFunction('DENSITY', owner, 'rho', [abs_sal_func, cons_temp_func, 'PRESWAT_L1'], None)
dens_ctxt = ParameterContext('DENSITY', param_type=ParameterFunctionType(dens_func), variability=VariabilityEnum.TEMPORAL)
dens_ctxt.uom = 'kg m-3'
dens_ctxt_id = self.dataset_management.create_parameter_context(name=dens_ctxt.name, parameter_context=dens_ctxt.dump(), parameter_type='pfunc', unit_of_measure=dens_ctxt.uom)
param_context_ids.append(dens_ctxt_id)
pdict_id = self.dataset_management.create_parameter_dictionary('L1_SBE37', parameter_context_ids=param_context_ids, temporal_context='time')
return pdict_id
def _data_product(self, name, stream_def, exchange_pt):
tdom, sdom = time_series_domain()
dp_obj = DataProduct(name=name, description='blah', spatial_domain=sdom.dump(), temporal_domain=tdom.dump())
dp_id = self.data_product_management.create_data_product(dp_obj, stream_def, exchange_pt)
return dp_id
def _data_process(self, proc_def_id, input_products, output_product, stream_def):
fake_producer = DataProducer(name='fake_producer')
fake_producer_id, _ = self.container.resource_registry.create(fake_producer)
self.data_process_management.assign_stream_definition_to_data_process_definition(stream_def,proc_def_id,binding='output')
data_process_id = self.data_process_management.create_data_process(proc_def_id, input_products, {'output':output_product})
self.container.resource_registry.create_association(subject=data_process_id, predicate=PRED.hasDataProducer, object=fake_producer_id)
self.data_process_management.activate_data_process(data_process_id)
def _fake_producer(self):
if not hasattr(self, 'producer'):
self.fake_producer_id,_ = self.container.resource_registry.create(DataProducer(name='fake_producer'))
return self.fake_producer_id
def _publisher(self, data_product_id):
stream_ids, _ = self.container.resource_registry.find_resources(subject=data_product_id, predicate=PRED.hasStream, id_only=True)
stream_id = stream_ids[0]
route = self.pubsub_management.read_stream_route(stream_id)
publisher = StandaloneStreamPublisher(stream_id, route)
return publisher
def _get_param_vals(self, name, slice_, dims):
shp = utils.slice_shape(slice_, dims)
def _getarr(vmin, shp, vmax=None,):
if vmax is None:
return np.empty(shp).fill(vmin)
return np.arange(vmin, vmax, (vmax - vmin) / int(utils.prod(shp)), dtype='float32').reshape(shp)
if name == 'LAT':
ret = np.empty(shp)
ret.fill(45)
elif name == 'LON':
ret = np.empty(shp)
ret.fill(-71)
elif name == 'TEMPWAT_L0':
ret = _getarr(280000, shp, 350000)
elif name == 'CONDWAT_L0':
ret = _getarr(100000, shp, 750000)
elif name == 'PRESWAT_L0':
ret = _getarr(3000, shp, 10000)
elif name in self.value_classes: # Non-L0 parameters
ret = self.value_classes[name][:]
else:
return np.zeros(shp)
return ret
def _setup_streams(self, exchange_pt1, exchange_pt2, available_fields_in=[], available_fields_out=[]):
proc_def_id = self._create_proc_def()
incoming_pdict_id = self._L0_pdict()
outgoing_pdict_id = self._L1_pdict()
incoming_stream_def_id = self.pubsub_management.create_stream_definition('L0_stream_def', parameter_dictionary_id=incoming_pdict_id, available_fields=available_fields_in)
outgoing_stream_def_id = self.pubsub_management.create_stream_definition('L1_stream_def', parameter_dictionary_id=outgoing_pdict_id, available_fields=available_fields_out)
L0_data_product_id = self._data_product('L0_SBE37', incoming_stream_def_id, exchange_pt1)
L1_data_product_id = self._data_product('L1_SBE37', outgoing_stream_def_id, exchange_pt2)
self._data_process(proc_def_id, [L0_data_product_id], L1_data_product_id, outgoing_stream_def_id)
stream_ids, _ = self.container.resource_registry.find_objects(L0_data_product_id, PRED.hasStream, None, True)
stream_id_in = stream_ids[0]
stream_ids, _ = self.container.resource_registry.find_objects(L1_data_product_id, PRED.hasStream, None, True)
stream_id_out = stream_ids[0]
stream_route_in = self.pubsub_management.read_stream_route(stream_id_in)
stream_route_out = self.pubsub_management.read_stream_route(stream_id_out)
return (stream_id_in,stream_id_out,stream_route_in,stream_route_out,incoming_stream_def_id,outgoing_stream_def_id)
def _validate_transforms(self, rdt_in, rdt_out):
#passthrus
self.assertTrue(np.allclose(rdt_in['time'], rdt_out['time']))
self.assertTrue(np.allclose(rdt_in['lat'], rdt_out['lat']))
self.assertTrue(np.allclose(rdt_in['lon'], rdt_out['lon']))
self.assertTrue(np.allclose(rdt_in['TEMPWAT_L0'], rdt_out['TEMPWAT_L0']))
self.assertTrue(np.allclose(rdt_in['CONDWAT_L0'], rdt_out['CONDWAT_L0']))
self.assertTrue(np.allclose(rdt_in['PRESWAT_L0'], rdt_out['PRESWAT_L0']))
# TEMPWAT_L1 = (TEMPWAT_L0 / 10000) - 10
t1 = (rdt_out['TEMPWAT_L0'] / 10000) - 10
self.assertTrue(np.allclose(rdt_out['TEMPWAT_L1'], t1))
# CONDWAT_L1 = (CONDWAT_L0 / 100000) - 0.5
c1 = (rdt_out['CONDWAT_L0'] / 100000) - 0.5
self.assertTrue(np.allclose(rdt_out['CONDWAT_L1'], c1))
# Equation uses p_range, which is a calibration coefficient - Fixing to 679.34040721
# PRESWAT_L1 = (PRESWAT_L0 * p_range / (0.85 * 65536)) - (0.05 * p_range)
p1 = (rdt_out['PRESWAT_L0'] * 679.34040721 / (0.85 * 65536)) - (0.05 * 679.34040721)
self.assertTrue(np.allclose(rdt_out['PRESWAT_L1'], p1))
# PRACSAL = gsw.SP_from_C((CONDWAT_L1 * 10), TEMPWAT_L1, PRESWAT_L1)
ps = gsw.SP_from_C((rdt_out['CONDWAT_L1'] * 10.), rdt_out['TEMPWAT_L1'], rdt_out['PRESWAT_L1'])
self.assertTrue(np.allclose(rdt_out['PRACSAL'], ps))
# absolute_salinity = gsw.SA_from_SP(PRACSAL, PRESWAT_L1, longitude, latitude)
# conservative_temperature = gsw.CT_from_t(absolute_salinity, TEMPWAT_L1, PRESWAT_L1)
# DENSITY = gsw.rho(absolute_salinity, conservative_temperature, PRESWAT_L1)
abs_sal = gsw.SA_from_SP(rdt_out['PRACSAL'], rdt_out['PRESWAT_L1'], rdt_out['lon'], rdt_out['lat'])
cons_temp = gsw.CT_from_t(abs_sal, rdt_out['TEMPWAT_L1'], rdt_out['PRESWAT_L1'])
rho = gsw.rho(abs_sal, cons_temp, rdt_out['PRESWAT_L1'])
self.assertTrue(np.allclose(rdt_out['DENSITY'], rho))
def test_execute_transform(self):
available_fields_in = ['time', 'lat', 'lon', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0']
available_fields_out = ['time', 'lat', 'lon', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0', 'TEMPWAT_L1','CONDWAT_L1','PRESWAT_L1','PRACSAL', 'DENSITY']
exchange_pt1 = 'xp1'
exchange_pt2 = 'xp2'
