本文整理汇总了Python中pyon.net.endpoint.Subscriber.initialize方法的典型用法代码示例。如果您正苦于以下问题:Python Subscriber.initialize方法的具体用法?Python Subscriber.initialize怎么用?Python Subscriber.initialize使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pyon.net.endpoint.Subscriber
的用法示例。
在下文中一共展示了Subscriber.initialize方法的7个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: get_realtime_visualization_data
# 需要导入模块: from pyon.net.endpoint import Subscriber [as 别名]
# 或者: from pyon.net.endpoint.Subscriber import initialize [as 别名]
def get_realtime_visualization_data(self, query_token=''):
"""This operation returns a block of visualization data for displaying data product in real time. This operation requires a
user specific token which was provided from a previous request to the init_realtime_visualization operation.
@param query_token str
@retval datatable str
@throws NotFound Throws if specified query_token or its visualization product does not exist
"""
log.debug( "get_realtime_visualization_data Vis worker: %s", self.id)
ret_val = []
if not query_token:
raise BadRequest("The query_token parameter is missing")
#Taking advantage of idempotency
xq = self.container.ex_manager.create_xn_queue(query_token)
subscriber = Subscriber(from_name=xq)
subscriber.initialize()
msgs = subscriber.get_all_msgs(timeout=2)
for x in range(len(msgs)):
msgs[x].ack()
# Different messages should get processed differently. Ret val will be decided by the viz product type
ret_val = self._process_visualization_message(msgs)
#TODO - replace as need be to return valid GDT data
#return {'viz_data': ret_val}
return ret_val
示例2: get_realtime_visualization_data
# 需要导入模块: from pyon.net.endpoint import Subscriber [as 别名]
# 或者: from pyon.net.endpoint.Subscriber import initialize [as 别名]
def get_realtime_visualization_data(self, query_token='', callback='', tqx=""):
"""This operation returns a block of visualization data for displaying data product in real time. This operation requires a
user specific token which was provided from a previous request to the init_realtime_visualization operation.
@param query_token str
@retval datatable str
@throws NotFound Throws if specified query_token or its visualization product does not exist
"""
print " >>>>>>>>>>>>>>> QUERY TOKEN : ", query_token
print " >>>>>>>>>>>>>>> callback : ", callback
print ">>>>>>>>>>>>>>> TQX : ", tqx
reqId = 0
# If a reqId was passed in tqx, extract it
if tqx:
tqx_param_list = tqx.split(";")
for param in tqx_param_list:
key, value = param.split(":")
if key == 'reqId':
reqId = value
ret_val = []
if not query_token:
raise BadRequest("The query_token parameter is missing")
#try:
#Taking advantage of idempotency
xq = self.container.ex_manager.create_xn_queue(query_token)
subscriber = Subscriber(from_name=xq)
subscriber.initialize()
msgs = subscriber.get_all_msgs(timeout=2)
for x in range(len(msgs)):
msgs[x].ack()
# Different messages should get processed differently. Ret val will be decided by the viz product type
ret_val = self._process_visualization_message(msgs, callback, reqId)
#except Exception, e:
# raise e
#finally:
# subscriber.close()
#TODO - replace as need be to return valid GDT data
#return {'viz_data': ret_val}
return ret_val
示例3: get_realtime_visualization_data
# 需要导入模块: from pyon.net.endpoint import Subscriber [as 别名]
# 或者: from pyon.net.endpoint.Subscriber import initialize [as 别名]
def get_realtime_visualization_data(self, query_token=''):
"""This operation returns a block of visualization data for displaying data product in real time. This operation requires a
user specific token which was provided from a previous request to the init_realtime_visualization operation.
