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In the previous tutorial we created a work queue. The assumption behind a work queue is that each task is delivered to exactly one worker. In this part we‘ll do something completely different -- we‘ll deliver a message to multiple consumers. This pattern is known as "publish/subscribe".
To illustrate the pattern, we‘re going to build a simple logging system. It will consist of two programs -- the first will emit log messages and the second will receive and print them.
In our logging system every running copy of the receiver program will get the messages. That way we‘ll be able to run one receiver and direct the logs to disk; and at the same time we‘ll be able to run another receiver and see the logs on the screen.
Essentially, published log messages are going to be broadcast to all the receivers.
In previous parts of the tutorial we sent and received messages to and from a queue. Now it‘s time to introduce the full messaging model in Rabbit.
Let‘s quickly go over what we covered in the previous tutorials:
The core idea in the messaging model in RabbitMQ is that the producer never sends any messages directly to a queue. Actually, quite often the producer doesn‘t even know if a message will be delivered to any queue at all.
Instead, the producer can only send messages to an exchange. An exchange is a very simple thing. On one side it receives messages from producers and the other side it pushes them to queues. The exchange must know exactly what to do with a message it receives. Should it be appended to a particular queue? Should it be appended to many queues? Or should it get discarded. The rules for that are defined by the exchange type.
There are a few exchange types available: direct, topic, headers and fanout. We‘ll focus on the last one -- the fanout. Let‘s create an exchange of that type, and call it logs:
channel.exchange_declare(exchange=‘logs‘,
type=‘fanout‘)
The fanout exchange is very simple. As you can probably guess from the name, it just broadcasts all the messages it receives to all the queues it knows. And that‘s exactly what we need for our logger.
Now, we can publish to our named exchange instead:
1 channel.basic_publish(exchange=‘logs‘, 2 routing_key=‘‘, 3 body=message)
As you may remember previously we were using queues which had a specified name (remember hello and task_queue?). Being able to name a queue was crucial for us -- we needed to point the workers to the same queue. Giving a queue a name is important when you want to share the queue between producers and consumers.
But that‘s not the case for our logger. We want to hear about all log messages, not just a subset of them. We‘re also interested only in currently flowing messages not in the old ones. To solve that we need two things.
Firstly, whenever we connect to Rabbit we need a fresh, empty queue. To do it we could create a queue with a random name, or, even better - let the server choose a random queue name for us. We can do this by not supplying the queue parameter to queue_declare:
1 result = channel.queue_declare()
At this point result.method.queue contains a random queue name. For example it may look like amq.gen-JzTY20BRgKO-HjmUJj0wLg.
Secondly, once we disconnect the consumer the queue should be deleted. There‘s an exclusive flag for that:
1 result = channel.queue_declare(exclusive=True)
We‘ve already created a fanout exchange and a queue. Now we need to tell the exchange to send messages to our queue. That relationship between exchange and a queue is called abinding.
1 channel.queue_bind(exchange=‘logs‘, 2 queue=result.method.queue)
From now on the logs exchange will append messages to our queue.
The producer program, which emits log messages, doesn‘t look much different from the previous tutorial. The most important change is that we now want to publish messages to our logs exchange instead of the nameless one. We need to supply a routing_key when sending, but its value is ignored for fanout exchanges. Here goes the code for emit_log.py script:
1 #!/usr/bin/env python 2 import pika 3 import sys 4 5 connection = pika.BlockingConnection(pika.ConnectionParameters( 6 host=‘localhost‘)) 7 channel = connection.channel() 8 9 channel.exchange_declare(exchange=‘logs‘, 10 type=‘fanout‘) 11 12 message = ‘ ‘.join(sys.argv[1:]) or "info: Hello World!" 13 channel.basic_publish(exchange=‘logs‘, 14 routing_key=‘‘, 15 body=message) 16 print " [x] Sent %r" % (message,) 17 connection.close()
As you see, after establishing the connection we declared the exchange. This step is neccesary as publishing to a non-existing exchange is forbidden.
The messages will be lost if no queue is bound to the exchange yet, but that‘s okay for us; if no consumer is listening yet we can safely discard the message.
The code for receive_logs.py:
1 #!/usr/bin/env python 2 import pika 3 4 connection = pika.BlockingConnection(pika.ConnectionParameters( 5 host=‘localhost‘)) 6 channel = connection.channel() 7 8 channel.exchange_declare(exchange=‘logs‘, 9 type=‘fanout‘) 10 11 result = channel.queue_declare(exclusive=True) 12 queue_name = result.method.queue 13 14 channel.queue_bind(exchange=‘logs‘, 15 queue=queue_name) 16 17 print ‘ [*] Waiting for logs. To exit press CTRL+C‘ 18 19 def callback(ch, method, properties, body): 20 print " [x] %r" % (body,) 21 22 channel.basic_consume(callback, 23 queue=queue_name, 24 no_ack=True) 25 26 channel.start_consuming()
We‘re done. If you want to save logs to a file, just open a console and type:
$ python receive_logs.py > logs_from_rabbit.log
If you wish to see the logs on your screen, spawn a new terminal and run:
$ python receive_logs.py
And of course, to emit logs type:
$ python emit_log.py
Using rabbitmqctl list_bindings you can verify that the code actually creates bindings and queues as we want. With two receive_logs.py programs running you should see something like:
$ sudo rabbitmqctl list_bindings
Listing bindings ...
logs exchange amq.gen-JzTY20BRgKO-HjmUJj0wLg queue []
logs exchange amq.gen-vso0PVvyiRIL2WoV3i48Yg queue []
...done.
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原文地址：http://www.cnblogs.com/lintong/p/4382451.html