stream_id_in,stream_id_out,stream_route_in,stream_route_out,stream_def_in_id,stream_def_out_id = self._setup_streams(exchange_pt1, exchange_pt2, available_fields_in, available_fields_out)
rdt_in = RecordDictionaryTool(stream_definition_id=stream_def_in_id)
dt = 20
rdt_in['time'] = np.arange(dt)
rdt_in['lat'] = [40.992469] * dt
rdt_in['lon'] = [-71.727069] * dt
rdt_in['TEMPWAT_L0'] = self._get_param_vals('TEMPWAT_L0', slice(None), (dt,))
rdt_in['CONDWAT_L0'] = self._get_param_vals('CONDWAT_L0', slice(None), (dt,))
rdt_in['PRESWAT_L0'] = self._get_param_vals('PRESWAT_L0', slice(None), (dt,))
msg = rdt_in.to_granule()
#pid = self.container.spawn_process('transform_stream','ion.processes.data.transforms.transform_prime','TransformPrime',{'process':{'routes':{(stream_id_in, stream_id_out):None},'stream_id':stream_id_out}})
config = {'process':{'routes':{(stream_id_in, stream_id_out):None},'queue_name':exchange_pt1, 'publish_streams':{str(stream_id_out):stream_id_out}, 'process_type':'stream_process'}}
pid = self.container.spawn_process('transform_stream','ion.processes.data.transforms.transform_prime','TransformPrime',config)
rdt_out = self.container.proc_manager.procs[pid]._execute_transform(msg, (stream_id_in,stream_id_out))
#need below to wrap result in a param val object
rdt_out = RecordDictionaryTool.load_from_granule(rdt_out.to_granule())
for k,v in rdt_out.iteritems():
self.assertEqual(len(v), dt)
self._validate_transforms(rdt_in, rdt_out)
self.container.proc_manager.terminate_process(pid)
def test_transform_prime_no_available_fields(self):
available_fields_in = []
available_fields_out = []
exchange_pt1 = 'xp1'
exchange_pt2 = 'xp2'
stream_id_in,stream_id_out,stream_route_in,stream_route_out,stream_def_in_id,stream_def_out_id = self._setup_streams(exchange_pt1, exchange_pt2, available_fields_in, available_fields_out)
#launch transform
config = {'process':{'routes':{(stream_id_in, stream_id_out):None},'queue_name':exchange_pt1, 'publish_streams':{str(stream_id_out):stream_id_out}, 'process_type':'stream_process'}}
pid = self.container.spawn_process('transform_stream','ion.processes.data.transforms.transform_prime','TransformPrime',config)
#create publish
publisher = StandaloneStreamPublisher(stream_id_in, stream_route_in)
self.container.proc_manager.procs[pid].subscriber.xn.bind(stream_route_in.routing_key, publisher.xp)
#data
rdt_in = RecordDictionaryTool(stream_definition_id=stream_def_in_id)
dt = 20
rdt_in['time'] = np.arange(dt)
rdt_in['lat'] = [40.992469] * dt
rdt_in['lon'] = [-71.727069] * dt
rdt_in['TEMPWAT_L0'] = self._get_param_vals('TEMPWAT_L0', slice(None), (dt,))
rdt_in['CONDWAT_L0'] = self._get_param_vals('CONDWAT_L0', slice(None), (dt,))
rdt_in['PRESWAT_L0'] = self._get_param_vals('PRESWAT_L0', slice(None), (dt,))
msg = rdt_in.to_granule()
#publish granule to transform and have transform publish it to subsciber
#validate transformed data
e = gevent.event.Event()
def cb(msg, sr, sid):
self.assertEqual(sid, stream_id_out)
rdt_out = RecordDictionaryTool.load_from_granule(msg)
self.assertEquals(set([k for k,v in rdt_out.iteritems()]), set(available_fields_out))
for k,v in rdt_out.iteritems():
self.assertEquals(rdt_out[k], None)
e.set()
sub = StandaloneStreamSubscriber('stream_subscriber', cb)
sub.xn.bind(stream_route_out.routing_key, getattr(self.container.proc_manager.procs[pid], stream_id_out).xp)
self.addCleanup(sub.stop)
sub.start()
#publish msg to transform
publisher.publish(msg)
#wait to receive msg
self.assertTrue(e.wait(4))
#self.container.proc_manager.terminate_process(pid)
def test_transform_prime(self):
available_fields_in = ['time', 'lat', 'lon', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0']
available_fields_out = ['time', 'lat', 'lon', 'TEMPWAT_L0', 'CONDWAT_L0', 'PRESWAT_L0', 'TEMPWAT_L1','CONDWAT_L1','PRESWAT_L1','PRACSAL', 'DENSITY']
exchange_pt1 = 'xp1'
exchange_pt2 = 'xp2'
stream_id_in,stream_id_out,stream_route_in,stream_route_out,stream_def_in_id,stream_def_out_id = self._setup_streams(exchange_pt1, exchange_pt2, available_fields_in, available_fields_out)
#launch transform
config = {'process':{'routes':{(stream_id_in, stream_id_out):None},'queue_name':exchange_pt1, 'publish_streams':{str(stream_id_out):stream_id_out}, 'process_type':'stream_process'}}
pid = self.container.spawn_process('transform_stream','ion.processes.data.transforms.transform_prime','TransformPrime',config)
#create publish
publisher = StandaloneStreamPublisher(stream_id_in, stream_route_in)
self.container.proc_manager.procs[pid].subscriber.xn.bind(stream_route_in.routing_key, publisher.xp)
#data
rdt_in = RecordDictionaryTool(stream_definition_id=stream_def_in_id)
dt = 20
rdt_in['time'] = np.arange(dt)
rdt_in['lat'] = [40.992469] * dt
rdt_in['lon'] = [-71.727069] * dt
rdt_in['TEMPWAT_L0'] = self._get_param_vals('TEMPWAT_L0', slice(None), (dt,))
rdt_in['CONDWAT_L0'] = self._get_param_vals('CONDWAT_L0', slice(None), (dt,))
rdt_in['PRESWAT_L0'] = self._get_param_vals('PRESWAT_L0', slice(None), (dt,))
msg = rdt_in.to_granule()
#publish granule to transform and have transform publish it to subsciber
#validate transformed data
e = gevent.event.Event()
def cb(msg, sr, sid):
self.assertEqual(sid, stream_id_out)
rdt_out = RecordDictionaryTool.load_from_granule(msg)
self.assertEquals(set([k for k,v in rdt_out.iteritems()]), set(available_fields_out))
self._validate_transforms(rdt_in, rdt_out)
e.set()
sub = StandaloneStreamSubscriber('stream_subscriber', cb)
sub.xn.bind(stream_route_out.routing_key, getattr(self.container.proc_manager.procs[pid], stream_id_out).xp)
self.addCleanup(sub.stop)
sub.start()
#publish msg to transform
publisher.publish(msg)
#wait to receive msg
self.assertTrue(e.wait(4))
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 TestTransformWorkerSubscriptions(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.dataset_management_client = DatasetManagementServiceClient(
node=self.container.node)
self.pubsub_client = PubsubManagementServiceClient(
node=self.container.node)
self.dataproductclient = DataProductManagementServiceClient(
node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(
node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(
node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(
node=self.container.node)
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.wait_time = CFG.get_safe('endpoint.receive.timeout', 10)
