rabbitmq 生产者 消费者（多个线程消费同一个队列里面的任务。）

Posted 2021-01-28 北风之神0509

rabbitmq作为消息队列可以有消息消费确认机制，redis的list结构可以简单充当消息队列，但不具备消费确认机制，随意关停程序，会丢失一部分正在程序中处理但还没执行完的消息。

使用rabbitmq的最常用库pika

 

 

# coding=utf-8
"""
一个通用的rabbitmq生产者和消费者。使用多个线程消费同一个消息队列。
"""
import abc
import functools
import time
from threading import Lock
from pika import BasicProperties
# noinspection PyUnresolvedReferences
from app.utils_ydf import (LoggerMixin, LogManager, decorators, RabbitMqHelper, BoundedThreadPoolExecutor)


class RabbitmqPublisher(LoggerMixin):
    def __init__(self, queue_name):
        self._queue_name = queue_name
        channel = RabbitMqHelper().creat_a_channel()
        channel.queue_declare(queue=queue_name, durable=True)
        self.channel = channel
        self.lock = Lock()

    def publish(self, msg):
        with self.lock:
            self.channel.basic_publish(exchange=‘‘,
                                       routing_key=self._queue_name,
                                       body=msg,
                                       properties=BasicProperties(
                                           delivery_mode=2,  # make message persistent
                                       )
                                       )
            self.logger.debug(f‘放入 {msg} 到 {self._queue_name} 队列中‘)


class RabbitmqConsumer(LoggerMixin, ):
    def __init__(self, queue_name, consuming_function=None, threads_num=100, max_retry_times=3, log_level=1, is_print_detail_exception=True):
        """
        :param queue_name:
        :param consuming_function: 处理消息的函数，函数有且只能有一个参数，参数表示消息。
        :param threads_num:
        :param max_retry_times:
        :param log_level:
        :param is_print_detail_exception:
        """
        self._queue_name = queue_name
        self.consuming_function = consuming_function
        self.threadpool = BoundedThreadPoolExecutor(threads_num)
        self._max_retry_times = max_retry_times
        self.logger.setLevel(log_level * 10)
        self.logger.info(f‘{self.__class__} 被实例化‘)
        self._is_print_detail_exception = is_print_detail_exception
        self.rabbitmq_helper = RabbitMqHelper(heartbeat_interval=30)
        channel = self.rabbitmq_helper.creat_a_channel()
        channel.queue_declare(queue=self._queue_name, durable=True)
        channel.basic_qos(prefetch_count=threads_num)
        self.channel = channel
        LogManager(‘pika.heartbeat‘).get_logger_and_add_handlers(1)

    @decorators.keep_circulating(1)    # 是为了保证无论rabbitmq异常中断多久，无需重启程序就能保证恢复后，程序正常。
    def start_consuming_message(self):
        def callback(ch, method, properties, body):
            msg = body.decode()
            self.logger.debug(f‘从rabbitmq取出的消息是：  {msg}‘)
            # ch.basic_ack(delivery_tag=method.delivery_tag)
            self.threadpool.submit(self.__consuming_function, ch, method, properties, msg)

        self.channel.basic_consume(callback,
                                   queue=self._queue_name,
                                   # no_ack=True
                                   )
        self.channel.start_consuming()

    @staticmethod
    def ack_message(channelx, delivery_tagx):
        """Note that `channel` must be the same pika channel instance via which
        the message being ACKed was retrieved (AMQP protocol constraint).
        """
        if channelx.is_open:
            channelx.basic_ack(delivery_tagx)
        else:
            # Channel is already closed, so we can‘t ACK this message;
            # log and/or do something that makes sense for your app in this case.
            pass

    def __consuming_function(self, ch, method, properties, msg, current_retry_times=0):
        if current_retry_times < self._max_retry_times:
            # noinspection PyBroadException
            try:
                self.consuming_function(msg)
                # ch.basic_ack(delivery_tag=method.delivery_tag)
                self.rabbitmq_helper.connection.add_callback_threadsafe(functools.partial(self.ack_message, ch, method.delivery_tag))
            except Exception as e:
                self.logger.error(f‘函数 {self.consuming_function}  第{current_retry_times+1}次发生错误，\n 原因是{e}‘, exc_info=self._is_print_detail_exception)
                self.__consuming_function(ch, method, properties, msg, current_retry_times + 1)
        else:
            self.logger.critical(f‘达到最大重试次数 {self._max_retry_times} 后,仍然失败‘)
            # ch.basic_ack(delivery_tag=method.delivery_tag)
            self.rabbitmq_helper.connection.add_callback_threadsafe(functools.partial(self.ack_message, ch, method.delivery_tag))


if __name__ == ‘__main__‘:
    rabbitmq_publisher = RabbitmqPublisher(‘queue_test‘)
    [rabbitmq_publisher.publish(str(i)) for i in range(1000)]


    def f(msg):
        print(‘....  ‘, msg)
        time.sleep(10)  # 模拟做某事需要10秒种。


    rabbitmq_consumer = RabbitmqConsumer(‘queue_test‘, consuming_function=f, threads_num=20)
    rabbitmq_consumer.start_consuming_message()