Reference: https://www.rabbitmq.com/tutorials/tutorial-three-python.html

"Hello World!"

The simplest thing that doessomething

Work queues

Distributing tasks among workers (the competing consumers pattern)

Publish/Subscribe

Sending messages to many consumers at once

Routing

Receiving messages selectively

Topics

Receiving messages based on a pattern (topics)

RPC

Request/reply ("RPC") patternexample

Publish/Subscribe

(using the pika 0.10.0 Python client)

Prerequisites

This tutorial assumes RabbitMQ is installedand running on localhost on standard port (5672). In case you use a different host, port or credentials, connections settings would require adjusting.

Where to get help

If you're having trouble going through this tutorial you can contact us through the mailing list.

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.

Exchanges

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:

  • producer is a user application that sends messages.
  • queue is a buffer that stores messages.
  • consumer is a user application that receives messages.

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.

Listing exchanges

To list the exchanges on the server you can run the ever useful rabbitmqctl:

$ sudo rabbitmqctl list_exchanges
Listing exchanges ...
logs fanout
amq.direct direct
amq.topic topic
amq.fanout fanout
amq.headers headers
...done.

In this list there are some amq.* exchanges and the default (unnamed) exchange. These are created by default, but it is unlikely you'll need to use them at the moment.

Nameless exchange

In previous parts of the tutorial we knew nothing about exchanges, but still were able to send messages to queues. That was possible because we were using a default exchange, which we identify by the empty string ("").

Recall how we published a message before:

channel.basic_publish(exchange='',
routing_key='hello',
body=message)

The exchange parameter is the name of the exchange. The empty string denotes the default or namelessexchange: messages are routed to the queue with the name specified by routing_key, if it exists.

Now, we can publish to our named exchange instead:

channel.basic_publish(exchange='logs',
routing_key='',
body=message)

Temporary queues

As you may remember previously we were using queues which had a specified name (remember hello andtask_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:

result = channel.queue_declare()

At this point result.method.queue contains a random queue name. For example it may look likeamq.gen-JzTY20BRgKO-HjmUJj0wLg.

Secondly, once we disconnect the consumer the queue should be deleted. There's an exclusive flag for that:

result = channel.queue_declare(exclusive=True)

Bindings

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 a binding.

channel.queue_bind(exchange='logs',
queue=result.method.queue)

From now on the logs exchange will append messages to our queue.

Listing bindings

You can list existing bindings using, you guessed it, rabbitmqctl list_bindings.

Putting it all together

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
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
#!/usr/bin/env python
import pika
import sys connection = pika.BlockingConnection(pika.ConnectionParameters(
host='localhost'))
channel = connection.channel() 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()

(emit_log.py source)

As you see, after establishing the connection we declared the exchange. This step is necessary 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
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
#!/usr/bin/env python
import pika connection = pika.BlockingConnection(pika.ConnectionParameters(
host='localhost'))
channel = connection.channel() channel.exchange_declare(exchange='logs',
type='fanout') result = channel.queue_declare(exclusive=True)
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()

(receive_logs.py source)

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.

The interpretation of the result is straightforward: data from exchange logs goes to two queues with server-assigned names. And that's exactly what we intended.

To find out how to listen for a subset of messages, let's move on to tutorial 4

python rabittmq 使用的更多相关文章

  1. Python中的多进程与多线程(一)

    一.背景 最近在Azkaban的测试工作中,需要在测试环境下模拟线上的调度场景进行稳定性测试.故而重操python旧业,通过python编写脚本来构造类似线上的调度场景.在脚本编写过程中,碰到这样一个 ...

  2. Python高手之路【六】python基础之字符串格式化

    Python的字符串格式化有两种方式: 百分号方式.format方式 百分号的方式相对来说比较老,而format方式则是比较先进的方式,企图替换古老的方式,目前两者并存.[PEP-3101] This ...

  3. Python 小而美的函数

    python提供了一些有趣且实用的函数,如any all zip,这些函数能够大幅简化我们得代码,可以更优雅的处理可迭代的对象,同时使用的时候也得注意一些情况   any any(iterable) ...

