def _register_service(self):
definition = self.process_definition
existing_services, _ = self.container.resource_registry.find_resources(
restype="Service", name=definition.name)
if len(existing_services) > 0:
if len(existing_services) > 1:
log.warning(
"There is more than one service object for %s. Using the first one"
% definition.name)
service_id = existing_services[0]._id
else:
svc_obj = Service(name=definition.name,
exchange_name=definition.name)
service_id, _ = self.container.resource_registry.create(svc_obj)
svcdefs, _ = self.container.resource_registry.find_resources(
restype="ServiceDefinition", name=definition.name)
if svcdefs:
try:
self.container.resource_registry.create_association(
service_id, "hasServiceDefinition", svcdefs[0]._id)
except BadRequest:
log.warn(
"Failed to associate %s Service and ServiceDefinition. It probably exists.",
definition.name)
else:
log.error("Cannot find ServiceDefinition resource for %s",
definition.name)
return service_id, definition.name
def build_data_dict(self, rdt):
np_dict = {}
time_array = rdt[rdt.temporal_parameter]
if time_array is None:
raise ValueError("A granule needs a time array")
for k,v in rdt.iteritems():
# Sparse values are different and aren't constructed using NumpyParameterData
if isinstance(rdt.param_type(k), SparseConstantType):
value = v[0]
if hasattr(value, 'dtype'):
value = np.asscalar(value)
time_start = np.asscalar(time_array[0])
np_dict[k] = ConstantOverTime(k, value, time_start=time_start, time_end=None) # From now on
continue
elif isinstance(rdt.param_type(k), CategoryType):
log.warning("Category types temporarily unsupported")
continue
elif isinstance(rdt.param_type(k), RecordType):
value = v
else:
value = v
try:
if k == 'temp_sample':
print repr(value)
np_dict[k] = NumpyParameterData(k, value, time_array)
except:
raise
return np_dict
def _register_service(self):
definition = self.process_definition
existing_services, _ = self.container.resource_registry.find_resources(
restype="Service", name=definition.name)
if len(existing_services) > 0:
if len(existing_services) > 1:
log.warning("There is more than one service object for %s. Using the first one" % definition.name)
service_id = existing_services[0]._id
else:
svc_obj = Service(name=definition.name, exchange_name=definition.name)
service_id, _ = self.container.resource_registry.create(svc_obj)
svcdefs, _ = self.container.resource_registry.find_resources(
restype="ServiceDefinition", name=definition.name)
if svcdefs:
try:
self.container.resource_registry.create_association(
service_id, "hasServiceDefinition", svcdefs[0]._id)
except BadRequest:
log.warn("Failed to associate %s Service and ServiceDefinition. It probably exists.",
definition.name)
else:
log.error("Cannot find ServiceDefinition resource for %s",
definition.name)
return service_id, definition.name
def _register_service(self):
if not self.process_definition_id:
log.error("No process definition id. Not registering service")
return
if len(self.pds) < 1:
log.error("Must have at least one PD available to register a service")
return
pd_name = self.pds[0]
pd = ProcessDispatcherServiceClient(to_name=pd_name)
definition = pd.read_process_definition(self.process_definition_id)
existing_services, _ = self.container.resource_registry.find_resources(
restype="Service", name=definition.name)
if len(existing_services) > 0:
if len(existing_services) > 1:
log.warning("There is more than one service object for %s. Using the first one" % definition.name)
service_id = existing_services[0]._id
else:
svc_obj = Service(name=definition.name, exchange_name=definition.name)
service_id, _ = self.container.resource_registry.create(svc_obj)
svcdefs, _ = self.container.resource_registry.find_resources(
restype="ServiceDefinition", name=definition.name)
if svcdefs:
self.container.resource_registry.create_association(
service_id, "hasServiceDefinition", svcdefs[0]._id)
else:
log.error("Cannot find ServiceDefinition resource for %s",
definition.name)
return service_id
def build_data_dict(self, rdt):
np_dict = {}
time_array = rdt[rdt.temporal_parameter]
if time_array is None:
raise ValueError("A granule needs a time array")
for k, v in rdt.iteritems():
# Sparse values are different and aren't constructed using NumpyParameterData
if isinstance(rdt.param_type(k), SparseConstantType):
value = v[0]
if hasattr(value, 'dtype'):
value = np.asscalar(value)
time_start = np.asscalar(time_array[0])
np_dict[k] = ConstantOverTime(k,
value,
time_start=time_start,
time_end=None) # From now on
continue
elif isinstance(rdt.param_type(k), CategoryType):
log.warning("Category types temporarily unsupported")
continue
elif isinstance(rdt.param_type(k), RecordType):
value = v
else:
value = v
try:
if k == 'temp_sample':
print repr(value)
np_dict[k] = NumpyParameterData(k, value, time_array)
except:
raise
return np_dict
def _req_callback(self, result):
"""
Terrestrial server callback for result receipts.
Pop pending command, append result and publish.
"""
log.debug('Terrestrial server got result: %s', str(result))
try:
id = result['command_id']
_result = result['result']
cmd = self._tx_dict.pop(id)
cmd.time_completed = time.time()
cmd.result = _result
if cmd.resource_id:
origin = cmd.resource_id
elif cmd.svc_name:
origin = cmd.svc_name + self._xs_name
else:
raise KeyError
self._publisher.publish_event(
event_type='RemoteCommandResult',
command=cmd,
origin=origin)
log.debug('Published remote result: %s to origin %s.', str(result),
str(origin))
except KeyError:
log.warning('Error publishing remote result: %s.', str(result))
def retrieve_function_and_define_args(self, stream_id, dataprocess_id):
import importlib
argument_list = {}
function = ''
context = {}
#load the details of this data process
dataprocess_info = self._dataprocesses[dataprocess_id]
try:
#todo: load once into a 'set' of modules?
#load the associated transform function
egg_uri = dataprocess_info.get_safe('uri','')
if egg_uri:
egg = self.download_egg(egg_uri)
import pkg_resources
pkg_resources.working_set.add_entry(egg)
else:
log.warning('No uri provided for module in data process definition.')