@param query_token str
@retval datatable str
@throws NotFound Throws if specified query_token or its visualization product does not exist
"""
log.debug( "get_realtime_visualization_data Vis worker: %s", self.id)
ret_val = []
if not query_token:
raise BadRequest("The query_token parameter is missing")
try:
#Taking advantage of idempotency
queue_name = '-'.join([USER_VISUALIZATION_QUEUE, query_token])
xq = self.container.ex_manager.create_xn_queue(queue_name)
subscriber = Subscriber(from_name=xq)
subscriber.initialize()
except:
# Close the subscriber if it exists
if subscriber:
subscriber.close()
raise BadRequest("Could not subscribe to the real-time queue")
msgs = subscriber.get_all_msgs(timeout=2)
for x in range(len(msgs)):
msgs[x].ack()
subscriber.close()
# Different messages should get processed differently. Ret val will be decided by the viz product type
ret_val = self._process_visualization_message(msgs)
return ret_val
示例4: get_realtime_visualization_data
# 需要导入模块: from pyon.net.endpoint import Subscriber [as 别名]
# 或者: from pyon.net.endpoint.Subscriber import initialize [as 别名]
def get_realtime_visualization_data(self, query_token=''):
"""This operation returns a block of visualization data for displaying data product in real time. This operation requires a
user specific token which was provided from a previsou request to the init_realtime_visualization operation.
@param query_token str
@retval datatable str
@throws NotFound Throws if specified query_token or its visualization product does not exist
"""
if not query_token:
raise BadRequest("The query_token parameter is missing")
try:
#Taking advantage of idempotency
xq = self.container.ex_manager.create_xn_queue(query_token)
subscriber = Subscriber(from_name=xq)
subscriber.initialize()
msg_count,_ = subscriber.get_stats()
log.info('Messages in user queue 1: %s ' % msg_count)
ret_val = []
msgs = subscriber.get_all_msgs(timeout=2)
for x in range(len(msgs)):
msgs[x].ack()
# Different messages should get processed differently. Ret val will be decided by the viz product type
ret_val = self._process_visualization_message(msgs)
msg_count,_ = subscriber.get_stats()
log.info('Messages in user queue 2: %s ' % msg_count)
except Exception, e:
raise e
示例5: test_visualization_queue
# 需要导入模块: from pyon.net.endpoint import Subscriber [as 别名]
# 或者: from pyon.net.endpoint.Subscriber import initialize [as 别名]
def test_visualization_queue(self):
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
user_queue_name = USER_VISUALIZATION_QUEUE
xq = self.container.ex_manager.create_xn_queue(user_queue_name)
salinity_subscription_id = self.pubsubclient.create_subscription(
stream_ids=data_product_stream_ids,
exchange_name = user_queue_name,
name = "user visualization queue"
)
subscriber = Subscriber(from_name=xq)
subscriber.initialize()
# after the queue has been created it is safe to activate the subscription
self.pubsubclient.activate_subscription(subscription_id=salinity_subscription_id)
#Start the output stream listener to monitor and collect messages
#results = self.start_output_stream_and_listen(None, data_product_stream_ids)
#Not sure why this is needed - but it is
#subscriber._chan.stop_consume()
ctd_sim_pid = self.start_simple_input_stream_process(ctd_stream_id)
gevent.sleep(10.0) # Send some messages - don't care how many
msg_count,_ = xq.get_stats()
log.info('Messages in user queue 1: %s ' % msg_count)
#Validate the data from each of the messages along the way
#self.validate_messages(results)
# for x in range(msg_count):
# mo = subscriber.get_one_msg(timeout=1)
# print mo.body
# mo.ack()
msgs = subscriber.get_all_msgs(timeout=2)
for x in range(len(msgs)):
msgs[x].ack()
self.validate_messages(msgs[x])
# print msgs[x].body
#Should be zero after pulling all of the messages.
msg_count,_ = xq.get_stats()
log.info('Messages in user queue 2: %s ' % msg_count)
#Trying to continue to receive messages in the queue
gevent.sleep(5.0) # Send some messages - don't care how many
#Turning off after everything - since it is more representative of an always on stream of data!
self.process_dispatcher.cancel_process(ctd_sim_pid) # kill the ctd simulator process - that is enough data
#Should see more messages in the queue
msg_count,_ = xq.get_stats()
log.info('Messages in user queue 3: %s ' % msg_count)
msgs = subscriber.get_all_msgs(timeout=2)
for x in range(len(msgs)):
msgs[x].ack()
self.validate_messages(msgs[x])
#Should be zero after pulling all of the messages.