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_multi_subscriptions(self):
self.dp_list = []
self.event1_verified = Event()
self.event2_verified = Event()
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(
name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(
name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition,
self.stream_def_id)
# create the DataProduct
input_dp_obj = IonObject(RT.DataProduct,
name='input_data_product_one',
description='input test stream one')
self.input_dp_one_id = self.dataproductclient.create_data_product(
data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
input_dp_obj = IonObject(RT.DataProduct,
name='input_data_product_two',
description='input test stream two')
self.input_dp_two_id = self.dataproductclient.create_data_product(
data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
#retrieve the Stream for this data product
stream_ids, assoc_ids = self.rrclient.find_objects(
self.input_dp_one_id, PRED.hasStream, RT.Stream, True)
self.stream_one_id = stream_ids[0]
stream_ids, assoc_ids = self.rrclient.find_objects(
self.input_dp_two_id, PRED.hasStream, RT.Stream, True)
self.stream_two_id = stream_ids[0]
dpd_id = self.create_data_process_definition()
dp1_func_output_dp_id, dp2_func_output_dp_id = self.create_output_data_products(
)
first_dp_id = self.create_data_process_one(dpd_id,
dp1_func_output_dp_id)
second_dp_id = self.create_data_process_two(dpd_id,
self.input_dp_two_id,
dp2_func_output_dp_id)
#retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(
subject=first_dp_id,
predicate=PRED.hasSubscription,
object_type=RT.Subscription,
id_only=False)
log.debug('test_transform_worker subscription_obj: %s',
subscription_objs[0])
#create subscription to stream ONE, create data process and publish granule on stream ONE
#create a queue to catch the published granules of stream ONE
self.subscription_one_id = self.pubsub_client.create_subscription(
name='parsed_subscription_one',
stream_ids=[self.stream_one_id],
exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription,
self.subscription_one_id)
self.pubsub_client.activate_subscription(self.subscription_one_id)
self.addCleanup(self.pubsub_client.deactivate_subscription,
self.subscription_one_id)
stream_route_one = self.pubsub_client.read_stream_route(
self.stream_one_id)
self.publisher_one = StandaloneStreamPublisher(
stream_id=self.stream_one_id, stream_route=stream_route_one)
self.start_event_listener()
#data process 1 adds conductivity + pressure and puts the result in salinity
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher_one.publish(msg=rdt.to_granule(),
stream_id=self.stream_one_id)
#retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(
subject=second_dp_id,
predicate=PRED.hasSubscription,
object_type=RT.Subscription,
id_only=False)
log.debug('test_transform_worker subscription_obj: %s',
subscription_objs[0])
#create subscription to stream ONE and TWO, move TW subscription, create data process and publish granule on stream TWO
#create a queue to catch the published granules of stream TWO
self.subscription_two_id = self.pubsub_client.create_subscription(
name='parsed_subscription_one_two',
stream_ids=[self.stream_two_id],
exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription,
self.subscription_two_id)
self.pubsub_client.activate_subscription(self.subscription_two_id)
self.addCleanup(self.pubsub_client.deactivate_subscription,
self.subscription_two_id)
stream_route_two = self.pubsub_client.read_stream_route(
self.stream_two_id)
self.publisher_two = StandaloneStreamPublisher(
stream_id=self.stream_two_id, stream_route=stream_route_two)
#data process 1 adds conductivity + pressure and puts the result in salinity
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher_one.publish(msg=rdt.to_granule(),
stream_id=self.stream_one_id)
#data process 2 adds salinity + pressure and puts the result in conductivity
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [22]
rdt['pressure'] = [4]
rdt['salinity'] = [1]
self.publisher_two.publish(msg=rdt.to_granule(),
stream_id=self.stream_two_id)
self.assertTrue(self.event2_verified.wait(self.wait_time))
self.assertTrue(self.event1_verified.wait(self.wait_time))
@attr('LOCOINT')
@unittest.skipIf(os.getenv('CEI_LAUNCH_TEST', False),
'Skip test while in CEI LAUNCH mode')
def test_two_transforms_inline(self):
self.dp_list = []
self.event1_verified = Event()
self.event2_verified = Event()
self.parameter_dict_id = self.dataset_management_client.read_parameter_dictionary_by_name(
name='ctd_parsed_param_dict', id_only=True)
# create the StreamDefinition
self.stream_def_id = self.pubsub_client.create_stream_definition(
name='stream_def', parameter_dictionary_id=self.parameter_dict_id)
self.addCleanup(self.pubsub_client.delete_stream_definition,
self.stream_def_id)
# create the DataProduct
input_dp_obj = IonObject(RT.DataProduct,
name='input_data_product_one',
description='input test stream one')
self.input_dp_one_id = self.dataproductclient.create_data_product(
data_product=input_dp_obj, stream_definition_id=self.stream_def_id)
dpd_id = self.create_data_process_definition()
dp1_func_output_dp_id, dp2_func_output_dp_id = self.create_output_data_products(
)
first_dp_id = self.create_data_process_one(dpd_id,
dp1_func_output_dp_id)
second_dp_id = self.create_data_process_two(dpd_id,
dp1_func_output_dp_id,
dp2_func_output_dp_id)
#retrieve subscription from data process one
subscription_objs, _ = self.rrclient.find_objects(
subject=first_dp_id,
predicate=PRED.hasSubscription,
object_type=RT.Subscription,
id_only=False)
log.debug('test_transform_worker subscription_obj: %s',
subscription_objs[0])
#retrieve the Stream for these data product
stream_ids, assoc_ids = self.rrclient.find_objects(
self.input_dp_one_id, PRED.hasStream, RT.Stream, True)
self.stream_one_id = stream_ids[0]
#the input to data process two is the output from data process one
stream_ids, assoc_ids = self.rrclient.find_objects(
dp1_func_output_dp_id, PRED.hasStream, RT.Stream, True)
self.stream_two_id = stream_ids[0]
# Run provenance on the output dataproduct of the second data process to see all the links
# are as expected
output_data_product_provenance = self.dataproductclient.get_data_product_provenance(
dp2_func_output_dp_id)