module = importlib.import_module(dataprocess_info.get_safe('module', '') )
function = getattr(module, dataprocess_info.get_safe('function','') )
arguments = dataprocess_info.get_safe('arguments', '')
argument_list = dataprocess_info.get_safe('argument_map', {})
if self.has_context_arg(function,argument_list ):
context = self.create_context_arg(stream_id, dataprocess_id)
except ImportError:
log.error('Error running transform')
log.debug('retrieve_function_and_define_args argument_list: %s',argument_list)
return function, argument_list, context
def tearDown(self):
self.waiter.stop()
try:
self.container.terminate_process(self._haa_pid)
except BadRequest:
log.warning("Couldn't terminate HA Agent in teardown (May have been terminated by a test)")
self._stop_container()
def acquire_samples(self, max_samples=0):
log.debug('Orb_DataAgentPlugin.acquire_samples')
if os.path.exists(self.data_dir):
files = os.listdir(self.data_dir)
cols = []
rows = []
for f in files:
fpath = self.data_dir + f
with open(fpath) as fh:
try:
pkt = json.load(fh)
if not cols:
cols = [str(c['chan']) for c in pkt['channels']]
row = self._extract_row(pkt, cols)
dims = [len(c) for c in row[:3]]
if all(d==400 for d in dims):
rows.append(row)
else:
log.warning('Inconsistent dimensions %s, %s' % (str(dims), fpath))
fh.close()
os.remove(fpath)
log.info('sample: ' + fpath)
except Exception as ex:
log.warn(ex)
log.warn('Incomplete packet %s' % fpath)
if cols and rows:
coltypes = {}
for c in cols:
coltypes[c] = '400i4'
cols.append('time')
samples = dict(cols=cols, data=rows, coltypes=coltypes)
return samples
def _req_callback(self, result):
"""
Terrestrial server callback for result receipts.
Pop pending command, append result and publish.
"""
log.debug('Terrestrial server got result: %s', str(result))
try:
id = result['command_id']
_result = result['result']
cmd = self._tx_dict.pop(id)
cmd.time_completed = time.time()
cmd.result = _result
if cmd.resource_id:
origin = cmd.resource_id
elif cmd.svc_name:
origin = cmd.svc_name + self._xs_name
else:
raise KeyError
self._publisher.publish_event(event_type='RemoteCommandResult',
command=cmd,
origin=origin)
log.debug('Published remote result: %s to origin %s.', str(result),
str(origin))
except KeyError:
log.warning('Error publishing remote result: %s.', str(result))
def acquire_samples(self, max_samples=0):
log.debug('Orb_DataAgentPlugin.acquire_samples')
if os.path.exists(self.data_dir):
files = os.listdir(self.data_dir)
cols = []
rows = []
for f in files:
fpath = self.data_dir + f
with open(fpath) as fh:
try:
pkt = json.load(fh)
if not cols:
cols = [str(c['chan']) for c in pkt['channels']]
row = self._extract_row(pkt, cols)
dims = [len(c) for c in row[:3]]
if all(d == 400 for d in dims):
rows.append(row)
else:
log.warning('Inconsistent dimensions %s, %s' %
(str(dims), fpath))
fh.close()
os.remove(fpath)
log.info('sample: ' + fpath)
except Exception as ex:
log.warn(ex)
log.warn('Incomplete packet %s' % fpath)
if cols and rows:
coltypes = {}
for c in cols:
coltypes[c] = '400i4'
cols.append('time')
samples = dict(cols=cols, data=rows, coltypes=coltypes)
return samples
def tearDown(self):
self.waiter.stop()
try:
self.container.terminate_process(self._haa_pid)
except BadRequest:
log.warning("Couldn't terminate HA Agent in teardown (May have been terminated by a test)")
self._stop_container()
def _result_complete(self, result):
"""
"""
if self._client:
log.debug('Remote endpoint enqueuing result %s.', str(result))
self._client.enqueue(result)
else:
log.warning('Received a result but no client available to transmit.')
def on_start(self):
super(NotificationWorker, self).on_start()
self.smtp_client = setting_up_smtp_client()
# ------------------------------------------------------------------------------------
# Start by loading the user info and reverse user info dictionaries
# ------------------------------------------------------------------------------------
try:
self.user_info = self.load_user_info()
self.reverse_user_info = calculate_reverse_user_info(self.user_info)
log.info("On start up, notification workers loaded the following user_info dictionary: %s" % self.user_info)
log.info("The calculated reverse user info: %s" % self.reverse_user_info)
except NotFound as exc:
if exc.message.find("users_index") > -1:
log.warning("Notification workers found on start up that users_index have not been loaded yet.")
else:
raise NotFound(exc.message)
# ------------------------------------------------------------------------------------
# Create an event subscriber for Reload User Info events
# ------------------------------------------------------------------------------------
def reload_user_info(event_msg, headers):
"""
Callback method for the subscriber to ReloadUserInfoEvent
"""
notification_id = event_msg.notification_id
log.info(
"(Notification worker received a ReloadNotificationEvent. The relevant notification_id is %s"
% notification_id
)
try:
self.user_info = self.load_user_info()
except NotFound:
log.warning("ElasticSearch has not yet loaded the user_index.")
self.reverse_user_info = calculate_reverse_user_info(self.user_info)
self.test_hook(self.user_info, self.reverse_user_info)
log.debug("After a reload, the user_info: %s" % self.user_info)
log.debug("The recalculated reverse_user_info: %s" % self.reverse_user_info)
# the subscriber for the ReloadUSerInfoEvent
self.reload_user_info_subscriber = EventSubscriber(event_type="ReloadUserInfoEvent", callback=reload_user_info)
self.reload_user_info_subscriber.start()
# ------------------------------------------------------------------------------------
# Create an event subscriber for all events that are of interest for notifications
# ------------------------------------------------------------------------------------
self.event_subscriber = EventSubscriber(queue_name="uns_queue", callback=self.process_event)
self.event_subscriber.start()
def _result_complete(self, result):
"""
"""
if self._client:
log.debug('Remote endpoint enqueuing result %s.', str(result))
self._client.enqueue(result)
else:
log.warning(
'Received a result but no client available to transmit.')
def on_sample(self, sample):
try:
stream_name = sample['stream_name']
self._stream_buffers[stream_name].insert(0, sample)
if not self._stream_greenlets[stream_name]:
self._publish_stream_buffer(stream_name)
except KeyError:
log.warning('Instrument agent %s received sample with bad stream name %s.',
self._agent._proc_name, stream_name)
def _stop_pagent(self):
"""
Stop the port agent.
