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远程调用

Table of Contents

RPC模式

生产者发送消息给Exchange, Exchange把消息推送给消费者，消费者接收，处理完消息，返回响应给生产者

客户端接口

生产者创建一个FibonacciRpcClient的客户端，call方法会发送消息给rabbitMQ，阻塞当前程序直到收到响应为止 

fibonacci_rpc = FibonacciRpcClient()
result = fibonacci_rpc.call(4)
print("fib(4) is %r" % result)

回调队列

生产者在发送消息前会创建一个回调队列，用来接收消费者发回的响应,在发送消息的时候用reply_to属性标记回调队列，而当消费者处理完消息后把结果包装到响应内再发送给回调队列 

result = channel.queue_declare(exclusive=True)
callback_queue = result.method.queue

channel.basic_publish(exchange='',
                      routing_key='rpc_queue',
                      properties=pika.BasicProperties(
                          reply_to = callback_queue,
                      ),
                      body=request)

correlation id

同一个rpc客户端接口可能发送多次请求，而通过同一个回调队列也相应会接收到多次返回响应，为了标明哪个响应对应哪个请求，所以在发送请求的时候会带上一个id, 这个id就用correlation_id来标识 

result = channel.queue_declare(exclusive=True)
callback_queue = result.method.queue
corr_id = 123456789
channel.basic_publish(exchange='',
                      routing_key='rpc_queue',
                      properties=pika.BasicProperties(
                          reply_to = callback_queue,
                          correlation_id = corr_id,
                      ),
                      body=request)

综合实例

rpc.png

生产者

#!/usr/bin/env python
import pika
import uuid

class FibonacciRpcClient(object):
    def __init__(self):
        self.connection = pika.BlockingConnection(pika.ConnectionParameters(
                host='localhost'))

        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(30)")
response = fibonacci_rpc.call(30)
print(" [.] Got %r" % response)
  1. 建立与rabbitMQ服务器的connect, channel, 以及声明一个回调队列callback_queue
  2. self.channel.basic_consume：注册callback队列，监听响应
  3. 'on_response'：检查响应中的correlation_id是否和发送的一致，如果一致把响应的body保存下来
  4. call：产生唯一的correletion_id, 发送消息给rabbitMQ服务器，盲等待响应到了，返回最后结果

消费者

#!/usr/bin/env python
import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(
        host='localhost'))

channel = connection.channel()

channel.queue_declare(queue='rpc_queue')

def fib(n):
    if n == 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fib(n-1) + fib(n-2)

def on_request(ch, method, props, body):
    n = int(body)

    print(" [.] fib(%s)" % n)
    response = fib(n)

    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)

channel.basic_qos(prefetch_count=1)
channel.basic_consume(on_request, queue='rpc_queue')

print(" [x] Awaiting RPC requests")
channel.start_consuming()

消费者接受消息，解析计算参数，计算结果，包装响应，发送消息给回调队列。注意：routing_key=props.rely_to, correlation_id = props.correlation_id

测试

启动消费者 

$ python rpc_server.py

[x] Awaiting RPC requests

发送rpc请求，等待计算结果 

$ python rpc_client.py

[x] Requesting fib(30)

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