msg_count,_ = xq.get_stats()
log.info('Messages in user queue 4: %s ' % msg_count)
subscriber.close()
self.container.ex_manager.delete_xn(xq)
示例6: test_consume_one_message_at_a_time
# 需要导入模块: from pyon.net.endpoint import Subscriber [as 别名]
# 或者: from pyon.net.endpoint.Subscriber import initialize [as 别名]
def test_consume_one_message_at_a_time(self):
# see also pyon.net.test.test_channel:TestChannelInt.test_consume_one_message_at_a_time
pub3 = Publisher(to_name=(self.container.ex_manager.default_xs.exchange, 'routed.3'))
pub5 = Publisher(to_name=(self.container.ex_manager.default_xs.exchange, 'routed.5'))
#
# SETUP COMPLETE, BEGIN TESTING OF EXCHANGE OBJECTS
#
xq = self.container.ex_manager.create_xn_queue('random_queue')
self.addCleanup(xq.delete)
# recv'd messages from the subscriber
self.recv_queue = Queue()
def cb(m, h):
raise StandardError("Subscriber callback never gets called back!")
sub = Subscriber(from_name=xq, callback=cb)
sub.initialize()
# publish 10 messages - we're not bound yet, so they'll just dissapear
for x in xrange(10):
pub3.publish("3,%s" % str(x))
# allow time for routing
time.sleep(2)
# no messages yet
self.assertRaises(Timeout, sub.get_one_msg, timeout=0)
# now, we'll bind the xq
xq.bind('routed.3')
# even tho we are consuming, there are no messages - the previously published ones all dissapeared
self.assertRaises(Timeout, sub.get_one_msg, timeout=0)
# publish those messages again
for x in xrange(10):
pub3.publish("3,%s" % str(x))
# allow time for routing
time.sleep(2)
# NOW we have messages!
for x in xrange(10):
mo = sub.get_one_msg(timeout=10)
self.assertEquals(mo.body, "3,%s" % str(x))
mo.ack()
# we've cleared it all
self.assertRaises(Timeout, sub.get_one_msg, timeout=0)
# bind a wildcard and publish on both
xq.bind('routed.*')
for x in xrange(10):
time.sleep(0.3)
pub3.publish("3,%s" % str(x))
time.sleep(0.3)
pub5.publish("5,%s" % str(x))
# allow time for routing
time.sleep(2)
# should get all 20, interleaved
for x in xrange(10):
mo = sub.get_one_msg(timeout=1)
self.assertEquals(mo.body, "3,%s" % str(x))
mo.ack()
mo = sub.get_one_msg(timeout=1)
self.assertEquals(mo.body, "5,%s" % str(x))
mo.ack()
# add 5 binding, remove all other bindings
xq.bind('routed.5')
xq.unbind('routed.3')
xq.unbind('routed.*')
# try publishing to 3, shouldn't arrive anymore
pub3.publish("3")
self.assertRaises(Timeout, sub.get_one_msg, timeout=0)
# let's turn off the consumer and let things build up a bit
sub._chan.stop_consume()
for x in xrange(10):
pub5.publish("5,%s" % str(x))
# allow time for routing
time.sleep(2)
# 10 messages in the queue, no consumers
self.assertTupleEqual((10, 0), sub._chan.get_stats())
# drain queue
sub._chan.start_consume()
#.........这里部分代码省略.........
