python学习之rabbitmq

0、讲述rabbit中各部分的含义及作用

https://www.jb51.net/article/75647.htm

1、rabbitMQ的安装

1）在安装rabbitmq之前需要先安装erlang，下载地址如下：

http://www.erlang.org/downloads根据系统选择，安装按提示一直下一步就OK,安装完后，再安装rabbitmq

2、rabbitmq的下载地址：http://www.rabbitmq.com/download.html

3、rabbitmq队列

假设现在需要从武汉到北京去见一个网友，哈哈哈，先的打电话约下，然后确定路线和交通工具吧，这就是下边这段代码的实际模型

import pika
import random

connection = pika.BlockingConnection(pika.ConnectionParameters('localhost'))  #先打电话约下，看能否找到人
channel = connection.channel()                                               #确定路线
channel.queue_declare(queue='task_queue', durable=True)                      #确定交通工具，而且交通工具的名称叫‘task_queue',durable = True表示就是你到了北京以后交通工具依然存在

number = random.randint(1, 1000)
message = 'hello world:{num}'.format(num = number)

channel.basic_publish(exchange='',      #交换机，此时没有交换机参与，所以参数为空，
                       routing_key='task_queue',    #交通工具的名称
                       body=message,         #要发送给的内容
                       properties=pika.BasicProperties(
                           delivery_mode=2,)   #表示不管路通不通，你携带的消息都不会因为外界情况而消失
                      )
print(" [x] Sent %r" % (message,))
connection.close()

import pika
import time

hostname = 'localhost'
parameters = pika.ConnectionParameters(hostname)
connection = pika.BlockingConnection(parameters)

channel = connection.channel()
channel.queue_declare(queue='task_queue', durable=True)

def callback(ch, method, properties, body):
    print(" [x] Received %r" % (body,))
    # time.sleep(5)
    print(" [x] Done")
    ch.basic_ack(delivery_tag=method.delivery_tag)   #回调函数中需要给发布者发送的消息

channel.basic_qos(prefetch_count=1)

channel.basic_consume(callback, queue='task_queue', no_ack=False)  #no_ack=False当消费者接到消息后，需要调用回掉函数告诉发布者，消息的接受情况
print(' [*] Waiting for messages. To exit press CTRL+C')
channel.start_consuming()

下边的代码是通过交换机来实现消息的发送的，具体如下：

import pika

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

channel.exchange_declare(exchange='logs',      #交换机的名称为logs
                         exchange_type='fanout')

message = "info: Hello World!"
channel.basic_publish(exchange='logs',
                      routing_key='',
                      body=message)
print(" [x] Sent %r" % message)
connection.close()

import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost'))
channel = connection.channel()
channel.exchange_declare(exchange='logs',     #声明交换机的名称以及交换机发送消息的模式，这的名称要和publishor的交换机的名称相同，相当于publishor和consumor同时向exchange寻找，
                                              #否则publishor和consumor相互找不到，会迷路！！
                            exchange_type='fanout')      #这不同的版本有可能会出错，有的说的是可以写为type = 'fanout',在我的电脑上运行会出错，
                                                         #改为exchange_type = 'fanout'仍然会出错，后来运行cmd->service.msc->找到rabbitmq关闭后再启动就OK了，
                                                         #至于为啥，如果你找到了，跟我说一声，先谢谢啦
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    #得到队列的名字
channel.queue_bind(exchange='logs',
                   queue=queue_name)  #将交换机和队列的名字绑定，也就是说exchange = ‘logs'的交换机只能公国queue = queue_name来发送消息
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()

4、rabbitmq有选择的接受消息，模型如下

更过相关内容详见：http://www.cnblogs.com/alex3714/articles/5248247.html

5、client发送给指令，server根据指令运行完毕后再将结果返回给client

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,   #类中定义的方法__init__()是为了建立链接，同时定义一个callback_queue,再basic_publish中传递给server端，用于存放运行的结果
                                   no_ack=True,
                                   queue=self.callback_queue)     #这里的basic_consume只是声明，如果要取消息应该取callback__queue中取
    def on_response(self, ch, method, props, body):
        if self.corr_id == props.correlation_id:    #确定发的指令和收到的结果是相互对应的
            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() #去队列中取数据，不停的循环，非阻塞版的start_consuming(),去调用basic_consume()
        return int(self.response)

fibonacci_rpc = FibonacciRpcClient()
print(" [x] Requesting fib(30)")
response = fibonacci_rpc.call()
print(" [.] Got %r" % response)

import pika
import time

connection = pika.BlockingConnection(pika.ConnectionParameters(
    host='localhost'))
channel = connection.channel()
channel.queue_declare(queue='rpc_queue')

def fib(n):
    if n == :
        return
    elif n == :
        return
    else:
        return fib(n - ) + fib(n - )
def on_request(ch, method, props, body):  #method存放的是bsic_consume中读取数据routing_key,props中存放的是从basic_consume中读取的protperties的数据，body存放的是从发送过来的消息。
    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=)
channel.basic_consume(on_request, queue='rpc_queue')

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