java入坑rabbitmq(Python操作rabbitMQ的示例代码)
java入坑rabbitmq
Python操作rabbitMQ的示例代码引入
rabbitmq 是一个由 erlang 语言开发的 amqp 的开源实现。
rabbitmq是一款基于amqp协议的消息中间件,它能够在应用之间提供可靠的消息传输。在易用性,扩展性,高可用性上表现优秀。使用消息中间件利于应用之间的解耦,生产者(客户端)无需知道消费者(服务端)的存在。而且两端可以使用不同的语言编写,大大提供了灵活性。
中文文档
安装
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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 install erlang # 安装rabbitmq yum - y install rabbitmq - server # 启动/停止 service rabbitmq - server start / stop |
rabbitmq工作模型
简单模式
生产者
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import pika connection = pika.blockingconnection(pika.connectionparameters( host = 'localhost' )) channel = connection.channel() channel.queue_declare(queue = 'hello' ) channel.basic_publish(exchange = '', routing_key = 'hello' , body = 'hello world!' ) print ( " [x] sent 'hello world!'" ) connection.close() |
消费者
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connection = pika.blockingconnection(pika.connectionparameters(host = 'localhost' )) channel = connection.channel() channel.queue_declare(queue = 'hello' ) def callback(ch, method, properties, body): print ( " [x] received %r" % body) channel.basic_consume( callback, queue = 'hello' , no_ack = true) print ( ' [*] waiting for messages. to exit press ctrl+c' ) channel.start_consuming() |
相关参数
1,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。
- 回调函数中的 ch.basic_ack(delivery_tag=method.delivery_tag)
- basic_comsume中的no_ack=false
接收消息端应该这么写:
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import pika connection = pika.blockingconnection(pika.connectionparameters( host = '10.211.55.4' )) 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) channel.basic_consume(callback, queue = 'hello' , no_ack = false) print ( ' [*] waiting for messages. to exit press ctrl+c' ) channel.start_consuming() |
2,durable :消息不丢失
生产者
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import pika connection = pika.blockingconnection(pika.connectionparameters(host = '10.211.55.4' )) channel = connection.channel() # make message persistent channel.queue_declare(queue = 'hello' , durable = true) 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() |
3,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1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
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import pika connection = pika.blockingconnection(pika.connectionparameters(host = '10.211.55.4' )) channel = connection.channel() # make message persistent 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) 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() |
exchange模型
1,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
生产者
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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() |
消费者
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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() |
2,关键字发送
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。
exchange type = direct
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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() |
3,模糊匹配
exchange type = topic
发送者路由值 队列中
old.boy.python old.* -- 不匹配
old.boy.python old.# -- 匹配
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
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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() |
基于rabbitmq的rpc
callback queue 回调队列
一个客户端向服务器发送请求,服务器端处理请求后,将其处理结果保存在一个存储体中。而客户端为了获得处理结果,那么客户在向服务器发送请求时,同时发送一个回调队列地址 reply_to 。
correlation id 关联标识
一个客户端可能会发送多个请求给服务器,当服务器处理完后,客户端无法辨别在回调队列中的响应具体和那个请求时对应的。为了处理这种情况,客户端在发送每个请求时,同时会附带一个独有 correlation_id 属性,这样客户端在回调队列中根据 correlation_id 字段的值就可以分辨此响应属于哪个请求。
客户端发送请求:
某个应用将请求信息交给客户端,然后客户端发送rpc请求,在发送rpc请求到rpc请求队列时,客户端至少发送带有reply_to以及correlation_id两个属性的信息
服务端工作流:
等待接受客户端发来rpc请求,当请求出现的时候,服务器从rpc请求队列中取出请求,然后处理后,将响应发送到reply_to指定的回调队列中
客户端接受处理结果:
客户端等待回调队列中出现响应,当响应出现时,它会根据响应中correlation_id字段的值,将其返回给对应的应用
服务者