"""
if self._pagent:
pid = self._pagent.get_pid()
if pid:
log.info('Stopping pagent pid %i.', pid)
self._pagent.stop()
else:
log.warning('No port agent running.')
def on_start(self):
super(NotificationWorker,self).on_start()
self.reverse_user_info = None
self.user_info = None
#------------------------------------------------------------------------------------
# Start by loading the user info and reverse user info dictionaries
#------------------------------------------------------------------------------------
try:
self.user_info = self.load_user_info()
self.reverse_user_info = calculate_reverse_user_info(self.user_info)
log.debug("On start up, notification workers loaded the following user_info dictionary: %s" % self.user_info)
log.debug("The calculated reverse user info: %s" % self.reverse_user_info )
except NotFound as exc:
if exc.message.find('users_index') > -1:
log.warning("Notification workers found on start up that users_index have not been loaded yet.")
else:
raise NotFound(exc.message)
#------------------------------------------------------------------------------------
# Create an event subscriber for Reload User Info events
#------------------------------------------------------------------------------------
def reload_user_info(event_msg, headers):
'''
Callback method for the subscriber to ReloadUserInfoEvent
'''
notification_id = event_msg.notification_id
log.debug("(Notification worker received a ReloadNotificationEvent. The relevant notification_id is %s" % notification_id)
try:
self.user_info = self.load_user_info()
except NotFound:
log.warning("ElasticSearch has not yet loaded the user_index.")
self.reverse_user_info = calculate_reverse_user_info(self.user_info)
self.test_hook(self.user_info, self.reverse_user_info)
log.debug("After a reload, the user_info: %s" % self.user_info)
log.debug("The recalculated reverse_user_info: %s" % self.reverse_user_info)
# the subscriber for the ReloadUSerInfoEvent
self.reload_user_info_subscriber = EventSubscriber(
event_type="ReloadUserInfoEvent",
origin='UserNotificationService',
callback=reload_user_info
)
self.add_endpoint(self.reload_user_info_subscriber)
def on_sample(self, sample):
try:
stream_name = sample['stream_name']
self._stream_buffers[stream_name].insert(0, sample)
if not self._stream_greenlets[stream_name]:
self._publish_stream_buffer(stream_name)
except KeyError:
log.warning('Instrument agent %s received sample with bad stream name %s.',
self._agent._proc_name, stream_name)
def reload_user_info(event_msg, headers):
'''
Callback method for the subscriber to ReloadUserInfoEvent
'''
try:
self.user_info = self.load_user_info()
except NotFound:
log.warning("ElasticSearch has not yet loaded the user_index.")
self.reverse_user_info = calculate_reverse_user_info(self.user_info)
self.test_hook(self.user_info, self.reverse_user_info)
def add_granule(self, stream_id, rdt):
''' Appends the granule's data to the coverage and persists it. '''
if stream_id in self._bad_coverages:
log.info(
'Message attempting to be inserted into bad coverage: %s',
DatasetManagementService._get_coverage_path(
self.get_dataset(stream_id)))
#--------------------------------------------------------------------------------
# Coverage determiniation and appending
#--------------------------------------------------------------------------------
dataset_id = self.get_dataset(stream_id)
if not dataset_id:
log.error('No dataset could be determined on this stream: %s',
stream_id)
return
try:
coverage = self.get_coverage(stream_id)
except IOError as e:
log.error(
"Couldn't open coverage: %s",
DatasetManagementService._get_coverage_path(
self.get_dataset(stream_id)))
raise CorruptionError(e.message)
if not coverage:
log.error(
'Could not persist coverage from granule, coverage is None')
return
#--------------------------------------------------------------------------------
# Actual persistence
#--------------------------------------------------------------------------------
if rdt[rdt.temporal_parameter] is None:
log.warning("Empty granule received")
return
# Parse the RDT and set hte values in the coverage
self.insert_values(coverage, rdt, stream_id)
# Force the data to be flushed
DatasetManagementService._save_coverage(coverage)
self.update_metadata(dataset_id, rdt)
try:
window = rdt[rdt.temporal_parameter][[0, -1]]
window = window.tolist()
except (ValueError, IndexError):
window = None
self.dataset_changed(dataset_id, window)
def cancel(self, process_id):
self.container.proc_manager.terminate_process(process_id)
log.debug('PD: Terminated Process (%s)', process_id)
try:
self._remove_process(process_id)
except ValueError:
log.warning("PD: No record of %s to remove?" % process_id)
self.event_pub.publish_event(event_type="ProcessLifecycleEvent",
origin=process_id, origin_type="DispatchedProcess",
state=ProcessStateEnum.TERMINATE)
return True
def get_stored_values(self, lookup_value):
if not self.new_lookups.empty():
new_values = self.new_lookups.get()
self.lookup_docs = new_values + self.lookup_docs
lookup_value_document_keys = self.lookup_docs
for key in lookup_value_document_keys:
try:
document = self.stored_value_manager.read_value(key)
if lookup_value in document:
return document[lookup_value]
except NotFound:
log.warning('Specified lookup document does not exist')
return None
def get_stored_values(self, lookup_value):
if not self.new_lookups.empty():
new_values = self.new_lookups.get()
self.lookup_docs = new_values + self.lookup_docs
lookup_value_document_keys = self.lookup_docs
for key in lookup_value_document_keys:
try:
document = self.stored_value_manager.read_value(key)
if lookup_value in document:
return document[lookup_value]
except NotFound:
log.warning('Specified lookup document does not exist')
return None
def load_data_process(self, stream_id=""):
dpms_client = DataProcessManagementServiceClient()
dataprocess_details_list = dpms_client.read_data_process_for_stream(
stream_id)
dataprocess_ids = []
#this returns a list of data process info dicts
for dataprocess_details in dataprocess_details_list:
dataprocess_details = DotDict(dataprocess_details or {})
dataprocess_id = dataprocess_details.dataprocess_id
#set metrics attributes
dataprocess_details.granule_counter = 0
self._dataprocesses[dataprocess_id] = dataprocess_details
log.debug('load_data_process dataprocess_id: %s', dataprocess_id)
log.debug('load_data_process dataprocess_details: %s',
dataprocess_details)
# validate details
# if not outstream info avaialable log a warning but TF may publish an event so proceed
if not dataprocess_details.out_stream_def or not dataprocess_details.output_param:
log.warning(
'No output stream details provided for data process %s, will not publish a granule',
dataprocess_id)
#add the stream id to the map
if 'in_stream_id' in dataprocess_details:
if dataprocess_details['in_stream_id'] in self._streamid_map:
(self._streamid_map[dataprocess_details['in_stream_id']]
).append(dataprocess_id)
else:
self._streamid_map[dataprocess_details['in_stream_id']] = [
dataprocess_id
]
#todo: add transform worker id
self.event_publisher.publish_event(
origin=dataprocess_id,
origin_type='DataProcess',
status=DataProcessStatusType.NORMAL,
description='data process loaded into transform worker')
#create a publisher for output stream
self.create_publisher(dataprocess_id, dataprocess_details)
dataprocess_ids.append(dataprocess_id)
return dataprocess_ids
def process_gateway_agent_request(resource_id, operation):
try:
if not resource_id:
raise BadRequest("Am agent resource_id was not found in the URL")
if operation == '':
raise BadRequest("An agent operation was not specified in the URL")
# Ensure there is no unicode
resource_id = str(resource_id)
operation = str(operation)
# Retrieve json data from HTTP Post payload
json_params = None
