Python之路第十二天,高级(4)-Python操作rabbitMQ

mac2022-06-30  79

rabbitMQ

RabbitMQ是一个在AMQP基础上完整的,可复用的企业消息系统。他遵循Mozilla Public License开源协议。 MQ全称为Message Queue, 消息队列(MQ)是一种应用程序对应用程序的通信方法。应用程序通过读写出入队列的消息(针对应用程序的数据)来通信,而无需专用连接来链接它们。消 息传递指的是程序之间通过在消息中发送数据进行通信,而不是通过直接调用彼此来通信,直接调用通常是用于诸如远程过程调用的技术。排队指的是应用程序通过 队列来通信。队列的使用除去了接收和发送应用程序同时执行的要求。

RabbitMQ安装

CentOS: 1.安装epel源,其实就是一个yum配置文件,可以到/etc/yum.repo.d/里查看 [root@localhost ~]# yum -y install epel-release 2.安装erlang [root@localhost ~]# yum -y install erlang 3.安装RabbitMQ [root@localhost]# yum -y install rabbitmq-server 4.启动/停止 [root@localhost ~]# service rabbitmq-server start/stop

PYTHON API 安装

pip3 install pika

PYTHON 操作 rabbitMQ:

对于RabbitMQ来说,生产和消费不再针对内存里的一个Queue对象,而是某台服务器上的RabbitMQ Server实现的消息队列。

最基本的生产者消费者:

生产者代码:

import pika # 连接rabbit服务器(localhost是本机,如果是其他服务器请修改为ip地址) connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) # 创建频道 channel = connection.channel() # 创建一个队列名叫hello channel.queue_declare(queue='hello') # exchange -- 它使我们能够确切地指定消息应该到哪个队列去。 # 向队列插入数值 routing_key是队列名 body是要插入的内容 channel.basic_publish(exchange='', routing_key='hello', body='Hello World!') print("发送消息到队列里") #缓冲区已经flush而且消息已经确认发送到了RabbitMQ中,关闭链接 connection.close()

消费者代码:

import pika # 连接接rabbit connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) # 创建频道 channel = connection.channel() # 如果生产者没有运行创建队列,那么消费者也许就找不到队列了。为了避免这个问题 # 所有消费者也创建这个队列,如果这个队列存在,这条语句就不起作用了 channel.queue_declare(queue='hello') # 接收消息需要使用callback这个函数来接收,他会被pika库来调用 def callback(ch, method, properties, body): print(" [x] Received %r" % body) # 从队列取数据 callback是回调函数 如果拿到数据 那么将执行callback函数 channel.basic_consume(callback, queue='hello', no_ack=True) print(' [*] 等待信息. To exit press CTRL+C') # 永远循环等待数据处理和callback处理的数据 channel.start_consuming()

acknowledgment消息不丢失

no-ack = False,如果消费者遇到情况(its channel is closed, connection is closed, or TCP connection is lost)挂掉了,那么,RabbitMQ会重新将该任务添加到队列中。

生产者代码不变。

消费者:

import pika # 链接rabbit connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) # 创建频道 channel = connection.channel() # 如果生产者没有运行创建队列,那么消费者创建队列 channel.queue_declare(queue='hello') def callback(ch, method, properties, body): print(" [x] Received %r" % body) import time time.sleep(10) print 'ok' # 主要使用此代码 手动回复ACK ch.basic_ack(delivery_tag = method.delivery_tag) channel.basic_consume(callback, queue='hello', no_ack=False) print(' [*] Waiting for messages. To exit press CTRL+C') channel.start_consuming()

durable消息不丢失(持久化)

生产者:

import pika # 连接rabbit服务器 connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) # 创建频道 channel = connection.channel() # 创建队列,使用durable方法 channel.queue_declare(queue='hello', durable=True) #如果想让队列实现持久化那么加上durable=True channel.basic_publish(exchange='', routing_key='hello', body='Hello World!', properties=pika.BasicProperties( delivery_mode=2, # 标记我们的消息为持久化的 - 通过设置 delivery_mode 属性为 2 # 这样必须设置,让消息实现持久化 )) # 这个exchange参数就是这个exchange的名字. 空字符串标识默认的或者匿名的exchange:如果存在routing_key, 消息路由到routing_key指定的队列中。 print(" [x] 开始队列'") connection.close()

消费者:

import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) # 创建频道 channel = connection.channel() # 创建队列,使用durable方法 channel.queue_declare(queue='hello', durable=True) def callback(ch, method, properties, body): print(" [x] Received %r" % body) import time time.sleep(10) print 'ok' ch.basic_ack(delivery_tag = method.delivery_tag) channel.basic_consume(callback, queue='hello', no_ack=False) print(' [*] 等待队列. To exit press CTRL+C') channel.start_consuming()

