我正在使用RabbitMQ
个队列。我想通过一个程序运行多个消费者对象实例。以下是我创建Operator
1 producer and 1 consumer
课程
class Operator(object):
def __init__(self, delegate: callable, identifier):
"""
Create a new instance of the Operator and initialize the connections
"""
self._queue_details = self._get_queue_details()
self._host_ip = self._queue_details['IP']
self._port = self._queue_details['Port']
self._username = self._queue_details['Username']
self._password = self._queue_details['Password']
self._input_queue_name = self._queue_details['ReadQueueName']
self._output_queue_name = self._queue_details['WriteQueueName']
self._error_queue_name = self._queue_details['ErrorQueueName']
self._delegate = delegate
self._identifier = identifier
self._queue_connection = None
self._input_channel = None
self._output_channel = None
self._error_channel = None
self.is_busy = False
self.mark_to_terminate = False
def __del__(self):
# close connections
self._queue_connection.close()
@staticmethod
def _initialize_channel(connection, queue_name, durable):
channel = connection.channel()
channel.queue_declare(queue=queue_name, durable=durable)
return channel
@staticmethod
def _get_queue_details() -> dict:
return ConfigurationManager().get_value('queueDetails')
@staticmethod
def _get_connection(username, password, host_ip, port):
connection = pika.BlockingConnection(pika.ConnectionParameters(
credentials=pika.PlainCredentials(username, password), host=host_ip, port=port))
return connection
def initialize_operator(self):
connection = self._get_connection(self._username, self._password, self._host_ip, self._port)
self._queue_connection = connection
self._input_channel = self._initialize_channel(connection, self._input_queue_name, durable=False)
self._output_channel = self._initialize_channel(connection, self._output_queue_name, durable= True)
self._error_channel = self._initialize_channel(connection, self._error_queue_name, durable=True)
def consume(self):
self._input_channel.basic_qos(prefetch_count=1)
self._input_channel.basic_consume(self._process_incoming_message, queue=self._input_queue_name)
self._input_channel.start_consuming()
def _push_to_queue(self, channel, response):
channel.basic_publish(exchange='', routing_key=self._output_queue_name, body=response,
properties=pika.BasicProperties(delivery_mode=2)) # make message persistent
def _process_incoming_message(self, channel, method, properties, message):
self.is_busy = True
processed_result, is_error = self._delegate(message)
if is_error:
self._error_channel.basic_publish(exchange='', routing_key=self._output_queue_name, body=processed_result,
properties=pika.BasicProperties(delivery_mode=2))
else:
self._output_channel.basic_publish(exchange='', routing_key=self._output_queue_name, body=processed_result,
properties=pika.BasicProperties(delivery_mode=2))
# send in the final ack of the process.
channel.basic_ack(delivery_tag=method.delivery_tag)
# close connection if to avoid receiving messages
if self.mark_to_terminate:
self._queue_connection.close()
self.is_busy = False
从我的主要剧本中我启动代理如下:
# spins up the agent
for count in range(spin_up_count):
instance = Operator(self._translate_and_parse, f'Operator: {time.time()}')
instance.initialize_operator()
process = Process(target=instance.consume)
process.start()
self._online_agents.append((instance, process))
问题是,当我去process.start()
时,它会向我投掷TypeError
TypeError:无法挑选_thread.lock对象
完成堆栈跟踪
File "C:/Users/adity/Documents/PythonProjects/Caligo/Caligo/QueueService.py", line 201, in _scale_up
process.start()
File "C:\Users\adity\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\process.py", line 105, in start
self._popen = self._Popen(self)
File "C:\Users\adity\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\context.py", line 223, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "C:\Users\adity\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\context.py", line 322, in _Popen
return Popen(process_obj)
File "C:\Users\adity\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\popen_spawn_win32.py", line 65, in __init__
reduction.dump(process_obj, to_child)
File "C:\Users\adity\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\reduction.py", line 60, in dump
ForkingPickler(file, protocol).dump(obj)
TypeError: can't pickle _thread.lock objects
答案 0 :(得分:0)
RabbitMQ团队监控the rabbitmq-users
mailing list,有时只回答StackOverflow上的问题。
在启动分叉进程之前,不要实例化Operator
个对象。您也无法使instance.consume
成为分叉流程的目标。
target
实例的Process
方法应创建Operator
实例,然后调用consume
方法。
如果您需要管理分叉流程,您应该跟踪流程ID并使用信号与它们进行通信。