python学习-day11

一、Rabbitmq

       RabbitMQ 即一个消息队列，主要是用来实现应用程序的异步和解耦，同时也能起到消息缓冲，消息分发的作用。RabbitMQ使用的是AMQP协议，它是一种二进制协议。默认启动端口 5672。在 RabbitMQ 中，如下图结构：

• 左侧 P 代表 生产者，也就是往 RabbitMQ 发消息的程序。生产者需要完成的任务：

• 创建RabbitMQ连接
  获取信道
  声明交换器
  创建消息
  发布消息
  关闭信道
  关闭RabbitMQ连接 

• 中间即是 RabbitMQ，其中包括了 交换机 和 队列。
• 右侧 C 代表 消费者，也就是往 RabbitMQ 拿消息的程序。消费者需要完成的任务：

  创建RabbitMQ连接
  获取信道
  声明交换器
  声明队列
  队列和交换器绑定
  消费信息
  关闭信道
  关闭RabbitMQ连接

• Exchange: 接受客户端发送的消息，并根据Binding将消息路由给服务器中的队列，Exchange分为direct, fanout, topic三种。
• Binding: 连接Exchange和Queue，包含路由规则。
• Queue: 消息队列，存储还未被消费的消息。
• Message: Header+Body
• Channel: 通道，执行AMQP的命令；一个连接可创建多个通道以节省资源

1. dircted exchange

     路由键exchange，该交换机收到消息后会把消息发送到指定routing-key的queue中。rabbitmq内部默认有一个特殊的dircted exchange，该交换机的name是空字符串，所有queue都默认binding 到该交换机上。所有binding到该交换机上的queue，routing-key都和queue的name一样。

 生产者：

import pika
credentials = pika.PlainCredentials('admin', '123456')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '192.168.170.134',5672,'/',credentials))
channel = connection.channel()

# 声明queue
channel.queue_declare(queue='hello')

# n RabbitMQ a message can never be sent directly to the queue, it always needs to go through an exchange.
channel.basic_publish(exchange='',
                      routing_key='hello',
                      body='Hello World!')
print(" [x] Sent 'Hello World!'")
connection.close()

消费者：

import pika
credentials = pika.PlainCredentials('admin', '123456')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '192.168.170.134',5672,'/',credentials))
channel = connection.channel()
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()

 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。

生产者：

import pika,sys

credentials = pika.PlainCredentials('admin', '123456')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '192.168.170.134',5672,'/',credentials))
channel = connection.channel()
channel.exchange_declare(exchange='direct_logs',
                         type='direct')

severity = sys.argv[1] if len(sys.argv) > 1 else 'info'
message = ' '.join(sys.argv[2:]) or '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,sys

credentials = pika.PlainCredentials('admin', '123456')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '192.168.170.134',5672,'/',credentials))
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()

 运行结果：

2. fanout exchange

      发布/订阅exchange ，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。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。

生产者：

import pika,sys

credentials = pika.PlainCredentials('admin', '123456')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '192.168.170.134',5672,'/',credentials))
channel = connection.channel()
# 声明queue
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：

import pika

credentials = pika.PlainCredentials('admin', '123456')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '192.168.170.134',5672,'/',credentials))
channel = connection.channel()

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)

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()

 3. topic exchange

      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。

生产者：

import pika,sys

credentials = pika.PlainCredentials('admin', '123456')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '192.168.170.134',5672,'/',credentials))
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

credentials = pika.PlainCredentials('admin', '123456')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '192.168.170.134',5672,'/',credentials))
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()

 二、基于rabbitmq的RPC

      基于rabbitmq的rpc实现流程：

    （1）首先客户端发送一个reply_to和corrention_id的请求,发布到RPC队列中；

    （2）服务器端处理这个请求，并把处理结果发布到一个回调Queue,此Queue的名称应当与reply_to的名称一致

    （3）客户端从回调Queue中得到先前correlation_id设定的值的处理结果。如果碰到和先前不一样的corrention_id的值，将会忽略而不是抛出异常。

  对于上面所提到的回调Queue中的消费处理使用的是BasicProperties类。

服务端：

import pika

cre_publiser = pika.PlainCredentials('admin', '123456')
conn_para = pika.ConnectionParameters('192.168.170.134',5672,'/',cre_publiser)
connection = pika.BlockingConnection(conn_para)

# 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()

客户端：

import pika
import uuid
class FibonacciRpcClient(object):
    def __init__(self):
        self.cre_publiser = pika.PlainCredentials('admin', '123456')
        self.conn_para = pika.ConnectionParameters('192.168.170.134',5672,'/',self.cre_publiser)
        self.connection = pika.BlockingConnection(self.conn_para)

        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, n):
        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=str(n))
        while self.response is None:
            self.connection.process_data_events()
        return int(self.response)


fibonacci_rpc = FibonacciRpcClient()

print(" [x] Requesting fib(6)")
response = fibonacci_rpc.call(6)
print(" [.] Got %r" % response)