消息获取顺序

默认消息队列里的数据是按照顺序被消费者拿走,例如:消费者1 去队列中获取 奇数 序列的任务,消费者2去队列中获取 偶数 序列的任务。

channel.basic_qos(prefetch_count=1) 表示谁来谁取,不再按照奇偶数排列。

import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) channel = connection.channel() channel.queue_declare(queue='hello'durable=True) # 设置队列持久化 def callback(ch, method, properties, body): print(" [x] Received %r" % body) import time time.sleep(10) print 'ok' # 消息未处理完前不要发送信息的消息 ch.basic_ack(delivery_tag = method.delivery_tag) # 表示谁来谁取,不再按照奇偶数排列 channel.basic_qos(prefetch_count=1) channel.basic_consume(callback, queue='hello', no_ack=False) print(' [*] Waiting for messages. To exit press CTRL+C') channel.start_consuming()

发布订阅

发布订阅和简单的消息队列区别在于,发布订阅会将消息发送给所有的订阅者,而消息队列中的数据被消费一次便消失。所以,RabbitMQ实现发布和订阅时,会为每一个订阅者创建一个队列,而发布者发布消息时,会将消息放置在所有相关队列中。

exchange type = fanout

发布者:

import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) channel = connection.channel() channel.exchange_declare(exchange='logs', type='fanout') message = ' '.join(sys.argv[1:]) or "info: Hello World!" channel.basic_publish(exchange='logs', routing_key='', body=message) print(" [x] Sent %r" % message) connection.close()

订阅者:

import pika connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) channel = connection.channel() channel.exchange_declare(exchange='logs', type='fanout') result = channel.queue_declare(exclusive=True) queue_name = result.method.queue channel.queue_bind(exchange='logs', queue=queue_name) print(' [*] Waiting for logs. To exit press CTRL+C') def callback(ch, method, properties, body): print(" [x] %r" % body) channel.basic_consume(callback, queue=queue_name, no_ack=True) channel.start_consuming()

关键字发送

exchange type = direct

之前事例,发送消息时明确指定某个队列并向其中发送消息,RabbitMQ还支持根据关键字发送,即:队列绑定关键字,发送者将数据根据关键字发送到消息exchange,exchange根据 关键字 判定应该将数据发送至指定队列。

发送者:

import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) channel = connection.channel() channel.exchange_declare(exchange='direct_logs', type='direct') severity = sys.argv[1] if len(sys.argv) > 1 else 'info' message = ' '.join(sys.argv[2:]) or 'Hello World!' channel.basic_publish(exchange='direct_logs', routing_key=severity, body=message) print(" [x] Sent %r:%r" % (severity, message)) connection.close()

订阅者:

import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) channel = connection.channel() channel.exchange_declare(exchange='direct_logs', type='direct') result = channel.queue_declare(exclusive=True) queue_name = result.method.queue severities = sys.argv[1:] if not severities: sys.stderr.write("Usage: %s [info] [warning] [error]\n" % sys.argv[0]) sys.exit(1) for severity in severities: channel.queue_bind(exchange='direct_logs', queue=queue_name, routing_key=severity) print(' [*] Waiting for logs. To exit press CTRL+C') def callback(ch, method, properties, body): print(" [x] %r:%r" % (method.routing_key, body)) channel.basic_consume(callback, queue=queue_name, no_ack=True) channel.start_consuming()

模糊匹配

exchange type = topic

在topic类型下,可以让队列绑定几个模糊的关键字,之后发送者将数据发送到exchange,exchange将传入”路由值“和 ”关键字“进行匹配,匹配成功,则将数据发送到指定队列。

# 表示可以匹配0个或多个单词* 表示只能匹配一个单词

发送者路由值 队列中

old.boy.python old.* -- 不匹配 old.boy.python old.# -- 匹配

发送者:

import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) channel = connection.channel() channel.exchange_declare(exchange='topic_logs', type='topic') routing_key = sys.argv[1] if len(sys.argv) > 1 else 'anonymous.info' message = ' '.join(sys.argv[2:]) or 'Hello World!' channel.basic_publish(exchange='topic_logs', routing_key=routing_key, body=message) print(" [x] Sent %r:%r" % (routing_key, message)) connection.close()

订阅者:

import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) channel = connection.channel() channel.exchange_declare(exchange='topic_logs', type='topic') result = channel.queue_declare(exclusive=True) queue_name = result.method.queue binding_keys = sys.argv[1:] if not binding_keys: sys.stderr.write("Usage: %s [binding_key]...\n" % sys.argv[0]) sys.exit(1) for binding_key in binding_keys: channel.queue_bind(exchange='topic_logs', queue=queue_name, routing_key=binding_key) print(' [*] Waiting for logs. To exit press CTRL+C') def callback(ch, method, properties, body): print(" [x] %r:%r" % (method.routing_key, body)) channel.basic_consume(callback, queue=queue_name, no_ack=True) channel.start_consuming()

转载于:https://www.cnblogs.com/zhangxunan/p/5703437.html

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