if request.method == "POST":
payload = request.form['payload']
json_params = json_loads(str(payload))
if 'agentRequest' not in json_params:
raise Inconsistent("The JSON request is missing the 'agentRequest' key in the request")
if 'agentId' not in json_params['agentRequest']:
raise Inconsistent("The JSON request is missing the 'agentRequest' key in the request")
if 'agentOp' not in json_params['agentRequest']:
raise Inconsistent("The JSON request is missing the 'agentOp' key in the request")
if json_params['agentRequest']['agentId'] != resource_id:
raise Inconsistent("Target agent id in the JSON request (%s) does not match agent id in URL (%s)" % (
str(json_params['agentRequest']['agentId']), resource_id))
if json_params['agentRequest']['agentOp'] != operation:
raise Inconsistent("Target agent operation in the JSON request (%s) does not match agent operation in URL (%s)" % (
str(json_params['agentRequest']['agentOp']), operation))
resource_agent = ResourceAgentClient(resource_id, process=service_gateway_instance)
param_list = create_parameter_list('agentRequest', 'resource_agent', ResourceAgentProcessClient, operation, json_params)
# Validate requesting user and expiry and add governance headers
ion_actor_id, expiry = get_governance_info_from_request('agentRequest', json_params)
ion_actor_id, expiry = validate_request(ion_actor_id, expiry)
param_list['headers'] = build_message_headers(ion_actor_id, expiry)
methodToCall = getattr(resource_agent, operation)
result = methodToCall(**param_list)
return gateway_json_response(result)
except Exception, e:
if e is NotFound:
log.warning('The agent instance for id %s is not found.' % resource_id)
return build_error_response(e)
def tearDown(self):
new_policy = {'preserve_n': 0}
self.haa_client.reconfigure_policy(new_policy)
self.await_ha_state('STEADY')
self.assertEqual(len(self.get_running_procs()), 0)
self.waiter.stop()
try:
self._kill_haagent()
except BadRequest:
log.warning("Couldn't terminate HA Agent in teardown (May have been terminated by a test)")
self.container.resource_registry.delete(self.service_def_id, del_associations=True)
self._stop_container()
def _restart_transform(self, transform_id):
transform = self.clients.resource_registry.read(transform_id)
configuration = transform.configuration
proc_def_ids,other = self.clients.resource_registry.find_objects(subject=transform_id,predicate=PRED.hasProcessDefinition,id_only=True)
if len(proc_def_ids) < 1:
log.warning('Transform did not have a correct process definition.')
return
pid = self.clients.process_dispatcher.schedule_process(
process_definition_id=proc_def_ids[0],
configuration=configuration
)
transform.process_id = pid
self.clients.resource_registry.update(transform)
def on_sample_mult(self, sample_list):
"""
Enqueues a list of granules and publishes them
"""
streams = set()
for sample in sample_list:
try:
stream_name = sample['stream_name']
self._stream_buffers[stream_name].insert(0, sample)
streams.add(stream_name)
except KeyError:
log.warning('Instrument agent %s received sample with bad stream name %s.',
self._agent._proc_name, stream_name)
for stream_name in streams:
if not self._stream_greenlets[stream_name]:
self._publish_stream_buffer(stream_name)
def add_granule(self,stream_id, rdt):
''' Appends the granule's data to the coverage and persists it. '''
if stream_id in self._bad_coverages:
log.info('Message attempting to be inserted into bad coverage: %s',
DatasetManagementService._get_coverage_path(self.get_dataset(stream_id)))
#--------------------------------------------------------------------------------
# Coverage determiniation and appending
#--------------------------------------------------------------------------------
dataset_id = self.get_dataset(stream_id)
if not dataset_id:
log.error('No dataset could be determined on this stream: %s', stream_id)
return
try:
coverage = self.get_coverage(stream_id)
except IOError as e:
log.error("Couldn't open coverage: %s",
DatasetManagementService._get_coverage_path(self.get_dataset(stream_id)))
raise CorruptionError(e.message)
if not coverage:
log.error('Could not persist coverage from granule, coverage is None')
return
#--------------------------------------------------------------------------------
# Actual persistence
#--------------------------------------------------------------------------------
if rdt[rdt.temporal_parameter] is None:
log.warning("Empty granule received")
return
# Parse the RDT and set hte values in the coverage
self.insert_values(coverage, rdt, stream_id)
# Force the data to be flushed
DatasetManagementService._save_coverage(coverage)
self.update_metadata(dataset_id, rdt)
try:
window = rdt[rdt.temporal_parameter][[0,-1]]
window = window.tolist()
except (ValueError, IndexError):
window = None
self.dataset_changed(dataset_id, window)
def on_sample_mult(self, sample_list):
"""
Enqueues a list of granules and publishes them
"""
streams = set()
for sample in sample_list:
try:
stream_name = sample['stream_name']
self._stream_buffers[stream_name].insert(0, sample)
streams.add(stream_name)
except KeyError:
log.warning('Instrument agent %s received sample with bad stream name %s.',
self._agent._proc_name, stream_name)
for stream_name in streams:
if not self._stream_greenlets[stream_name]:
self._publish_stream_buffer(stream_name)
def reload_user_info(event_msg, headers):
"""
Callback method for the subscriber to ReloadUserInfoEvent
"""
notification_id = event_msg.notification_id
log.debug("(UNS instance) received a ReloadNotificationEvent. The relevant notification_id is %s" % notification_id)
try:
self.user_info = self.load_user_info()
except NotFound:
log.warning("ElasticSearch has not yet loaded the user_index.")
self.reverse_user_info = calculate_reverse_user_info(self.user_info)
log.debug("(UNS instance) After a reload, the user_info: %s" % self.user_info)
log.debug("(UNS instance) The recalculated reverse_user_info: %s" % self.reverse_user_info)
def _results_from_response(self, response, id_only):
deserializer = IonObjectDeserializer(obj_registry=get_obj_registry())
if not (response.has_key('hits') and response['hits'].has_key('hits')):
return []
hits = response['hits']['hits']
if len(hits) > 0:
if len(hits) >= SEARCH_BUFFER_SIZE:
log.warning("Query results exceeded search buffer limitations")
self.raise_search_buffer_exceeded()
if id_only:
return [str(i['_id']) for i in hits]
results = map(deserializer.deserialize, hits)
return results
else:
return []
def _results_from_response(self, response, id_only):
deserializer = IonObjectDeserializer(obj_registry=get_obj_registry())
if not (response.has_key('hits') and response['hits'].has_key('hits')):
return []
hits = response['hits']['hits']
if len(hits) > 0:
if len(hits) >= SEARCH_BUFFER_SIZE:
log.warning("Query results exceeded search buffer limitations")
self.raise_search_buffer_exceeded()
if id_only:
return [str(i['_id']) for i in hits]
results = map(deserializer.deserialize,hits)
return results
else:
return []
def tearDown(self):
new_policy = {'preserve_n': 0}
self.haa_client.reconfigure_policy(new_policy)
self.assertEqual(len(self.get_running_procs()), 0)
self.await_ha_state('STEADY')
self.waiter.stop()
try:
self._kill_haagent()
except BadRequest:
log.warning(
"Couldn't terminate HA Agent in teardown (May have been terminated by a test)"
)
self.container.resource_registry.delete(self.service_def_id,
del_associations=True)
self._stop_container()
def restart_transform(transform_id):
transform = self.clients.resource_registry.read(transform_id)
configuration = transform.configuration
proc_def_ids, other = self.clients.resource_registry.find_objects(
subject=transform_id,
predicate=PRED.hasProcessDefinition,
id_only=True)
if len(proc_def_ids) < 1:
log.warning(
'Transform did not have a correct process definition.')
