一、RabbitMQ安装
RabbitMQ是一个在AMQP基础上完整的,可复用的企业消息系统,它遵循Mozilla Pulic 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,而无需专用链接来链接它们。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。
1.yum安装rabbitmq
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#安装配置epel源 rpm - ivh http: / / dl.fedoraproject.org / pub / epel / 6 / i386 / epel - release - 6 - 8.noarch .rpm #安装Erlang yum - y insatll erlang #安装RabbitMQ yum - y install rabbitmq - server #注意: service rabbitmq - server start / stop |
2,安装API
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#pip安装: pip install pika #源码安装: https: / / pypi.python.org / pypi / pika #官网地址 |
之前我们在介绍线程,进程的时候介绍过python中自带的队列用法,下面我们通过一段代码复习一下:
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#生产者消费者模型,解耦的意思就是两个程序之间,互相没有关联了,互不影响。 import queue import threading import time q = queue.Queue( 20 ) #队列里最多存放20个元素 def productor(arg): #生成者,创建30个线程来请求吃包子,往队列里添加请求元素 q.put( str (arg) + '- 包子' ) for i in range ( 30 ): t = threading.Thread(target = productor,args = (i,)) t.start() def consumer(arg): #消费者,接收到队列请求以后开始生产包子,来消费队列里的请求 while True : print (arg,q.get()) time.sleep( 2 ) for j in range ( 3 ): t = threading.Thread(target = consumer,args = (j,)) t.start() |
二、通过Python来操作RabbitMQ队列
上面我们已经将环境装备好,下面我们通过Pika模块来对Rabbitmq队列来进行操作,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。
1,基本用法
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####################################生产者##################################### import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host = '192.168.10.131' )) #创建一个链接对象,对象中绑定rabbitmq的IP地址 channel = connection.channel() #创建一个频道 channel.queue_declare(queue = 'name1' ) #通过这个频道来创建队列,如果MQ中队列存在忽略,没有则创建 channel.basic_publish(exchange = '', routing_key = 'name1' , #指定队列名称 body = 'Hello World!' ) #往该队列中发送一个消息 print ( " [x] Sent 'Hello World!'" ) connection.close() #发送完关闭链接 |
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#####################################消费者###################################### import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host = '192.168.10.131' )) #创建一个链接对象,对象中绑定rabbitmq的IP地址 channel = connection.channel() #创建一个频道 channel.queue_declare(queue = 'name1' ) #通过这个频道来创建队列,如果MQ中队列存在忽略,没有则创建 def callback(ch, method, properties, body): #callback函数负责接收队列里的消息 print ( " [x] Received %r" % body) channel.basic_consume(callback, #从队列里去消息 queue = 'name1' , #指定队列名 no_ack = True ) print ( ' [*] Waiting for messages. To exit press CTRL+C' ) channel.start_consuming() |
acknowledgment 消息不丢失
上面的例子中如果我们将no-ack=False ,那么当消费者遇到情况(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。
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import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host = '192.168.10.131' )) channel = connection.channel() channel.queue_declare(queue = 'name1' ) 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) #向生成者发送消费完毕的确认信息,然后生产者将此条消息同队列里剔除 channel.basic_consume(callback, queue = 'name1' , no_ack = False ) #如果no_ack=False,当消费者down掉了,RabbitMQ会重新将该任务添加到队列中 print ( ' [*] Waiting for messages. To exit press CTRL+C' ) channel.start_consuming() |
上例如果消费者中断后如果不超过10秒,重新链接的时候数据还在。当超过10秒之后,消费者往生产者发送了ack,重新链接的时候数据将消失。
durable消息不丢失
消费者down掉后我们知道怎么处理了,如果我的RabbitMQ服务down掉了该怎么办呢?
