RabbitMQ(pika模块)
RabbitMQ
基础
关于MQ:
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
1 2 3 4 5 6 7 8 | 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 install erlang 安装RabbitMQ $ yum -y install rabbitmq-server |
启动/停止:
1 | systemctl start/stop rabbitmq |
安装python-API:
1 2 3 4 5 6 7 | pip install pikaoreasy_install pikaor源码 https://pypi.python.org/pypi/pika |
API基础操作
先来看看使用RabbitMQ之前,怎么实现消息队列:利用Queue和Thread,每线程往内存里的队列里put一个数,另一个程序再去内存队列里取数。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | import Queueimport threadingmessage = Queue.Queue(10)def producer(i): while True: message.put(i)def consumer(i): while True: msg = message.get()for i in range(12): t = threading.Thread(target=producer, args=(i,)) t.start()for i in range(10): t = threading.Thread(target=consumer, args=(i,)) t.start() |
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 2 3 4 5 6 7 8 9 10 11 12 13 14 | import pika# ######################### 生产者 #########################connection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.136.8'))channel = connection.channel() #创建通道channel.queue_declare(queue='hello') #队列名称channel.basic_publish(exchange='', routing_key='hello', #路由名称 body='Hello World!') #发送内容print(" [x] Sent 'Hello World!'")connection.close() |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | import pika# ########################## 消费者 ##########################connection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.136.8'))channel = connection.channel()channel.queue_declare(queue='hello') #声明,队列名称,和producer创建的重复没有关系def callback(ch, method, properties, body): print(" [x] Received %r" % body)channel.basic_consume(callback, #获取body后执行回调函数 queue='hello', no_ack=True) #自动应答开启,会给MQ服务器发送一个ack:‘已经收到了’。print(' [*] Waiting for messages. To exit press CTRL+C')channel.start_consuming() |
消费者运行起来后会和RabbitMQ建立长连接,一旦生产者放数据到队列里,消费者就能获取到该值,并进行处理。
1 2 | [root@localhost ~]# netstat -ntp |grep beamtcp6 0 0 192.168.136.8:5672 192.168.136.1:52587 ESTABLISHED 1146/beam |
消息安全
1、no-ack = False(自动应答关闭)
如果生产者遇到情况(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。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | import pika#no-ack########################### 消费者 ##########################connection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.136.8'))channel = connection.channel()channel.queue_declare(queue='hello')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) #主动发送ack #打印‘ok’后才告诉MQ,这个消息已经处理完了。channel.basic_consume(callback, queue='hello', no_ack=False) #自动应答关闭,与channel.basic_ack共同使用print(' [*] Waiting for messages. To exit press CTRL+C')channel.start_consuming() |
2、durable
make message persistent 使消息持久化
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | import pika#durable########################## 生产者 #########################connection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.136.8'))channel = connection.channel()channel.queue_declare(queue='hello', durable=True) #开启持久化channel.basic_publish(exchange='', routing_key='hello', body='Hello World!', properties=pika.BasicProperties( delivery_mode=2, # make message persistent ))print(" [x] Sent 'Hello World!'")connection.close() |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | import pika#durable########################## 消费者 #########################connection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.136.8'))channel = connection.channel()# make message persistentchannel.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(' [*] 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奇偶顺序被消费者拿走,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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | import pikaconnection = pika.BlockingConnection(pika.ConnectionParameters(host='10.211.55.4'))channel = connection.channel()# make message persistentchannel.queue_declare(queue='hello')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) #增加这行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
与消息队列区别:
消息队列中的数据只要被消费一次便消失。
创建队列的数量:
同一份消息,有多少订阅者,就要创建多少个队列。(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。)
语法:
exchange type = fanout #fanout==>输出到很多
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # ######################### 发布者 #########################import pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.136.8'))channel = connection.channel()channel.exchange_declare(exchange='fanout_name',type='fanout')message = ' '.join(sys.argv[1:]) or "info: Hello World!"channel.basic_publish(exchange='fanout_name', #自命名exchange routing_key='', body=message)print(" [x] Sent %r" % message)connection.close() |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | # ########################## 订阅者1 ##########################import pikaconnection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.136.8'))channel = connection.channel()channel.exchange_declare(exchange='fanout_name',type='fanout') #创建exchange(if not exist)result = channel.queue_declare(exclusive=True)queue_name = result.method.queue #获取队列名称channel.queue_bind(exchange='fanout_name',queue=queue_name) #通过上面两个值绑定队列print(' [*] Waiting for fanout_name. 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() |