return
pid = self.clients.process_dispatcher.schedule_process(
process_definition_id=proc_def_ids[0],
configuration=configuration)
transform.process_id = pid
self.clients.resource_registry.update(transform)
def acquire_samples(self, max_samples=0):
log.debug('CDIP_DataAgentPlugin.acquire_samples')
# Read server, extract last sample.
data = requests.get(self.streaming_args.url)
m = None
for m in re.finditer(pattern, data.text, flags=re.MULTILINE):
pass
if not m:
log.warning('CDIP_DataAgentPlugin.acquire_samples: No data found.')
return None
year = int(m.group(1))
month = int(m.group(2))
day = int(m.group(3))
hour = int(m.group(4))
minute = int(m.group(5))
Hs = float(m.group(6))
Tp = float(m.group(7))
Dp = int(m.group(8))
Ta = float(m.group(9))
Temp = float(m.group(10))
# Create sample.
# [ntp64_ts, Hs, Tp, Dp, Ta, Temp]
# ['\xdb\x07\x00,\x00\x00\x00\x00', 2.66, 9.09, 328, 6.67, 12.2]
dt = datetime.datetime(year, month, day, hour, minute)
ts = NTP4Time(dt).to_ntp64()
sample = [ts, Hs, Tp, Dp, Ta, Temp]
# Compare to last reading.
if self.last_sample == sample:
log.debug('CDIP_DataAgentPlugin.acquire_samples: No new data.')
return None
# Update, pack and return.
log.debug('CDIP_DataAgentPlugin.acquire_samples: Got new data.')
log.debug('CDIP data: %s' % str(sample))
self.last_sample = sample
sample_desc = dict(cols=["time", "Hs", "Tp", "Dp", "Ta", "Temp"],
data=[sample])
return sample_desc
def acquire_samples(self, max_samples=0):
log.debug('CDIP_DataAgentPlugin.acquire_samples')
# Read server, extract last sample.
data = requests.get(self.streaming_args.url)
m = None
for m in re.finditer(pattern, data.text, flags=re.MULTILINE):
pass
if not m:
log.warning('CDIP_DataAgentPlugin.acquire_samples: No data found.')
return None
year = int(m.group(1))
month = int(m.group(2))
day = int(m.group(3))
hour = int(m.group(4))
minute = int(m.group(5))
Hs = float(m.group(6))
Tp = float(m.group(7))
Dp = int(m.group(8))
Ta = float(m.group(9))
Temp = float(m.group(10))
# Create sample.
# [ntp64_ts, Hs, Tp, Dp, Ta, Temp]
# ['\xdb\x07\x00,\x00\x00\x00\x00', 2.66, 9.09, 328, 6.67, 12.2]
dt = datetime.datetime(year, month, day, hour, minute)
ts = NTP4Time(dt).to_ntp64()
sample = [ts, Hs, Tp, Dp, Ta, Temp]
# Compare to last reading.
if self.last_sample == sample:
log.debug('CDIP_DataAgentPlugin.acquire_samples: No new data.')
return None
# Update, pack and return.
log.debug('CDIP_DataAgentPlugin.acquire_samples: Got new data.')
log.debug('CDIP data: %s' % str(sample))
self.last_sample = sample
sample_desc = dict(cols=["time", "Hs", "Tp", "Dp", "Ta", "Temp"],
data=[sample])
return sample_desc
def load_user_info(self):
'''
Method to load the user info dictionary used by the notification workers and the UNS
@retval user_info dict
'''
users, _ = self.resource_registry.find_resources(restype=RT.UserInfo)
user_info = {}
if not users:
return {}
for user in users:
notifications_disabled = False
notifications_daily_digest = False
notifications = self.get_user_notifications(user_info_id=user)
for variable in user.variables:
if type(variable) is dict and variable.has_key('name'):
if variable['name'] == 'notifications_daily_digest':
notifications_daily_digest = variable['value']
if variable['name'] == 'notifications_disabled':
notifications_disabled = variable['value']
else:
log.warning(
'Invalid variables attribute on UserInfo instance. UserInfo: %s',
user)
user_info[user._id] = {
'user_contact': user.contact,
'notifications': notifications,
'notifications_daily_digest': notifications_daily_digest,
'notifications_disabled': notifications_disabled
}
return user_info
def on_start(self): #pragma no cover
#--------------------------------------------------------------------------------
# Explicit on_start
#--------------------------------------------------------------------------------
# Skip TransformStreamListener and go to StreamProcess to avoid the subscriber being created
# We want explicit management of the thread and subscriber object for ingestion
TransformStreamProcess.on_start(self)
self.queue_name = self.CFG.get_safe('process.queue_name',self.id)
self.subscriber = StreamSubscriber(process=self, exchange_name=self.queue_name, callback=self.receive_callback)
self.thread_lock = RLock()
#--------------------------------------------------------------------------------
# Normal on_start after this point
#--------------------------------------------------------------------------------
BaseIngestionWorker.on_start(self)
self._rpc_server = self.container.proc_manager._create_listening_endpoint(from_name=self.id, process=self)
self.add_endpoint(self._rpc_server)
self.event_publisher = EventPublisher(OT.DatasetModified)
self.stored_value_manager = StoredValueManager(self.container)
self.lookup_docs = self.CFG.get_safe('process.lookup_docs',[])
self.input_product = self.CFG.get_safe('process.input_product','')
self.qc_enabled = self.CFG.get_safe('process.qc_enabled', True)
self.ignore_gaps = self.CFG.get_safe('service.ingestion.ignore_gaps', True)
if not self.ignore_gaps:
log.warning("Gap handling is not supported in release 2")
self.ignore_gaps = True
self.new_lookups = Queue()
self.lookup_monitor = EventSubscriber(event_type=OT.ExternalReferencesUpdatedEvent, callback=self._add_lookups, auto_delete=True)
self.add_endpoint(self.lookup_monitor)
self.qc_publisher = EventPublisher(event_type=OT.ParameterQCEvent)
self.connection_id = ''
self.connection_index = None
self.start_listener()
def test_realtime_visualization(self):
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product(
)
ctd_sim_pid = self.start_sinusoidal_input_stream_process(ctd_stream_id)
#TODO - Need to add workflow creation for google data table
vis_params = {}
vis_token = self.vis_client.initiate_realtime_visualization(
data_product_id=ctd_parsed_data_product_id,
visualization_parameters=vis_params)
#Trying to continue to receive messages in the queue
gevent.sleep(10.0) # Send some messages - don't care how many
#TODO - find out what the actual return data type should be
vis_data = self.vis_client.get_realtime_visualization_data(vis_token)
if (vis_data):
self.validate_google_dt_transform_results(vis_data)
#Trying to continue to receive messages in the queue
gevent.sleep(5.0) # Send some messages - don't care how many
#Turning off after everything - since it is more representative of an always on stream of data!