# Do a basic check to see if there were 2 entries in the provenance graph. Parent and Child.
self.assertTrue(len(output_data_product_provenance) == 3)
# confirm that the linking from the output dataproduct to input dataproduct is correct
self.assertTrue(
dp1_func_output_dp_id in
output_data_product_provenance[dp2_func_output_dp_id]['parents'])
self.assertTrue(
self.input_dp_one_id in
output_data_product_provenance[dp1_func_output_dp_id]['parents'])
#create subscription to stream ONE, create data process and publish granule on stream ONE
#create a queue to catch the published granules of stream ONE
subscription_id = self.pubsub_client.create_subscription(
name='parsed_subscription',
stream_ids=[self.stream_one_id, self.stream_two_id],
exchange_name=subscription_objs[0].exchange_name)
self.addCleanup(self.pubsub_client.delete_subscription,
subscription_id)
self.pubsub_client.activate_subscription(subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription,
subscription_id)
stream_route_one = self.pubsub_client.read_stream_route(
self.stream_one_id)
self.publisher_one = StandaloneStreamPublisher(
stream_id=self.stream_one_id, stream_route=stream_route_one)
#retrieve subscription from data process
subscription_objs, _ = self.rrclient.find_objects(
subject=second_dp_id,
predicate=PRED.hasSubscription,
object_type=RT.Subscription,
id_only=False)
log.debug('test_transform_worker subscription_obj: %s',
subscription_objs[0])
#data process 1 adds conductivity + pressure and puts the result in salinity
#data process 2 adds salinity + pressure and puts the result in conductivity
self.start_event_listener()
rdt = RecordDictionaryTool(stream_definition_id=self.stream_def_id)
rdt['time'] = [0] # time should always come first
rdt['conductivity'] = [1]
rdt['pressure'] = [2]
rdt['salinity'] = [8]
self.publisher_one.publish(msg=rdt.to_granule(),
stream_id=self.stream_one_id)
self.assertTrue(self.event2_verified.wait(self.wait_time))
self.assertTrue(self.event1_verified.wait(self.wait_time))
def create_data_process_definition(self):
#two data processes using one transform and one DPD
# Set up DPD and DP #2 - array add function
tf_obj = IonObject(
RT.TransformFunction,
name='add_array_func',
description='adds values in an array',
function='add_arrays',
module="ion_example.add_arrays",
arguments=['arr1', 'arr2'],
function_type=TransformFunctionType.TRANSFORM,
uri=
'http://sddevrepo.oceanobservatories.org/releases/ion_example-0.1-py2.7.egg'
)
add_array_func_id, rev = self.rrclient.create(tf_obj)
dpd_obj = IonObject(
RT.DataProcessDefinition,
name='add_arrays',
description='adds the values of two arrays',
data_process_type=DataProcessTypeEnum.TRANSFORM_PROCESS,
)
add_array_dpd_id = self.dataprocessclient.create_data_process_definition(
data_process_definition=dpd_obj, function_id=add_array_func_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(
self.stream_def_id, add_array_dpd_id, binding='add_array_func')
return add_array_dpd_id
def create_data_process_one(self, data_process_definition_id,
output_dataproduct):
# Create the data process
#data process 1 adds conductivity + pressure and puts the result in salinity
argument_map = {"arr1": "conductivity", "arr2": "pressure"}
output_param = "salinity"
dp1_data_process_id = self.dataprocessclient.create_data_process(
data_process_definition_id=data_process_definition_id,
inputs=[self.input_dp_one_id],
outputs=[output_dataproduct],
argument_map=argument_map,
out_param_name=output_param)
self.damsclient.register_process(dp1_data_process_id)
self.addCleanup(self.dataprocessclient.delete_data_process,
dp1_data_process_id)
self.dp_list.append(dp1_data_process_id)
return dp1_data_process_id
def create_data_process_two(self, data_process_definition_id,
input_dataproduct, output_dataproduct):
# Create the data process
#data process 2 adds salinity + pressure and puts the result in conductivity
argument_map = {'arr1': 'salinity', 'arr2': 'pressure'}
output_param = 'conductivity'
dp2_func_data_process_id = self.dataprocessclient.create_data_process(
data_process_definition_id=data_process_definition_id,
inputs=[input_dataproduct],
outputs=[output_dataproduct],
argument_map=argument_map,
out_param_name=output_param)
self.damsclient.register_process(dp2_func_data_process_id)
self.addCleanup(self.dataprocessclient.delete_data_process,
dp2_func_data_process_id)
self.dp_list.append(dp2_func_data_process_id)
return dp2_func_data_process_id
def create_output_data_products(self):
dp1_outgoing_stream_id = self.pubsub_client.create_stream_definition(
name='dp1_stream', parameter_dictionary_id=self.parameter_dict_id)
dp1_output_dp_obj = IonObject(RT.DataProduct,
name='data_process1_data_product',
description='output of add array func')
dp1_func_output_dp_id = self.dataproductclient.create_data_product(
dp1_output_dp_obj, dp1_outgoing_stream_id)
self.addCleanup(self.dataproductclient.delete_data_product,
dp1_func_output_dp_id)
# Retrieve the id of the OUTPUT stream from the out Data Product and add to granule logger
stream_ids, _ = self.rrclient.find_objects(dp1_func_output_dp_id,
PRED.hasStream, None, True)
self._output_stream_one_id = stream_ids[0]
dp2_func_outgoing_stream_id = self.pubsub_client.create_stream_definition(
name='dp2_stream', parameter_dictionary_id=self.parameter_dict_id)
dp2_func_output_dp_obj = IonObject(
RT.DataProduct,
name='data_process2_data_product',
description='output of add array func')
dp2_func_output_dp_id = self.dataproductclient.create_data_product(
dp2_func_output_dp_obj, dp2_func_outgoing_stream_id)
self.addCleanup(self.dataproductclient.delete_data_product,
dp2_func_output_dp_id)
# Retrieve the id of the OUTPUT stream from the out Data Product and add to granule logger
stream_ids, _ = self.rrclient.find_objects(dp2_func_output_dp_id,
PRED.hasStream, None, True)
self._output_stream_two_id = stream_ids[0]
subscription_id = self.pubsub_client.create_subscription(
'validator',
data_product_ids=[dp1_func_output_dp_id, dp2_func_output_dp_id])
self.addCleanup(self.pubsub_client.delete_subscription,
subscription_id)
def on_granule(msg, route, stream_id):
log.debug('recv_packet stream_id: %s route: %s msg: %s',
stream_id, route, msg)
self.validate_output_granule(msg, route, stream_id)
validator = StandaloneStreamSubscriber('validator',
callback=on_granule)
validator.start()
self.addCleanup(validator.stop)
self.pubsub_client.activate_subscription(subscription_id)
self.addCleanup(self.pubsub_client.deactivate_subscription,
subscription_id)
return dp1_func_output_dp_id, dp2_func_output_dp_id
def validate_event(self, *args, **kwargs):
"""
This method is a callback function for receiving DataProcessStatusEvent.
"""
data_process_event = args[0]
log.debug("DataProcessStatusEvent: %s",
str(data_process_event.__dict__))
#if data process already created, check origin
if not 'data process assigned to transform worker' in data_process_event.description:
self.assertIn(data_process_event.origin, self.dp_list)
def validate_output_granule(self, msg, route, stream_id):
self.assertTrue(
stream_id in
[self._output_stream_one_id, self._output_stream_two_id])
rdt = RecordDictionaryTool.load_from_granule(msg)
log.debug('validate_output_granule stream_id: %s', stream_id)
if stream_id == self._output_stream_one_id:
sal_val = rdt['salinity']
log.debug('validate_output_granule sal_val: %s', sal_val)
np.testing.assert_array_equal(sal_val, np.array([3]))
self.event1_verified.set()
else:
cond_val = rdt['conductivity']
log.debug('validate_output_granule cond_val: %s', cond_val)
np.testing.assert_array_equal(cond_val, np.array([5]))
self.event2_verified.set()
def start_event_listener(self):
es = EventSubscriber(event_type=OT.DataProcessStatusEvent,
callback=self.validate_event)
es.start()
self.addCleanup(es.stop)
class CtdbpTransformsIntTest(IonIntegrationTestCase):
def setUp(self):
super(CtdbpTransformsIntTest, self).setUp()
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.pubsub = PubsubManagementServiceClient()