创建多个订阅者,能更好的体现它的效果。
运行结果总结:
每个订阅者创建一个exchange队列,名称自定,发布者会把数据发送给所有叫这个名字的队列。因为数据只能被消费一次,所以有多少个订阅者,就有多少个队列。
发送到指定(not 固定)队列
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
1、按关键字寻找队列发送
exchange type = direct
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。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | # ######################### 生产者 ##########################关键字发送import pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters( host='192.168.136.8'))channel = connection.channel()channel.exchange_declare(exchange='direct_logs', type='direct')message = 'Hello World!'channel.basic_publish(exchange='direct_logs', routing_key="yes", #"yes","no","db" body=message)print(" [x] Sent %r" % (message))connection.close() |
模拟两个消费者,一个消费者的队列是("yes","db"),另一个消费者队列("no","db")。如果生产者发送的队列关键字是"yes"or"no",其一匹配;如果生产者发送的队列关键字是"db",则两个消费者都能接收到。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ########################### 消费者1 ##########################import pikaimport sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='192.168.136.8'))channel = connection.channel() channel.exchange_declare(exchange='direct_logs', type='direct') result = channel.queue_declare(exclusive=True)queue_name = result.method.queuechannel.queue_bind(exchange='direct_logs', queue=queue_name, routing_key='yes')channel.queue_bind(exchange='direct_logs', queue=queue_name, routing_key='db') 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() |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ########################### 消费者2 ##########################import pikaimport sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='192.168.136.8'))channel = connection.channel() channel.exchange_declare(exchange='direct_logs', type='direct') result = channel.queue_declare(exclusive=True)queue_name = result.method.queuechannel.queue_bind(exchange='direct_logs', queue=queue_name, routing_key='no')channel.queue_bind(exchange='direct_logs', queue=queue_name, routing_key='db') 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() |
2、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
1 2 3 | 发送者路由值 队列中python.topic.cn python.* -- 不匹配python.topic.cn python.# -- 匹配 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # ######################### 生产者 ##########################模糊匹配import pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters( host='192.168.136.8'))channel = connection.channel()channel.exchange_declare(exchange='topic_logs', type='topic')message = 'Hello World!'channel.basic_publish(exchange='topic_logs', routing_key="python.topic", body=message)print(" [x] Sent %r" % (message))connection.close() |
消费者1是‘*’匹配,消费者2是‘#’匹配:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ########################### 消费者1 ##########################import pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters( host='192.168.136.8'))channel = connection.channel()channel.exchange_declare(exchange='topic_logs', type='topic')result = channel.queue_declare(exclusive=True)queue_name = result.method.queuechannel.queue_bind(exchange='topic_logs', queue=queue_name, routing_key='python.*') #只匹配python.后有一个单词的print(' [*] Waiting for topic_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() |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 | ########################### 消费者2 ##########################import pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters( host='192.168.136.8'))channel = connection.channel()channel.exchange_declare(exchange='topic_logs', type='topic')result = channel.queue_declare(exclusive=True)queue_name = result.method.queuechannel.queue_bind(exchange='topic_logs', queue=queue_name, routing_key='python.#') #匹配python.后所有单词print(' [*] Waiting for topic_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() |
从结果得出结论,如果生产者发送的routing_key是:
python.topic.cn --> 只有消费者2能接收到
python.cn --> 消费者1和消费者2都能接收到
python. --> 消费者1和消费者2都能接收到
python --> 只有消费者2能接收到
网络搜索的概念:
Topic Exchange – 主题式交换器,通过消息的路由关键字和绑定关键字的模式匹配,将消息路由到被绑定的队列中。
这种路由器类型可以被用来支持经典的发布/订阅消息传输模型——使用主题名字空间作为消息寻址模式,将消息传递给那些部分或者全部匹配主题模式的多个消费者。
主题交换器类型的工作方式如下: 绑定关键字用零个或多个标记构成,每一个标记之间用“.”字符分隔。
绑定关键字必须用这种形式明确说明,并支持通配符:“*”匹配一个词组,“#”零个或多个词组。
因此绑定关键字“*.stock.#”匹配路由关键字“usd.stock”和“eur.stock.db”,但是不匹配“stock.nasdaq”
参考来源:http://www.cnblogs.com/wupeiqi/

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