示例7: test_multiple_visualization_queue
# 需要导入模块: from pyon.net.endpoint import Subscriber [as 别名]
# 或者: from pyon.net.endpoint.Subscriber import initialize [as 别名]
def test_multiple_visualization_queue(self):
# set up a workflow with the salinity transform and the doubler. We will direct the original stream and the doubled stream to queues
# and test to make sure the subscription to the queues is working correctly
assertions = self.assertTrue
# Build the workflow definition
workflow_def_obj = IonObject(RT.WorkflowDefinition, name='Viz_Test_Workflow',description='A workflow to test collection of multiple data products in queues')
workflow_data_product_name = 'TEST-Workflow_Output_Product' #Set a specific output product name
#-------------------------------------------------------------------------------------------------------------------------
#Add a transformation process definition for salinity
#-------------------------------------------------------------------------------------------------------------------------
ctd_L2_salinity_dprocdef_id = self.create_salinity_data_process_definition()
workflow_step_obj = IonObject('DataProcessWorkflowStep', data_process_definition_id=ctd_L2_salinity_dprocdef_id, persist_process_output_data=False) #Don't persist the intermediate data product
configuration = {'stream_name' : 'salinity'}
workflow_step_obj.configuration = configuration
workflow_def_obj.workflow_steps.append(workflow_step_obj)
#Create it in the resource registry
workflow_def_id = self.workflowclient.create_workflow_definition(workflow_def_obj)
aids = self.rrclient.find_associations(workflow_def_id, PRED.hasDataProcessDefinition)
assertions(len(aids) == 1 )
#The list of data product streams to monitor
data_product_stream_ids = list()
#Create the input data product
ctd_stream_id, ctd_parsed_data_product_id = self.create_ctd_input_stream_and_data_product()
data_product_stream_ids.append(ctd_stream_id)
#Create and start the workflow
workflow_id, workflow_product_id = self.workflowclient.create_data_process_workflow(workflow_def_id, ctd_parsed_data_product_id, timeout=30)
workflow_output_ids,_ = self.rrclient.find_subjects(RT.Workflow, PRED.hasOutputProduct, workflow_product_id, True)
assertions(len(workflow_output_ids) == 1 )
#Walk the associations to find the appropriate output data streams to validate the messages
workflow_dp_ids,_ = self.rrclient.find_objects(workflow_id, PRED.hasDataProduct, RT.DataProduct, True)
assertions(len(workflow_dp_ids) == 1 )
for dp_id in workflow_dp_ids:
stream_ids, _ = self.rrclient.find_objects(dp_id, PRED.hasStream, None, True)
assertions(len(stream_ids) == 1 )
data_product_stream_ids.append(stream_ids[0])
# Now for each of the data_product_stream_ids create a queue and pipe their data to the queue
user_queue_name1 = USER_VISUALIZATION_QUEUE + '1'
user_queue_name2 = USER_VISUALIZATION_QUEUE + '2'
# use idempotency to create queues
xq1 = self.container.ex_manager.create_xn_queue(user_queue_name1)
self.addCleanup(xq1.delete)
xq2 = self.container.ex_manager.create_xn_queue(user_queue_name2)
self.addCleanup(xq2.delete)
xq1.purge()
xq2.purge()
# the create_subscription call takes a list of stream_ids so create temp ones
dp_stream_id1 = list()
dp_stream_id1.append(data_product_stream_ids[0])
dp_stream_id2 = list()
dp_stream_id2.append(data_product_stream_ids[1])
salinity_subscription_id1 = self.pubsubclient.create_subscription( stream_ids=dp_stream_id1,
exchange_name = user_queue_name1, name = "user visualization queue1")
salinity_subscription_id2 = self.pubsubclient.create_subscription( stream_ids=dp_stream_id2,
exchange_name = user_queue_name2, name = "user visualization queue2")
# Create subscribers for the output of the queue
subscriber1 = Subscriber(from_name=xq1)
subscriber1.initialize()
subscriber2 = Subscriber(from_name=xq2)
subscriber2.initialize()
# after the queue has been created it is safe to activate the subscription
self.pubsubclient.activate_subscription(subscription_id=salinity_subscription_id1)
self.pubsubclient.activate_subscription(subscription_id=salinity_subscription_id2)
# Start input stream and wait for some time
ctd_sim_pid = self.start_simple_input_stream_process(ctd_stream_id)
gevent.sleep(5.0) # Send some messages - don't care how many
msg_count,_ = xq1.get_stats()
log.info('Messages in user queue 1: %s ' % msg_count)
msg_count,_ = xq2.get_stats()
log.info('Messages in user queue 2: %s ' % msg_count)
msgs1 = subscriber1.get_all_msgs(timeout=2)
msgs2 = subscriber2.get_all_msgs(timeout=2)
for x in range(min(len(msgs1), len(msgs2))):
msgs1[x].ack()
msgs2[x].ack()
#.........这里部分代码省略.........