消息队列是可以做持久化,如果我们在生产消息的时候就指定某条消息需要做持久化,那么RabbitMQ发现有问题时,就会将消息保存到硬盘,持久化下来。
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####################################生产者##################################### #!/usr/bin/env python import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host = '192.168.10.131' )) channel = connection.channel() channel.queue_declare(queue = 'name2' , durable = True ) #指定队列持久化 channel.basic_publish(exchange = '', routing_key = 'name2' , body = 'Hello World!' , properties = pika.BasicProperties( delivery_mode = 2 , #指定消息持久化 )) print ( " [x] Sent 'Hello World!'" ) connection.close() |
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#####################################消费者######################################
#!/usr/bin/env python # -*- coding:utf-8 -*- import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host = '192.168.10.131' )) channel = connection.channel() channel.queue_declare(queue = 'name2' , 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 = 'name2' , no_ack = False ) print ( ' [*] Waiting for messages. 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的,例如:消费者1去队列中获取奇数序列任务,消费者2去队列中获取偶数序列的任务,消费者1处理的比较快而消费者2处理的比较慢,那么消费者1就会一直处于繁忙的状态,为了解决这个问题在需要加入下面代码:
channel.basic_qos(prefetch_count=1) :表示谁来获取,不再按照奇偶数 排列
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#!/usr/bin/env python # -*- coding:utf-8 -*- import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host = 'localhost' )) channel = connection.channel() channel.queue_declare(queue = 'name1' ) 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_qos(prefetch_count = 1 ) channel.basic_consume(callback, queue = 'name1' , no_ack = False ) print ( ' [*] Waiting for messages. To exit press CTRL+C' ) channel.start_consuming() |
2,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,二发布者发布消息时,会将消息放置在所有相关队列中。
在RabbitMQ中,所有生产者提交的消息都有Exchange来接收,然后Exchange按照特定的策略转发到Queue进行存储,RabbitMQ提供了四种Exchange:fanout、direct、topic、header。由于header模式在实际工作中用的比较少,下面主要对前三种进行比较。
exchange type = fanout :任何发送到Fanout Exchange的消息都会被转发到与该Exchange绑定(Binding)的所有Queue上
为了方便理解,应用了上面这张图,可以清晰的看到相互之间的关系,当我们设置成fanout模式时,如何操作请看下面代码:
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####################################发布者#####################################
import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host = 'localhost' )) channel = connection.channel() channel.exchange_declare(exchange = 'test_fanout' , type = 'fanout' ) message = '4456' channel.basic_publish(exchange = 'test_fanout' , routing_key = '', body = message) print ( ' [x] Sent %r' % message) connection.close() |
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####################################订阅者#####################################
import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host = 'localhost' )) channel = connection.channel() channel.exchange_declare(exchange = 'test_fanout' , #创建一个exchange type = 'fanout' ) #任何发送到Fanout Exchange的消息都会被转发到与该Exchange绑定(Binding)的所有Queue上 #随机创建队列 result = channel.queue_declare(exclusive = True ) queue_name = result.method.queue #绑定 channel.queue_bind(exchange = 'test_fanout' , queue = queue_name) #exchange绑定后端队列 print ( '<------------->' ) def callback(ch,method,properties,body): print ( ' [x] %r' % body) channel.basic_consume(callback, queue = queue_name, no_ack = True ) channel.start_consuming() |
exchange type = direct:任何发送到Direct Exchange的消息都会被转发到RouteKey中指定的Queue上(关键字发送)
之前事例,发送消息时明确指定了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。
发布者:
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#!/usr/bin/env python import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters(host = 'localhost' )) channel = connection.channel() channel.exchange_declare(exchange = 'direct_test' , type = 'direct' ) severity = 'info' #设置一个key, message = '99999' channel.basic_publish(exchange = 'direct_test' , routing_key = severity, body = message) print ( " [x] Sent %r:%r" % (severity, message)) connection.close() |
订阅者1:
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#!/usr/bin/env python import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters(host = 'localhost' )) channel = connection.channel() channel.exchange_declare(exchange = 'direct_test' , type = 'direct' ) result = channel.queue_declare(exclusive = True ) queue_name = result.method.queue severities = [ 'error' , 'info' ,] #绑定队列,并发送关键字error,info for severity in severities: channel.queue_bind(exchange = 'direct_test' , 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() |
订阅者2:
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#!/usr/bin/env python import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters(host = 'localhost' )) channel = connection.channel() channel.exchange_declare(exchange = 'direct_test' , type = 'direct' ) result = channel.queue_declare(exclusive = True ) queue_name = result.method.queue severities = [ 'error' ,] for severity in severities: channel.queue_bind(exchange = 'direct_test' , 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() |
结论:当我们将发布者的key设置成Error的时候两个队列对可以收到Exchange的消息,当我们将key设置成info后,只有订阅者1可以收到Exchange的消息。
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;
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* :表示只能匹配一个单词。
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#发送路由值 队列中 www.cnblogs.com www. * - - - > #无法匹配 www.cnblogs.com www. # --->#匹配成功 |
发布者:
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#!/usr/bin/env python 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() #执行方式: python xxx.py name1 #name1为routing_key |
订阅者:
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#!/usr/bin/env python 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]...
" % 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() #执行方式: python xxx,py name1 |