self.process_dispatcher = ProcessDispatcherServiceClient()
self.dataset_management = DatasetManagementServiceClient()
self.data_process_management = DataProcessManagementServiceClient()
self.dataproduct_management = DataProductManagementServiceClient()
self.resource_registry = ResourceRegistryServiceClient()
# This is for the time values inside the packets going into the transform
self.i = 0
# Cleanup of queue created by the subscriber
def _get_new_ctd_packet(self, stream_definition_id, length):
rdt = RecordDictionaryTool(stream_definition_id=stream_definition_id)
rdt['time'] = numpy.arange(self.i, self.i + length)
for field in rdt:
if isinstance(
rdt._pdict.get_context(field).param_type, QuantityType):
rdt[field] = numpy.array(
[random.uniform(0.0, 75.0) for i in xrange(length)])
g = rdt.to_granule()
self.i += length
return g
def _create_input_param_dict_for_test(self, parameter_dict_name=''):
pdict = ParameterDictionary()
t_ctxt = ParameterContext(
'time',
param_type=QuantityType(value_encoding=numpy.dtype('float64')))
t_ctxt.axis = AxisTypeEnum.TIME
t_ctxt.uom = 'seconds since 01-01-1900'
pdict.add_context(t_ctxt)
cond_ctxt = ParameterContext(
'conductivity',
param_type=QuantityType(value_encoding=numpy.dtype('float32')))
cond_ctxt.uom = ''
pdict.add_context(cond_ctxt)
pres_ctxt = ParameterContext(
'pressure',
param_type=QuantityType(value_encoding=numpy.dtype('float32')))
pres_ctxt.uom = ''
pdict.add_context(pres_ctxt)
temp_ctxt = ParameterContext(
'temperature',
param_type=QuantityType(value_encoding=numpy.dtype('float32')))
temp_ctxt.uom = ''
pdict.add_context(temp_ctxt)
dens_ctxt = ParameterContext(
'density',
param_type=QuantityType(value_encoding=numpy.dtype('float32')))
dens_ctxt.uom = ''
pdict.add_context(dens_ctxt)
sal_ctxt = ParameterContext(
'salinity',
param_type=QuantityType(value_encoding=numpy.dtype('float32')))
sal_ctxt.uom = ''
pdict.add_context(sal_ctxt)
#create temp streamdef so the data product can create the stream
pc_list = []
for pc_k, pc in pdict.iteritems():
ctxt_id = self.dataset_management.create_parameter_context(
pc_k, pc[1].dump())
pc_list.append(ctxt_id)
self.addCleanup(self.dataset_management.delete_parameter_context,
ctxt_id)
pdict_id = self.dataset_management.create_parameter_dictionary(
parameter_dict_name, pc_list)
self.addCleanup(self.dataset_management.delete_parameter_dictionary,
pdict_id)
return pdict_id
def test_ctdbp_L0_all(self):
"""
Test packets processed by the ctdbp_L0_all transform
"""
#----------- Data Process Definition --------------------------------
dpd_obj = IonObject(
RT.DataProcessDefinition,
name='CTDBP_L0_all',
description=
'Take parsed stream and put the C, T and P into three separate L0 streams.',
module='ion.processes.data.transforms.ctdbp.ctdbp_L0',
class_name='CTDBP_L0_all')
dprocdef_id = self.data_process_management.create_data_process_definition(
dpd_obj)
self.addCleanup(
self.data_process_management.delete_data_process_definition,
dprocdef_id)
log.debug("created data process definition: id = %s", dprocdef_id)
#----------- Data Products --------------------------------
# Construct temporal and spatial Coordinate Reference System objects
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
input_param_dict = self._create_input_param_dict_for_test(
parameter_dict_name='fictitious_ctdp_param_dict')
# Get the stream definition for the stream using the parameter dictionary
# input_param_dict = self.dataset_management.read_parameter_dictionary_by_name('ctdbp_cdef_sample', id_only=True)
input_stream_def_dict = self.pubsub.create_stream_definition(
name='parsed', parameter_dictionary_id=input_param_dict)
self.addCleanup(self.pubsub.delete_stream_definition,
input_stream_def_dict)
log.debug("Got the parsed parameter dictionary: id: %s",
input_param_dict)
log.debug("Got the stream def for parsed input: %s",
input_stream_def_dict)
# Input data product
parsed_stream_dp_obj = IonObject(
RT.DataProduct,
name='parsed_stream',
description='Parsed stream input to CTBP L0 transform',
temporal_domain=tdom,
spatial_domain=sdom)
input_dp_id = self.dataproduct_management.create_data_product(
data_product=parsed_stream_dp_obj,
stream_definition_id=input_stream_def_dict)
self.addCleanup(self.dataproduct_management.delete_data_product,
input_dp_id)
# output data product
L0_stream_dp_obj = IonObject(
RT.DataProduct,
name='L0_stream',
description='L0_stream output of CTBP L0 transform',
temporal_domain=tdom,
spatial_domain=sdom)
L0_stream_dp_id = self.dataproduct_management.create_data_product(
data_product=L0_stream_dp_obj,
stream_definition_id=input_stream_def_dict)
self.addCleanup(self.dataproduct_management.delete_data_product,
L0_stream_dp_id)
# We need the key name here to be "L0_stream", since when the data process is launched, this name goes into
# the config as in config.process.publish_streams.L0_stream when the config is used to launch the data process
out_stream_ids, _ = self.resource_registry.find_objects(
L0_stream_dp_id, PRED.hasStream, RT.Stream, True)
self.assertTrue(len(out_stream_ids))
output_stream_id = out_stream_ids[0]
dproc_id = self.data_process_management.create_data_process(
data_process_definition_id=dprocdef_id,
in_data_product_ids=[input_dp_id],
out_data_product_ids=[L0_stream_dp_id],
configuration=None)
self.addCleanup(self.data_process_management.delete_data_process,
dproc_id)
log.debug("Created a data process for ctdbp_L0. id: %s", dproc_id)
# Activate the data process
self.data_process_management.activate_data_process(dproc_id)
self.addCleanup(self.data_process_management.deactivate_data_process,
dproc_id)
#----------- Find the stream that is associated with the input data product when it was created by create_data_product() --------------------------------
stream_ids, _ = self.resource_registry.find_objects(
input_dp_id, PRED.hasStream, RT.Stream, True)
self.assertTrue(len(stream_ids))
input_stream_id = stream_ids[0]
stream_route = self.pubsub.read_stream_route(input_stream_id)
log.debug("The input stream for the L0 transform: %s", input_stream_id)
#----------- Create a subscriber that will listen to the transform's output --------------------------------
ar = gevent.event.AsyncResult()
def subscriber(m, r, s):
ar.set(m)
sub = StandaloneStreamSubscriber(exchange_name='sub',
callback=subscriber)
sub_id = self.pubsub.create_subscription('subscriber_to_transform',
stream_ids=[output_stream_id],
exchange_name='sub')
self.addCleanup(self.pubsub.delete_subscription, sub_id)
self.pubsub.activate_subscription(sub_id)
self.addCleanup(self.pubsub.deactivate_subscription, sub_id)
sub.start()
self.addCleanup(sub.stop)
#----------- Publish on that stream so that the transform can receive it --------------------------------
pub = StandaloneStreamPublisher(input_stream_id, stream_route)
publish_granule = self._get_new_ctd_packet(
stream_definition_id=input_stream_def_dict, length=5)
pub.publish(publish_granule)
log.debug("Published the following granule: %s", publish_granule)
granule_from_transform = ar.get(timeout=20)
log.debug("Got the following granule from the transform: %s",
granule_from_transform)
# Check that the granule published by the L0 transform has the right properties
self._check_granule_from_transform(granule_from_transform)
def _check_granule_from_transform(self, granule):
"""
An internal method to check if a granule has the right properties
"""
pass
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 BulkIngestBase(object):
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 build_param_contexts(self):
raise NotImplementedError('build_param_contexts must be implemented in child classes')
def create_external_dataset(self):
raise NotImplementedError('create_external_dataset must be implemented in child classes')
def get_dvr_config(self):
raise NotImplementedError('get_dvr_config must be implemented in child classes')
def get_retrieve_client(self, dataset_id=''):
raise NotImplementedError('get_retrieve_client must be implemented in child classes')