#todo remove the try except
try:
self.process_dispatcher.cancel_process(
ctd_sim_pid
) # kill the ctd simulator process - that is enough data
except:
log.warning("cancelling process did not work")
vis_data = self.vis_client.get_realtime_visualization_data(vis_token)
if vis_data:
self.validate_google_dt_transform_results(vis_data)
# Cleanup
self.vis_client.terminate_realtime_visualization_data(vis_token)
def load_data_process(self, stream_id=""):
dpms_client = DataProcessManagementServiceClient()
dataprocess_details_list = dpms_client.read_data_process_for_stream(stream_id)
dataprocess_ids = []
#this returns a list of data process info dicts
for dataprocess_details in dataprocess_details_list:
dataprocess_details = DotDict(dataprocess_details or {})
dataprocess_id = dataprocess_details.dataprocess_id
#set metrics attributes
dataprocess_details.granule_counter = 0
self._dataprocesses[dataprocess_id] = dataprocess_details
log.debug('load_data_process dataprocess_id: %s', dataprocess_id)
log.debug('load_data_process dataprocess_details: %s', dataprocess_details)
# validate details
# if not outstream info avaialable log a warning but TF may publish an event so proceed
if not dataprocess_details.out_stream_def or not dataprocess_details.output_param:
log.warning('No output stream details provided for data process %s, will not publish a granule', dataprocess_id)
#add the stream id to the map
if 'in_stream_id' in dataprocess_details:
if dataprocess_details['in_stream_id'] in self._streamid_map:
(self._streamid_map[ dataprocess_details['in_stream_id'] ]).append(dataprocess_id)
else:
self._streamid_map[ dataprocess_details['in_stream_id'] ] = [dataprocess_id]
#todo: add transform worker id
self.event_publisher.publish_event(origin=dataprocess_id, origin_type='DataProcess', status=DataProcessStatusType.NORMAL,
description='data process loaded into transform worker')
#create a publisher for output stream
self.create_publisher(dataprocess_id, dataprocess_details)
dataprocess_ids.append(dataprocess_id)
return dataprocess_ids
def reload_user_info(event_msg, headers):
'''
Callback method for the subscriber to ReloadUserInfoEvent
'''
notification_id = event_msg.notification_id
log.debug(
"(Notification worker received a ReloadNotificationEvent. The relevant notification_id is %s"
% notification_id)
try:
self.user_info = self.load_user_info()
except NotFound:
log.warning("ElasticSearch has not yet loaded the user_index.")
self.reverse_user_info = calculate_reverse_user_info(
self.user_info)
self.test_hook(self.user_info, self.reverse_user_info)
log.debug("After a reload, the user_info: %s" % self.user_info)
log.debug("The recalculated reverse_user_info: %s" %
self.reverse_user_info)
def load_user_info(self):
'''
Method to load the user info dictionary used by the notification workers and the UNS
@retval user_info dict
'''
users, _ = self.resource_registry.find_resources(restype= RT.UserInfo)
user_info = {}
if not users:
return {}
for user in users:
notifications = []
notifications_disabled = False
notifications_daily_digest = False
log.debug('load_user_info: user.variables: %s', user.variables)
for variable in user.variables:
if type(variable) is dict and variable.has_key('name'):
if variable['name'] == 'notifications':
notifications = variable['value']
if variable['name'] == 'notifications_daily_digest':
notifications_daily_digest = variable['value']
if variable['name'] == 'notifications_disabled':
notifications_disabled = variable['value']
else:
log.warning('Invalid variables attribute on UserInfo instance. UserInfo: %s', user)
user_info[user._id] = { 'user_contact' : user.contact, 'notifications' : notifications,
'notifications_daily_digest' : notifications_daily_digest, 'notifications_disabled' : notifications_disabled}
return user_info
def retrieve_function_and_define_args(self, stream_id, dataprocess_id):
import importlib
argument_list = {}
function = ''
context = {}
#load the details of this data process
dataprocess_info = self._dataprocesses[dataprocess_id]
try:
#todo: load once into a 'set' of modules?
#load the associated transform function
egg_uri = dataprocess_info.get_safe('uri', '')
if egg_uri:
egg = self.download_egg(egg_uri)
import pkg_resources
pkg_resources.working_set.add_entry(egg)
else:
log.warning(
'No uri provided for module in data process definition.')
module = importlib.import_module(
dataprocess_info.get_safe('module', ''))
function = getattr(module,
dataprocess_info.get_safe('function', ''))
arguments = dataprocess_info.get_safe('arguments', '')
argument_list = dataprocess_info.get_safe('argument_map', {})
if self.has_context_arg(function, argument_list):
context = self.create_context_arg(stream_id, dataprocess_id)
except ImportError:
log.error('Error running transform')
log.debug('retrieve_function_and_define_args argument_list: %s',
argument_list)
return function, argument_list, context
def test_realtime_visualization(self):
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
ctd_sim_pid = self.start_sinusoidal_input_stream_process(ctd_stream_id)
#TODO - Need to add workflow creation for google data table
vis_params ={}
vis_token = self.vis_client.initiate_realtime_visualization(data_product_id=ctd_parsed_data_product_id, visualization_parameters=vis_params)
#Trying to continue to receive messages in the queue
gevent.sleep(10.0) # Send some messages - don't care how many
#TODO - find out what the actual return data type should be
vis_data = self.vis_client.get_realtime_visualization_data(vis_token)
if (vis_data):
self.validate_google_dt_transform_results(vis_data)
#Trying to continue to receive messages in the queue
gevent.sleep(5.0) # Send some messages - don't care how many
#Turning off after everything - since it is more representative of an always on stream of data!