  4. JavaScript之父Brendan Eich,Clojure 创建者Rich Hickey,Python创建者Van Rossum等编程大牛对程序员的职业建议

    软件开发是现时很火的职业.据美国劳动局发布的一项统计数据显示,从2014年至2024年,美国就业市场对开发人员的需求量将增长17%,而这个增长率比起所有职业的平均需求量高出了7%.很多人年轻人会选择编 ...

  5. 可爱的豆子——使用Beans思想让Python代码更易维护

    title: 可爱的豆子--使用Beans思想让Python代码更易维护 toc: false comments: true date: 2016-06-19 21:43:33 tags: [Pyth ...

  6. 使用Python保存屏幕截图(不使用PIL)

    起因 在极客学院讲授<使用Python编写远程控制程序>的课程中,涉及到查看被控制电脑屏幕截图的功能. 如果使用PIL,这个需求只需要三行代码: from PIL import Image ...

  7. Python编码记录

    字节流和字符串 当使用Python定义一个字符串时,实际会存储一个字节串: "abc"--[97][98][99] python2.x默认会把所有的字符串当做ASCII码来对待,但 ...

  8. Apache执行Python脚本

    由于经常需要到服务器上执行些命令,有些命令懒得敲,就准备写点脚本直接浏览器调用就好了,比如这样: 因为线上有现成的Apache,就直接放它里面了,当然访问安全要设置,我似乎别的随笔里写了安全问题,这里 ...

  9. python开发编译器

    引言 最近刚刚用python写完了一个解析protobuf文件的简单编译器,深感ply实现词法分析和语法分析的简洁方便.乘着余热未过,头脑清醒,记下一点总结和心得,方便各位pythoner参考使用. ...

随机推荐

  1. Xcode command line tools

    1.Xcode command line tools 安装 如果你不是一名 iOS 或 OS X 开发者,可以跳过安装 XCode 的过程,直接安装 Xcode command line tools. ...

  2. Tensorflow运行程序报错 FailedPreconditionError

    1 FailedPreconditionError错误现象 在运行tensorflow时出现报错,报错语句如下: FailedPreconditionError (see above for trac ...

  3. 设计模式之策略模式&amp;简单工厂模式

    学习设计模式已经有非常长一段时间了,事实上先前已经敲过一遍了.可是老认为没有学到什么,认识也不够深刻.如今趁着重构机房,再又一次来过,也不晚. 事实上在敲了机房之后,看看模式,事实上,曾经非常难理解. ...

  4. Cadence 5141 下TSMC 05U工艺库安装

    以下资料摘自:<T13RF PDK簡介>-張文旭 观念与TSMC工艺库的安装 管理者安裝TSMC 0.13 MS/RF的環境下之PDK的安裝方式相當容易,首先以root的方式進入Unix/ ...

  5. 常用代码之三:jQuery为按钮绑定事件的代码

    如题,比如有一个按钮:<input type='button' class='btn-text' id ='addHtml' value='新增' /> 为它添加onclick事件的代码: ...

  6. 使用C#和Thrift来访问Hbase实例

    今天试着用C#和Thrift来访问Hbase,主要参考了博客园上的这篇文章.查了Thrift,Hbase的资料,结合博客园的这篇文章,终于搞好了.期间经历了不少弯路,下面我尽量详细的记录下来,免得大家 ...

  7. Entity Framework 同一个上下文中,如何进行对同一个实体进行指定字段更新

    转自 http://www.cnblogs.com/flyfish2012/archive/2013/03/13/2957125.html 我在上一篇EF更新指定的字段当中介绍了,如何在EF指定字段进 ...

  8. RDD转换DataFrame

    Spark SQL有两种方法将RDD转为DataFrame. 1. 使用反射机制,推导包含指定类型对象RDD的schema.这种基于反射机制的方法使代码更简洁,而且如果你事先知道数据schema,推荐 ...

  9. [Contiki系列论文之2]WSN的自适应通信架构

    说明:本系列文章翻译自Contiki之父Adam Dunkels经典论文,版权归原作者全部. Contiki是由Adam Dunkels及其团队开发的系统.研读其论文是对深入理解Contiki系统的最 ...

  10. 解决&quot;VC6.0的ClassView里不能显示类或成员变量&quot;问题

    VC6.0是微软1998年公布的,是一款非常经典的编辑器.然而它有几个非经常见的bug,比方, .cpp文件打不开,智能提示出现异常.这里介绍"VC6.0的ClassView里不能显示类或成 ...