def test_data_ingest(self):
self.pdict_id = self.create_parameter_dict(self.name)
self.stream_def_id = self.create_stream_def(self.name, self.pdict_id)
self.data_product_id = self.create_data_product(self.name, self.description, self.stream_def_id)
self.dataset_id = self.get_dataset_id(self.data_product_id)
self.stream_id, self.route = self.get_stream_id_and_route(self.data_product_id)
self.external_dataset_id = self.create_external_dataset()
self.data_producer_id = self.register_external_dataset(self.external_dataset_id)
self.start_agent()
def create_parameter_dict(self, name=''):
return self.dataset_management.create_parameter_dictionary(name=name, parameter_context_ids=self.context_ids, temporal_context='time')
def create_stream_def(self, name='', pdict_id=''):
return self.pubsub_management.create_stream_definition(name=name, parameter_dictionary_id=pdict_id)
def create_data_product(self, name='', description='', stream_def_id=''):
tdom, sdom = time_series_domain()
tdom = tdom.dump()
sdom = sdom.dump()
dp_obj = DataProduct(
name=name,
description=description,
processing_level_code='Parsed_Canonical',
temporal_domain=tdom,
spatial_domain=sdom)
data_product_id = self.data_product_management.create_data_product(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 register_external_dataset(self, external_dataset_id=''):
return self.data_acquisition_management.register_external_data_set(external_dataset_id=external_dataset_id)
def get_dataset_id(self, data_product_id=''):
dataset_ids, assocs = self.resource_registry.find_objects(subject=data_product_id, predicate='hasDataset', id_only=True)
return dataset_ids[0]
def get_stream_id_and_route(self, data_product_id):
stream_ids, _ = self.resource_registry.find_objects(data_product_id, PRED.hasStream, RT.Stream, id_only=True)
stream_id = stream_ids[0]
route = self.pubsub_management.read_stream_route(stream_id)
#self.create_logger(self.name, stream_id)
return stream_id, route
def start_agent(self):
agent_config = {
'driver_config': self.get_dvr_config(),
'stream_config': {},
'agent': {'resource_id': self.external_dataset_id},
'test_mode': True
}
_ia_pid = self.container.spawn_process(
name=self.EDA_NAME,
module=self.EDA_MOD,
cls=self.EDA_CLS,
config=agent_config)
self._ia_client = ResourceAgentClient(self.external_dataset_id, process=FakeProcess())
cmd = AgentCommand(command=ResourceAgentEvent.INITIALIZE)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.GO_ACTIVE)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.RUN)
self._ia_client.execute_agent(cmd)
cmd = AgentCommand(command=DriverEvent.START_AUTOSAMPLE)
self._ia_client.execute_resource(command=cmd)
self.start_listener(self.dataset_id)
def stop_agent(self):
cmd = AgentCommand(command=DriverEvent.STOP_AUTOSAMPLE)
self._ia_client.execute_resource(cmd)
cmd = AgentCommand(command=ResourceAgentEvent.RESET)
self._ia_client.execute_agent(cmd)
def start_listener(self, dataset_id=''):
dataset_modified = Event()
#callback to use retrieve to get data from the coverage
def cb(*args, **kwargs):
self.get_retrieve_client(dataset_id=dataset_id)
#callback to keep execution going once dataset has been fully ingested
def cb2(*args, **kwargs):
dataset_modified.set()
es = EventSubscriber(event_type=OT.DatasetModified, callback=cb, origin=dataset_id)
es.start()
es2 = EventSubscriber(event_type=OT.DeviceCommonLifecycleEvent, callback=cb2, origin='BaseDataHandler._acquire_sample')
es2.start()
self.addCleanup(es.stop)
self.addCleanup(es2.stop)
#let it go for up to 120 seconds, then stop the agent and reset it
dataset_modified.wait(120)
self.stop_agent()
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.process_dispatch_client.create_process_definition(process_definition=producer_definition)
configuration = {
'process':{
'stream_id':stream_id,
}
}
pid = self.process_dispatch_client.schedule_process(process_definition_id=logger_procdef_id, configuration=configuration)
return pid
class TestOmsLaunch(IonIntegrationTestCase):
def setUp(self):
self._start_container()
self.container.start_rel_from_url('res/deploy/r2deploy.yml')
self.rrclient = ResourceRegistryServiceClient(node=self.container.node)
self.omsclient = ObservatoryManagementServiceClient(node=self.container.node)
self.imsclient = InstrumentManagementServiceClient(node=self.container.node)
self.damsclient = DataAcquisitionManagementServiceClient(node=self.container.node)
self.dpclient = DataProductManagementServiceClient(node=self.container.node)
self.pubsubcli = PubsubManagementServiceClient(node=self.container.node)
self.processdispatchclient = ProcessDispatcherServiceClient(node=self.container.node)
self.dataprocessclient = DataProcessManagementServiceClient(node=self.container.node)
self.dataset_management = DatasetManagementServiceClient()
# Use the network definition provided by RSN OMS directly.
rsn_oms = CIOMSClientFactory.create_instance(DVR_CONFIG['oms_uri'])
self._network_definition = RsnOmsUtil.build_network_definition(rsn_oms)
# get serialized version for the configuration:
self._network_definition_ser = NetworkUtil.serialize_network_definition(self._network_definition)
if log.isEnabledFor(logging.DEBUG):
log.debug("NetworkDefinition serialization:\n%s", self._network_definition_ser)
self.platformModel_id = None
self.all_platforms = {}
self.agent_streamconfig_map = {}
self._async_data_result = AsyncResult()
self._data_subscribers = []
self._samples_received = []
self.addCleanup(self._stop_data_subscribers)
self._async_event_result = AsyncResult()
self._event_subscribers = []
self._events_received = []
self.addCleanup(self._stop_event_subscribers)
self._start_event_subscriber()
self._set_up_DataProduct_obj()
self._set_up_PlatformModel_obj()
def _set_up_DataProduct_obj(self):
# Create data product object to be used for each of the platform log streams
tdom, sdom = time_series_domain()
sdom = sdom.dump()
tdom = tdom.dump()
self.pdict_id = self.dataset_management.read_parameter_dictionary_by_name('platform_eng_parsed', id_only=True)
self.platform_eng_stream_def_id = self.pubsubcli.create_stream_definition(
name='platform_eng', parameter_dictionary_id=self.pdict_id)
self.dp_obj = IonObject(RT.DataProduct,
name='platform_eng data',
description='platform_eng test',
temporal_domain = tdom,
spatial_domain = sdom)
def _set_up_PlatformModel_obj(self):
# Create PlatformModel
platformModel_obj = IonObject(RT.PlatformModel,
name='RSNPlatformModel',
description="RSNPlatformModel")
try:
self.platformModel_id = self.imsclient.create_platform_model(platformModel_obj)
except BadRequest as ex:
self.fail("failed to create new PLatformModel: %s" %ex)
log.debug( 'new PlatformModel id = %s', self.platformModel_id)
def _traverse(self, pnode, platform_id, parent_platform_objs=None):
"""
Recursive routine that repeatedly calls _prepare_platform to build
the object dictionary for each platform.
@param pnode PlatformNode
@param platform_id ID of the platform to be visited
@param parent_platform_objs dict of objects associated to parent
platform, if any.
@retval the dict returned by _prepare_platform at this level.
"""
log.info("Starting _traverse for %r", platform_id)
plat_objs = self._prepare_platform(pnode, platform_id, parent_platform_objs)
self.all_platforms[platform_id] = plat_objs
# now, traverse the children:
for sub_pnode in pnode.subplatforms.itervalues():
subplatform_id = sub_pnode.platform_id
self._traverse(sub_pnode, subplatform_id, plat_objs)
return plat_objs
def _prepare_platform(self, pnode, platform_id, parent_platform_objs):
"""
This routine generalizes the manual construction originally done in
test_oms_launch.py. It is called by the recursive _traverse method so
all platforms starting from a given base platform are prepared.
Note: For simplicity in this test, sites are organized in the same
hierarchical way as the platforms themselves.
@param pnode PlatformNode
@param platform_id ID of the platform to be visited
@param parent_platform_objs dict of objects associated to parent
platform, if any.