#todo remove the try except
try:
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
except:
log.warning("cancelling process did not work")
vis_data = self.vis_client.get_realtime_visualization_data(vis_token)
if vis_data:
self.validate_google_dt_transform_results(vis_data)
# Cleanup
self.vis_client.terminate_realtime_visualization_data(vis_token)
def process_oms_event():
if not request.data:
log.warning('process_oms_event: invalid OMS event payload: %r', request.data)
return gateway_json_response(OMS_BAD_REQUEST_RESPONSE)
payload = json_loads(str(request.data))
if not isinstance(payload, list):
log.warning('process_oms_event: invalid OMS event payload: '
'expecting array but got: %r', payload)
return gateway_json_response(OMS_BAD_REQUEST_RESPONSE)
log.debug('process_oms_event: payload=%s', payload)
event_publisher = EventPublisher()
for obj in payload:
for k in ['event_id', 'platform_id', 'message']:
if k not in obj:
log.warning('process_oms_event: invalid OMS event: %r missing. '
'Received object: %s', k, obj)
#return gateway_json_response(OMS_BAD_REQUEST_RESPONSE)
# note the the external event_id is captured in the sub_type field:
evt = dict(
event_type = 'OMSDeviceStatusEvent',
origin_type = 'OMS Platform',
origin = obj.get('platform_id', 'platform_id NOT PROVIDED'),
sub_type = obj.get('event_id', 'event_id NOT PROVIDED'),
description = obj.get('message', ''),
status_details = obj)
try:
event_publisher.publish_event(**evt)
log.debug('process_oms_event: published: %s', evt)
except Exception as e:
log.exception('process_oms_event: could not publish OMS event: %s', evt)
return gateway_json_response(OMS_ACCEPTED_RESPONSE)
def test_realtime_visualization(self):
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='GoogleDT_Test_Workflow',description='Tests the workflow of converting stream data to Google DT')
#Add a transformation process definition
google_dt_procdef_id = self.create_google_dt_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=google_dt_procdef_id, persist_process_output_data=True)
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id, timeout=20)
ctd_sim_pid = self.start_sinusoidal_input_stream_process(ctd_stream_id)
#TODO - Need to add workflow creation for google data table
vis_params ={}
vis_params['in_product_type'] = 'google_dt'
vis_token = self.vis_client.initiate_realtime_visualization(data_product_id=workflow_product_id, visualization_parameters=vis_params)
#Trying to continue to receive messages in the queue
gevent.sleep(10.0) # Send some messages - don't care how many
#TODO - find out what the actual return data type should be
vis_data = self.vis_client.get_realtime_visualization_data(vis_token)
print vis_data
#Trying to continue to receive messages in the queue
gevent.sleep(5.0) # Send some messages - don't care how many
#Turning off after everything - since it is more representative of an always on stream of data!
#todo remove the try except
try:
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
except:
log.warning("cancelling process did not work")
vis_data = self.vis_client.get_realtime_visualization_data(vis_token)
print vis_data
self.vis_client.terminate_realtime_visualization_data(vis_token)
#Stop the workflow processes
self.workflowclient.terminate_data_process_workflow(workflow_id, False) # Should test true at some point
#Cleanup to make sure delete is correct.
self.workflowclient.delete_workflow_definition(workflow_def_id)
def server_loop():
"""
"""
log.debug('Server greenlet started.')
while True:
if not self._server:
self._start_sock()
# Try to accept incomming message.
# If nothing available, sleep the greenlet.
# Never timeout.
log.debug('Server awaiting request.')
while True:
try:
request = self._server.recv_pyobj(NOBLOCK)
log.debug('Server got request %s.', str(request))
break
except ZMQError:
gevent.sleep(self._sleep)
# Increment the receive count and retrieve any
# instrumented test behaviors.
self.recv_count += 1
# Received a null request corresponding to a zmq interrupt.
# Abandon request and restart server.
if not request:
log.warning('Server got null request, abandoning request and restarting server socket.')
self._stop_sock()
# Valid message received.
# Try to send the message ack.
# If socket not available, sleep and retry.
# If timeout exceeded, abandon request and restart server.
# If successful, send request to callback.
else:
# Grab the current test behavior if any.
test_behavior = self.test_behaviors.get(self.recv_count, None)
# Run test behavior if any.
if test_behavior:
if test_behavior.type == R3PCTestBehavior.delay:
gevent.sleep(test_behavior.delay)
if test_behavior.type == R3PCTestBehavior.stop:
if test_behavior.delay > 0:
gevent.sleep(test_behavior.delay)
self._stop_sock()
break
if test_behavior.type == R3PCTestBehavior.restart:
if test_behavior.delay > 0:
gevent.sleep(test_behavior.delay)
self._stop_sock()
sendtime = time.time()
while self._server:
try:
log.debug('Server sending ack.')
self._server.send_pyobj('OK', NOBLOCK)
log.debug('Server ack send, calling callback.')
self._callback(request)
break
except ZMQError:
gevent.sleep(self._sleep)
if time.time() - sendtime > self._timeout:
log.warning('Server ack failed, abandoning request and restarting server socket.')
self._stop_sock()
def execute_acquire_sample(self, *args):
"""
Creates a copy of self._dh_config, creates a publisher, and spawns a greenlet to perform a data acquisition cycle
If the args[0] is a dict, any entries keyed with one of the 'PATCHABLE_CONFIG_KEYS' are used to patch the config
Greenlet binds to BaseDataHandler._acquire_sample and passes the publisher and config
Disallows multiple "new data" (unconstrained) requests using BaseDataHandler._semaphore lock
Called from:
InstrumentAgent._handler_observatory_execute_resource
|--> ExternalDataAgent._handler_streaming_execute_resource
@parameter args First argument can be a config dictionary
@throws IndexError if first argument is not a dictionary
@throws ConfigurationError if required members aren't present
@retval New ResourceAgentState (COMMAND)
"""
log.debug('Executing acquire_sample: args = {0}'.format(args))
# Make a copy of the config to ensure no cross-pollution
config = self._dh_config.copy()
# Patch the config if mods are passed in
try:
config_mods = args[0]
if not isinstance(config_mods, dict):
raise IndexError()
log.debug('Configuration modifications provided: {0}'.format(
config_mods))
for k in self._params['PATCHABLE_CONFIG_KEYS']:
p = get_safe(config_mods, k)
if not p is None:
config[k] = p
except IndexError:
log.info('No configuration modifications were provided')
# Verify that there is a stream_id member in the config
stream_id = get_safe(config, 'stream_id', None)
if not stream_id:
raise ConfigurationError(
'Configuration does not contain required \'stream_id\' member')
stream_route_param = get_safe(config, 'stream_route', None)
if not stream_route_param:
raise ConfigurationError(
'Configuration does not contain required stream_route member')
if isinstance(stream_route_param, StreamRoute):
# process_dispatcher.spawn does not support IonObjects, only JSONable configuration
# but many existing tests pass stream route directly
log.warning(
'stream_route config parameter: use of a StreamRoute object is deprecated, pass dict instead'
)
stream_route = stream_route_param
elif isinstance(stream_route_param, dict):
# approved method -- pass a dict with appropriate fields to reconstruct IonObject
log.debug('using stream route: %r', stream_route_param)
stream_route = IonObject(OT.StreamRoute, stream_route_param)
# stream_route = IonObject(RT.StreamRoute, exchange_point=stream_route_param['exchange_point'], routing_key=stream_route_param['routing_key'], credentials=stream_route_param['credentials'])
else:
raise ConfigurationError(
'stream_route value should be a dict, not %r' %
stream_route_param)
isNew = get_safe(config, 'constraints') is None
if isNew and not self._semaphore.acquire(blocking=False):
log.warn('Already acquiring new data - action not duplicated')
return
ndc = None
if isNew:
# Get the NewDataCheck attachment and add it's content to the config
ext_ds_id = get_safe(config, 'external_dataset_res_id')
if ext_ds_id:
ndc = self._find_new_data_check_attachment(ext_ds_id)
config['new_data_check'] = ndc
# Create a publisher to pass into the greenlet
publisher = StandaloneStreamPublisher(stream_id=stream_id,
stream_route=stream_route)
# Spawn a greenlet to do the data acquisition and publishing
g = spawn(self._acquire_sample, config, publisher,
self._unlock_new_data_callback,
self._update_new_data_check_attachment)
log.debug('** Spawned {0}'.format(g))
self._glet_queue.append(g)
return ResourceAgentState.COMMAND, None
def client_loop():
"""
"""
log.debug('Client greenlet started.')
