【Python之路】特别篇--RabbitMQ
RabbitMQ
解释RabbitMQ，就不得不提到AMQP（Advanced Message Queuing Protocol）协议。 AMQP协议是一种基于网络的消息传输协议，它能够在应用或组织之间提供可靠的消息传输。RabbitMQ是该AMQP协议的一种实现，利用它，可以将消息安全可靠的从发 送方传输到接收方。简单的说，就是消息发送方利用RabbitMQ将信息安全的传递给接收方。
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。
1.简单队列模型
基于Queue实现生产者,消费者模型
#!/usr/bin/env python # -*- coding:utf-8 -*- import Queue import threading message = 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。
生产者:
import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost'))
channel = connection.channel() channel.queue_declare(queue='hello') # 创建队列 channel.basic_publish(exchange='', routing_key='hello', body='Hello World!') print(" [x] Sent 'Hello World!'") connection.close()
消费者:
connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost'))
channel = connection.channel() channel.queue_declare(queue='hello') # 创建队列 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()
重要参数介绍：
（1）acknowledgment 消息不丢失
no_ack ＝ True，无应答,如果callback执行中断,数据丢失!
no_ack ＝ False，有应答, callback执行结束,告诉队列,删除原数据!
def callback(ch,method,properties,body): print(" [x] Received %r" % body) import time time.sleep(2) print('ok') ch.basic_ack(delivery_tag=method.delivery_tag) channel.basic_consume(callback,queue='s1',no_ack=False)
（2）durable 消息不丢失(数据持久化,保存硬盘)
生产者：
channel.queue_declare(queue='hello', durable=True) channel.basic_publish(exchange='', routing_key='hello', body='Hello World!', properties=pika.BasicProperties( delivery_mode=2, # 默认是1 make message persistent ))
消费者:
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)
（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,(谁先做完,就发给谁)
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()
2.exchange工作模型（fanout，direct，topic）
2.1 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
发布者:
import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) channel = connection.channel() channel.exchange_declare(exchange='logs', type='fanout') #创建交换机,指定名称,工作模式 message = "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) #不指定queue名字,rabbit会随机分配一个名字,exclusive=True会在使用此queue的消费者断开后,自动将queue删除 queue_name = result.method.queue channel.queue_bind(exchange='logs', queue=queue_name) # 队列绑定交换机 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()
2.2 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。
生产者:
import pika connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) channel = connection.channel() channel.exchange_declare(exchange='direct_logs', type='direct') severity = 'info' message = 'Hello World!' channel.basic_publish(exchange='direct_logs', routing_key=severity, body=message)
print(" [x] Sent %r:%r" % (severity, message)) connection.close()
消费者:
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) # 绑定多个关键字 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()
2.3 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
生产者:
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()
消费者:
import pika,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()
Remote procedure call (RPC)
#!/usr/bin/env python # -*-coding:utf-8 -*- import pika import subprocess credentials = pika.PlainCredentials('firefly','123456') connection = pika.BlockingConnection(pika.ConnectionParameters( host = '192.168.18.147', credentials=credentials )) channel = connection.channel() channel.queue_declare(queue='rpc_queue') def on_request(ch,method,props,body): cmd = str(body,encoding='utf-8') cmd_obj = subprocess.Popen(cmd,shell=True,stdout=subprocess.PIPE,stderr=subprocess.PIPE) response = cmd_obj.stdout.read() + cmd_obj.stderr.read() ch.basic_publish(exchange='', routing_key=props.reply_to, properties=pika.BasicProperties(correlation_id=props.correlation_id), body=response) ch.basic_ack(delivery_tag=method.delivery_tag) channel.basic_qos(prefetch_count=1) channel.basic_consume(on_request, queue='rpc_queue') print(" [x] Awaiting RPC requests") channel.start_consuming()
#!/usr/bin/env python # -*-coding:utf-8 -*- import pika import uuid class RPCServer(object): def __init__(self): self.credentials = pika.PlainCredentials('firefly','123456') self.connection = pika.BlockingConnection(pika.ConnectionParameters( host = '192.168.18.147', credentials=self.credentials )) self.channel = self.connection.channel() result = self.channel.queue_declare(exclusive=True) self.callback_queue = result.method.queue self.channel.basic_consume(self.on_response,no_ack=True,queue=self.callback_queue) def on_response(self, ch, method, props, body): if self.corr_id == props.correlation_id: self.response = body def call(self,inp): self.response = None self.corr_id = str(uuid.uuid4()) self.channel.basic_publish(exchange='', routing_key='rpc_queue', properties=pika.BasicProperties( reply_to=self.callback_queue, correlation_id=self.corr_id, ), body=inp) while self.response is None: self.connection.process_data_events() return self.response rep_server = RPCServer() print('Waiting Replay') response = rep_server.call('ipconfig') print(response.decode('gbk'))
