RbbitMQ（消息队列） #简单模式 服务端 import pika #连接 connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) 连接通道 channel = connection.channel() 声明队列 channel.queue_declare(queue='hello') 发送数据 channel.basic_publish(exchange='', routing_key='hello', body='Hello World!') print(" [x] Sent 'Hello World!'") 结束连接 connection.close() # ########################## 客户端 ########################## #获得连接对象 connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost')) 获得连接通道 channel = connection.channel() #声明队列 channel.queue_declare(queue='hello') 回调函数 def callback(ch, method, properties, body): print(" [x] Received %r" % body) #从通道取出数据执行回调函数 channel.basic_consume( callback, queue='hello', #队列名 no_ack=True) print(' [*] Waiting for messages. To exit press CTRL+C') 在通道等待数据传递过来 channel.start_consuming() #############################防止掉线客户端######################################## #no-ack ＝ False，如果消费者遇到情况挂掉了，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 import pika #连接 connection = pika.BlockingConnection(pika.ConnectionParameters( host='10.211.55.4')) 连接通道 channel = connection.channel() 声明队列 channel.queue_declare(queue='hello') def callback(ch, method, properties, body): print(" [x] Received %r" % body) import time time.sleep(10) print 'ok' #执行这行代码之后，才把数据销毁 ch.basic_ack(delivery_tag = method.delivery_tag) 获得管道数据执行回调函数 channel.basic_consume(callback, queue='hello', no_ack=False) print(' [*] Waiting for messages. To exit press CTRL+C') 等待 channel.start_consuming() #########################durable ：消息不丢失（服务端）########################################3 import pika 连接 connection = pika.BlockingConnection(pika.ConnectionParameters(host='10.211.55.4')) 连接通道 channel = connection.channel() 声明队列 channel.queue_declare(queue='hello', durable=True) push数据 channel.basic_publish(exchange='', #交换 routing_key='hello', body='Hello World!', 基础属性 properties=pika.BasicProperties( delivery_mode=2, # make message persistent #让消息持久发送 )) print(" [x] Sent 'Hello World!'") connection.close() ##################################消息不丢失（客户端）#############################################）############################################# import pika 连接 connection = pika.BlockingConnection(pika.ConnectionParameters(host='10.211.55.4')) 通道 channel = connection.channel() 生成队列 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' #确认 ch.basic_ack(delivery_tag = method.delivery_tag) 基础消耗方法，执行回调 channel.basic_consume(callback, queue='hello', no_ack=False) print(' [*] Waiting for messages. To exit press CTRL+C') 开始消耗 channel.start_consuming() ################################## (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 ################################客户端################################## 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' #确认， ch.basic_ack(delivery_tag = method.delivery_tag) #谁来谁取 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############# exchange type = fanout #交换类型 #############服务端######################## import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) channel = connection.channel() 声明交流 channel.exchange_declare(exchange='logs', type='fanout') message = ' '.join(sys.argv[1:]) or "info: Hello World!" push数据 channel.basic_publish(exchange='logs', #交流name routing_key='', body=message) print(" [x] Sent %r" % message) connection.close() ########################客户端################################################## # 消费者 #!/usr/bin/env python import pika connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) channel = connection.channel() 声明交流 channel.exchange_declare(exchange='logs', type='fanout') #订阅 声明队列 result = channel.queue_declare(exclusive=True) #队列名 queue_name = result.method.queue 与队列捆绑 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) 基本消耗 channel.basic_consume(callback, queue=queue_name, no_ack=True) #保护数据 #消耗通道 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。 ###########################客户端######################################## import pika import sys connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) 连接通道 channel = connection.channel() 声明交流 channel.exchange_declare(exchange='direct_logs', type='direct') #直接 声明队列 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] " % sys.argv[0]) sys.exit(1) for severity in severities: channel.queue_bind(exchange='direct_logs', queue=queue_name, routing_key=severity) 就是这个 print(' [*] Waiting for logs. To exit press CTRL+C') def callback(ch, method, properties, body): print(" [x] %r:%r" % (method.routing_key, body)) 消耗，获取队列信息回调 channel.basic_consume(callback, queue=queue_name, no_ack=True) 开始消耗 channel.start_consuming() ############################# 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 ##############################模糊查找############################################ import pika import sys 连接 connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) 管道 channel = connection.channel() 交流 channel.exchange_declare(exchange='topic_logs', type='topic') 话题 声明队列 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: 与队列捆绑 channel.queue_bind(exchange='topic_logs', queue=queue_name, routing_key=binding_key) #查找# 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############### 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。 ###################################服务器#### # 建立连接，服务器地址为localhost，可指定ip地址 connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) # 建立会话 channel = connection.channel() # 声明RPC请求队列 channel.queue_declare(queue='rpc_queue') # 数据处理方法 def fib(n): if n == 0: return 0 elif n == 1: return 1 else: return fib(n-1) + fib(n-2) # 对RPC请求队列中的请求进行处理 def on_request(ch, method, props, body): n = int(body) print(" [.] fib(%s)" % n) # 调用数据处理方法 response = fib(n) # 将处理结果(响应)发送到回调队列 ch.basic_publish(exchange='', routing_key=props.reply_to, properties=pika.BasicProperties(correlation_id = props.correlation_id), body=str(response)) ch.basic_ack(delivery_tag = method.delivery_tag) # 负载均衡，同一时刻发送给该服务器的请求不超过一个 channel.basic_qos(prefetch_count=1) channel.basic_consume(on_request, queue='rpc_queue') print(" [x] Awaiting RPC requests") channel.start_consuming() ################################################################## import pika import uuid class FibonacciRpcClient(object): def __init__(self): ”“” 客户端启动时，创建回调队列，会开启会话用于发送RPC请求以及接受响应 “”“ # 建立连接，指定服务器的ip地址 self.connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost')) # 建立一个会话，每个channel代表一个会话任务 self.channel = self.connection.channel() # 声明回调队列，再次声明的原因是，服务器和客户端可能先后开启，该声明是幂等的，多次声明，但只生效一次 result = self.channel.queue_declare(exclusive=True) # 将次队列指定为当前客户端的回调队列 self.callback_queue = result.method.queue # 客户端订阅回调队列，当回调队列中有响应时，调用`on_response`方法对响应进行处理; self.channel.basic_consume(self.on_response, no_ack=True, queue=self.callback_queue) # 对回调队列中的响应进行处理的函数 def on_response(self, ch, method, props, body): if self.corr_id == props.correlation_id: self.response = body # 发出RPC请求 def call(self, n): # 初始化 response self.response = None #生成correlation_id self.corr_id = str(uuid.uuid4()) # 发送RPC请求内容到RPC请求队列`rpc_queue`，同时发送的还有`reply_to`和`correlation_id` self.channel.basic_publish(exchange='', routing_key='rpc_queue', properties=pika.BasicProperties( reply_to = self.callback_queue, correlation_id = self.corr_id, ), body=str(n)) while self.response is None: self.connection.process_data_events() return int(self.response) # 建立客户端 fibonacci_rpc = FibonacciRpcClient() # 发送RPC请求 print(" [x] Requesting fib(30)") response = fibonacci_rpc.call(30) print(" [.] Got %r" % response)