while True:
# Start the client socket if necessary.
# If retries exceeded, end loop.
if not self._client:
self._start_sock()
# Pop first message from the queue.
# If empty sleep and retry.
while True:
try:
request = self._queue[0]
break
except IndexError:
gevent.sleep(self._sleep)
# Send request to server.
# If unable to send, sleep and retry.
startsend = time.time()
while True:
try:
log.debug('Client sending request %s.', request)
self._client.send_pyobj(request, NOBLOCK, 0)
self.send_count += 1
break
except ZMQError:
log.warning('Client socket not available for send.')
gevent.sleep(self._sleep)
if time.time() - startsend > self._timeout:
log.warning('Client timed out sending, restarting.')
self._stop_sock()
break
# Grab the current test behavior if any.
test_behavior = self.test_behaviors.get(self.send_count, None)
# Run test behavior if any.
if test_behavior:
if test_behavior.type == R3PCTestBehavior.delay:
gevent.sleep(test_behavior.delay)
if test_behavior.type == R3PCTestBehavior.stop:
if test_behavior.delay > 0:
gevent.sleep(test_behavior.delay)
self._stop_sock()
break
if test_behavior.type == R3PCTestBehavior.restart:
if test_behavior.delay > 0:
gevent.sleep(test_behavior.delay)
self._stop_sock()
# Receive ack from server.
# If unavailalbe, sleep and retry.
# If timeout exceeded, increment retry count and restart client.
# If ack received, zero retry could and pop message.
startrecv = time.time()
while self._client:
try:
log.debug('Client awaiting ack.')
reply = self._client.recv_pyobj(NOBLOCK)
log.debug('Client received ack: %s for request: %s',
reply, request)
if not reply:
self._stop_sock()
else:
self._queue.pop(0)
self._callback(request)
break
except ZMQError:
log.debug('Client socket unavailable to receive ack.')
gevent.sleep(self._sleep)
#delta = time.time() - startrecv
#log.debug('delta=%f', delta)
if time.time() - startrecv > self._timeout:
log.warning('Client timed out awaiting ack, restarting.')
self._stop_sock()
break
def server_loop():
"""
"""
log.debug('Server greenlet started.')
while True:
if not self._server:
self._start_sock()
# Try to accept incomming message.
# If nothing available, sleep the greenlet.
# Never timeout.
log.debug('Server awaiting request.')
while True:
try:
request = self._server.recv_pyobj(NOBLOCK)
log.debug('Server got request %s.', str(request))
break
except ZMQError:
gevent.sleep(self._sleep)
# Increment the receive count and retrieve any
# instrumented test behaviors.
self.recv_count += 1
# Received a null request corresponding to a zmq interrupt.
# Abandon request and restart server.
if not request:
log.warning('Server got null request, abandoning request and restarting server socket.')
self._stop_sock()
# Valid message received.
# Try to send the message ack.
# If socket not available, sleep and retry.
# If timeout exceeded, abandon request and restart server.
# If successful, send request to callback.
else:
# Grab the current test behavior if any.
test_behavior = self.test_behaviors.get(self.recv_count, None)
# Run test behavior if any.
if test_behavior:
if test_behavior.type == R3PCTestBehavior.delay:
gevent.sleep(test_behavior.delay)
if test_behavior.type == R3PCTestBehavior.stop:
if test_behavior.delay > 0:
gevent.sleep(test_behavior.delay)
self._stop_sock()
break
if test_behavior.type == R3PCTestBehavior.restart:
if test_behavior.delay > 0:
gevent.sleep(test_behavior.delay)
self._stop_sock()
sendtime = time.time()
while self._server:
try:
log.debug('Server sending ack.')
self._server.send_pyobj('OK', NOBLOCK)
log.debug('Server ack send, calling callback.')
self._callback(request)
break
except ZMQError:
gevent.sleep(self._sleep)
if time.time() - sendtime > self._timeout:
log.warning('Server ack failed, abandoning request and restarting server socket.')
self._stop_sock()
def on_start(self):
super(NotificationWorker, self).on_start()
self.reverse_user_info = None
self.user_info = None
#------------------------------------------------------------------------------------
# Start by loading the user info and reverse user info dictionaries
#------------------------------------------------------------------------------------
try:
self.user_info = self.load_user_info()
self.reverse_user_info = calculate_reverse_user_info(
self.user_info)
log.debug(
"On start up, notification workers loaded the following user_info dictionary: %s"
% self.user_info)
log.debug("The calculated reverse user info: %s" %
self.reverse_user_info)
except NotFound as exc:
if exc.message.find('users_index') > -1:
log.warning(
"Notification workers found on start up that users_index have not been loaded yet."
)
else:
raise NotFound(exc.message)
#------------------------------------------------------------------------------------
# Create an event subscriber for Reload User Info events
#------------------------------------------------------------------------------------
def reload_user_info(event_msg, headers):
'''
Callback method for the subscriber to ReloadUserInfoEvent
'''
notification_id = event_msg.notification_id
log.debug(
"(Notification worker received a ReloadNotificationEvent. The relevant notification_id is %s"
% notification_id)
try:
self.user_info = self.load_user_info()
except NotFound:
log.warning("ElasticSearch has not yet loaded the user_index.")
self.reverse_user_info = calculate_reverse_user_info(
self.user_info)
self.test_hook(self.user_info, self.reverse_user_info)
log.debug("After a reload, the user_info: %s" % self.user_info)
log.debug("The recalculated reverse_user_info: %s" %
self.reverse_user_info)
# the subscriber for the ReloadUSerInfoEvent
self.reload_user_info_subscriber = EventSubscriber(
event_type=OT.ReloadUserInfoEvent,
origin='UserNotificationService',
callback=reload_user_info)
self.add_endpoint(self.reload_user_info_subscriber)