@retval a dict of associated objects similar to those in
test_oms_launch
"""
site__obj = IonObject(RT.PlatformSite,
name='%s_PlatformSite' % platform_id,
description='%s_PlatformSite platform site' % platform_id)
site_id = self.omsclient.create_platform_site(site__obj)
if parent_platform_objs:
# establish hasSite association with the parent
self.rrclient.create_association(
subject=parent_platform_objs['site_id'],
predicate=PRED.hasSite,
object=site_id)
# prepare platform attributes and ports:
monitor_attribute_objs, monitor_attribute_dicts = self._prepare_platform_attributes(pnode, platform_id)
port_objs, port_dicts = self._prepare_platform_ports(pnode, platform_id)
device__obj = IonObject(RT.PlatformDevice,
name='%s_PlatformDevice' % platform_id,
description='%s_PlatformDevice platform device' % platform_id,
# ports=port_objs,
# platform_monitor_attributes = monitor_attribute_objs
)
device__dict = dict(ports=port_dicts,
platform_monitor_attributes=monitor_attribute_dicts)
self.device_id = self.imsclient.create_platform_device(device__obj)
self.imsclient.assign_platform_model_to_platform_device(self.platformModel_id, self.device_id)
self.rrclient.create_association(subject=site_id, predicate=PRED.hasDevice, object=self.device_id)
self.damsclient.register_instrument(instrument_id=self.device_id)
if parent_platform_objs:
# establish hasDevice association with the parent
self.rrclient.create_association(
subject=parent_platform_objs['device_id'],
predicate=PRED.hasDevice,
object=self.device_id)
agent__obj = IonObject(RT.PlatformAgent,
name='%s_PlatformAgent' % platform_id,
description='%s_PlatformAgent platform agent' % platform_id)
agent_id = self.imsclient.create_platform_agent(agent__obj)
if parent_platform_objs:
# add this platform_id to parent's children:
parent_platform_objs['children'].append(platform_id)
self.imsclient.assign_platform_model_to_platform_agent(self.platformModel_id, agent_id)
# agent_instance_obj = IonObject(RT.PlatformAgentInstance,
# name='%s_PlatformAgentInstance' % platform_id,
# description="%s_PlatformAgentInstance" % platform_id)
#
# agent_instance_id = self.imsclient.create_platform_agent_instance(
# agent_instance_obj, agent_id, device_id)
plat_objs = {
'platform_id': platform_id,
'site__obj': site__obj,
'site_id': site_id,
'device__obj': device__obj,
'device_id': self.device_id,
'agent__obj': agent__obj,
'agent_id': agent_id,
# 'agent_instance_obj': agent_instance_obj,
# 'agent_instance_id': agent_instance_id,
'children': []
}
log.info("plat_objs for platform_id %r = %s", platform_id, str(plat_objs))
stream_config = self._create_stream_config(plat_objs)
self.agent_streamconfig_map[platform_id] = stream_config
# self.agent_streamconfig_map[platform_id] = None
# self._start_data_subscriber(agent_instance_id, stream_config)
return plat_objs
def _prepare_platform_attributes(self, pnode, platform_id):
"""
Returns the list of PlatformMonitorAttributes objects corresponding to
the attributes associated to the given platform.
"""
# TODO complete the clean-up of this method
ret_infos = dict((n, a.defn) for (n, a) in pnode.attrs.iteritems())
monitor_attribute_objs = []
monitor_attribute_dicts = []
for attrName, attrDfn in ret_infos.iteritems():
log.debug("platform_id=%r: preparing attribute=%r", platform_id, attrName)
monitor_rate = attrDfn['monitorCycleSeconds']
units = attrDfn['units']
plat_attr_obj = IonObject(OT.PlatformMonitorAttributes,
id=attrName,
monitor_rate=monitor_rate,
units=units)
plat_attr_dict = dict(id=attrName,
monitor_rate=monitor_rate,
units=units)
monitor_attribute_objs.append(plat_attr_obj)
monitor_attribute_dicts.append(plat_attr_dict)
return monitor_attribute_objs, monitor_attribute_dicts
def _prepare_platform_ports(self, pnode, platform_id):
"""
Returns the list of PlatformPort objects corresponding to the ports
associated to the given platform.
"""
# TODO complete the clean-up of this method
port_objs = []
port_dicts = []
for port_id, network in pnode.ports.iteritems():
log.debug("platform_id=%r: preparing port=%r network=%s",
platform_id, port_id, network)
#
# Note: the name "IP" address has been changed to "network" address
# in the CI-OMS interface spec.
#
plat_port_obj = IonObject(OT.PlatformPort,
port_id=port_id,
ip_address=network)
plat_port_dict = dict(port_id=port_id,
network=network)
port_objs.append(plat_port_obj)
port_dicts.append(plat_port_dict)
return port_objs, port_dicts
def _create_stream_config(self, plat_objs):
platform_id = plat_objs['platform_id']
device_id = plat_objs['device_id']
#create the log data product
self.dp_obj.name = '%s platform_eng data' % platform_id
self.data_product_id = self.dpclient.create_data_product(data_product=self.dp_obj, stream_definition_id=self.platform_eng_stream_def_id)
self.damsclient.assign_data_product(input_resource_id=self.device_id, data_product_id=self.data_product_id)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(self.data_product_id, PRED.hasStream, None, True)
stream_config = self._build_stream_config(stream_ids[0])
return stream_config
def _build_stream_config(self, stream_id=''):
platform_eng_dictionary = DatasetManagementService.get_parameter_dictionary_by_name('platform_eng_parsed')
#get the streamroute object from pubsub by passing the stream_id
stream_def_ids, _ = self.rrclient.find_objects(stream_id,
PRED.hasStreamDefinition,
RT.StreamDefinition,
True)
stream_route = self.pubsubcli.read_stream_route(stream_id=stream_id)
stream_config = {'routing_key' : stream_route.routing_key,
'stream_id' : stream_id,
'stream_definition_ref' : stream_def_ids[0],
'exchange_point' : stream_route.exchange_point,
'parameter_dictionary':platform_eng_dictionary.dump()}
return stream_config
def _set_platform_agent_instances(self):
"""
Once most of the objs/defs associated with all platforms are in
place, this method creates and associates the PlatformAgentInstance
elements.
"""
self.platform_configs = {}
for platform_id, plat_objs in self.all_platforms.iteritems():
PLATFORM_CONFIG = {
'platform_id': platform_id,
'agent_streamconfig_map': None, #self.agent_streamconfig_map,
'driver_config': DVR_CONFIG,
'network_definition' : self._network_definition_ser
}
self.platform_configs[platform_id] = {
'platform_id': platform_id,
'agent_streamconfig_map': self.agent_streamconfig_map,
'driver_config': DVR_CONFIG,
'network_definition' : self._network_definition_ser
}
agent_config = {
'platform_config': PLATFORM_CONFIG,
}
self.stream_id = self.agent_streamconfig_map[platform_id]['stream_id']
# import pprint
# print '============== platform id within unit test: %s ===========' % platform_id
# pprint.pprint(agent_config)
#agent_config['platform_config']['agent_streamconfig_map'] = None
agent_instance_obj = IonObject(RT.PlatformAgentInstance,
name='%s_PlatformAgentInstance' % platform_id,
description="%s_PlatformAgentInstance" % platform_id,
agent_config=agent_config)
agent_id = plat_objs['agent_id']
device_id = plat_objs['device_id']
agent_instance_id = self.imsclient.create_platform_agent_instance(
agent_instance_obj, agent_id, self.device_id)
plat_objs['agent_instance_obj'] = agent_instance_obj
plat_objs['agent_instance_id'] = agent_instance_id
stream_config = self.agent_streamconfig_map[platform_id]
self._start_data_subscriber(agent_instance_id, stream_config)
def _start_data_subscriber(self, stream_name, stream_config):
"""
Starts data subscriber for the given stream_name and stream_config
"""
def consume_data(message, stream_route, stream_id):
# A callback for processing subscribed-to data.
log.info('Subscriber received data message: %s.', str(message))
self._samples_received.append(message)
self._async_data_result.set()
log.info('_start_data_subscriber stream_name=%r', stream_name)
stream_id = self.stream_id #stream_config['stream_id']
# Create subscription for the stream
exchange_name = '%s_queue' % stream_name
self.container.ex_manager.create_xn_queue(exchange_name).purge()
sub = StandaloneStreamSubscriber(exchange_name, consume_data)
sub.start()
self._data_subscribers.append(sub)
sub_id = self.pubsubcli.create_subscription(name=exchange_name, stream_ids=[stream_id])
self.pubsubcli.activate_subscription(sub_id)
sub.subscription_id = sub_id
def _stop_data_subscribers(self):
"""
Stop the data subscribers on cleanup.
"""
try:
for sub in self._data_subscribers:
if hasattr(sub, 'subscription_id'):
try:
self.pubsubcli.deactivate_subscription(sub.subscription_id)
except:
pass
self.pubsubcli.delete_subscription(sub.subscription_id)
sub.stop()
finally:
self._data_subscribers = []
def _start_event_subscriber(self, event_type="DeviceEvent", sub_type="platform_event"):
"""
Starts event subscriber for events of given event_type ("DeviceEvent"
by default) and given sub_type ("platform_event" by default).
"""
def consume_event(evt, *args, **kwargs):
# A callback for consuming events.
log.info('Event subscriber received evt: %s.', str(evt))
self._events_received.append(evt)
self._async_event_result.set(evt)
sub = EventSubscriber(event_type=event_type,
sub_type=sub_type,
callback=consume_event)
sub.start()
log.info("registered event subscriber for event_type=%r, sub_type=%r",
event_type, sub_type)
self._event_subscribers.append(sub)
sub._ready_event.wait(timeout=EVENT_TIMEOUT)
def _stop_event_subscribers(self):
"""
Stops the event subscribers on cleanup.
"""
try:
for sub in self._event_subscribers:
if hasattr(sub, 'subscription_id'):
try:
self.pubsubcli.deactivate_subscription(sub.subscription_id)
except:
pass
self.pubsubcli.delete_subscription(sub.subscription_id)
sub.stop()
finally:
self._event_subscribers = []
@skip("IMS does't net implement topology")
def test_hierarchy(self):
self._create_launch_verify(BASE_PLATFORM_ID)
@skip("Needs alignment with recent IMS changes")
def test_single_platform(self):
self._create_launch_verify('LJ01D')
def _create_launch_verify(self, base_platform_id):
# and trigger the traversal of the branch rooted at that base platform
# to create corresponding ION objects and configuration dictionaries:
pnode = self._network_definition.pnodes[base_platform_id]
base_platform_objs = self._traverse(pnode, base_platform_id)
# now that most of the topology information is there, add the
# PlatformAgentInstance elements
self._set_platform_agent_instances()
base_platform_config = self.platform_configs[base_platform_id]
log.info("base_platform_id = %r", base_platform_id)
#-------------------------------------------------------------------------------------
# Create Data Process Definition and Data Process for the eng stream monitor process
#-------------------------------------------------------------------------------------
dpd_obj = IonObject(RT.DataProcessDefinition,
name='DemoStreamAlertTransform',
description='For testing EventTriggeredTransform_B',
module='ion.processes.data.transforms.event_alert_transform',
class_name='DemoStreamAlertTransform')
self.platform_dprocdef_id = self.dataprocessclient.create_data_process_definition(dpd_obj)
#THERE SHOULD BE NO STREAMDEF REQUIRED HERE.
platform_streamdef_id = self.pubsubcli.create_stream_definition(name='platform_eng_parsed', parameter_dictionary_id=self.pdict_id)
self.dataprocessclient.assign_stream_definition_to_data_process_definition(platform_streamdef_id, self.platform_dprocdef_id, binding='output' )
config = {
'process':{
'timer_interval': 5,
'queue_name': 'a_queue',
'variable_name': 'input_voltage',
'time_field_name': 'preferred_timestamp',
'valid_values': [-100, 100],
'timer_origin': 'Interval Timer'
}
}
platform_data_process_id = self.dataprocessclient.create_data_process(self.platform_dprocdef_id, [self.data_product_id], {}, config)
self.dataprocessclient.activate_data_process(platform_data_process_id)
self.addCleanup(self.dataprocessclient.delete_data_process, platform_data_process_id)
#-------------------------------
# Launch Base Platform AgentInstance, connect to the resource agent client
#-------------------------------
agent_instance_id = base_platform_objs['agent_instance_id']
log.debug("about to call imsclient.start_platform_agent_instance with id=%s", agent_instance_id)
pid = self.imsclient.start_platform_agent_instance(platform_agent_instance_id=agent_instance_id)
log.debug("start_platform_agent_instance returned pid=%s", pid)
#wait for start
instance_obj = self.imsclient.read_platform_agent_instance(agent_instance_id)
gate = ProcessStateGate(self.processdispatchclient.read_process,
instance_obj.agent_process_id,
ProcessStateEnum.RUNNING)
self.assertTrue(gate.await(90), "The platform agent instance did not spawn in 90 seconds")
agent_instance_obj= self.imsclient.read_instrument_agent_instance(agent_instance_id)
log.debug('test_oms_create_and_launch: Platform agent instance obj: %s', str(agent_instance_obj))
# Start a resource agent client to talk with the instrument agent.
self._pa_client = ResourceAgentClient('paclient', name=agent_instance_obj.agent_process_id, process=FakeProcess())
log.debug(" test_oms_create_and_launch:: got pa client %s", str(self._pa_client))
log.debug("base_platform_config =\n%s", base_platform_config)
# ping_agent can be issued before INITIALIZE
retval = self._pa_client.ping_agent(timeout=TIMEOUT)
log.debug( 'Base Platform ping_agent = %s', str(retval) )
# issue INITIALIZE command to the base platform, which will launch the
# creation of the whole platform hierarchy rooted at base_platform_config['platform_id']
# cmd = AgentCommand(command=PlatformAgentEvent.INITIALIZE, kwargs=dict(plat_config=base_platform_config))
cmd = AgentCommand(command=PlatformAgentEvent.INITIALIZE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform INITIALIZE = %s', str(retval) )
# GO_ACTIVE
cmd = AgentCommand(command=PlatformAgentEvent.GO_ACTIVE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform GO_ACTIVE = %s', str(retval) )
# RUN:
cmd = AgentCommand(command=PlatformAgentEvent.RUN)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform RUN = %s', str(retval) )
# START_MONITORING:
cmd = AgentCommand(command=PlatformAgentEvent.START_MONITORING)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform START_MONITORING = %s', str(retval) )
# wait for data sample
# just wait for at least one -- see consume_data above
log.info("waiting for reception of a data sample...")
self._async_data_result.get(timeout=DATA_TIMEOUT)
self.assertTrue(len(self._samples_received) >= 1)
log.info("waiting a bit more for reception of more data samples...")
sleep(15)
log.info("Got data samples: %d", len(self._samples_received))
# wait for event
# just wait for at least one event -- see consume_event above
log.info("waiting for reception of an event...")
self._async_event_result.get(timeout=EVENT_TIMEOUT)
log.info("Received events: %s", len(self._events_received))
#get the extended platfrom which wil include platform aggreate status fields
extended_platform = self.imsclient.get_platform_device_extension(self.device_id)
# log.debug( 'test_single_platform extended_platform: %s', str(extended_platform) )
# log.debug( 'test_single_platform power_status_roll_up: %s', str(extended_platform.computed.power_status_roll_up.value) )
# log.debug( 'test_single_platform comms_status_roll_up: %s', str(extended_platform.computed.communications_status_roll_up.value) )
# STOP_MONITORING:
cmd = AgentCommand(command=PlatformAgentEvent.STOP_MONITORING)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform STOP_MONITORING = %s', str(retval) )
# GO_INACTIVE
cmd = AgentCommand(command=PlatformAgentEvent.GO_INACTIVE)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform GO_INACTIVE = %s', str(retval) )
# RESET: Resets the base platform agent, which includes termination of
# its sub-platforms processes:
cmd = AgentCommand(command=PlatformAgentEvent.RESET)
retval = self._pa_client.execute_agent(cmd, timeout=TIMEOUT)
log.debug( 'Base Platform RESET = %s', str(retval) )
#-------------------------------
# Stop Base Platform AgentInstance
#-------------------------------
self.imsclient.stop_platform_agent_instance(platform_agent_instance_id=agent_instance_id)
