rabbitmq

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send端

import pikacredentials = pika.PlainCredentials('zhou', '')
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.0.1.14',credentials=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()

receive端

import pikaconnection = pika.BlockingConnection(pika.ConnectionParameters(
'localhost'))
channel = connection.channel()#You may ask why we declare the queue again ‒ we have already declared it in our previous code.
# We could avoid that if we were sure that the queue already exists. For example if send.py program
#was run before. But we're not yet sure which program to run first. In such cases it's a good
# practice to repeat declaring the queue in both programs.
channel.queue_declare(queue='hello')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()

消费一个消息可能会花好几秒。你可能会问，如果如果一个消费者启动了一个长的任务，消息发了一半然后死了。按我们现在的代码，一旦rabbitmq传递了一个消息到给消费者，然后rabbitmq就迅速的将这个消息从内存里删除。在这种情况下，如果你kill了一个消费者，我们就会失去了这个正在传递的消息。

但是我们不想失去这个消息。如果一个消费者死了，我想把这个任务传给另一个消费者。

为了确保一个消息从不丢失，rabbitmq支持消息确认。消费者处理完信息后会向rabbitmq发送一个消息确认，这样rabbitmq就可以从内存里删除这个消息了。

如果一个消费者死掉了，没有发ack，rabbitmq就会知道这个消息没有传递成功，就会把这个消息重新存到queue里。

如果此时有其它的消费者在线，rabbitmq就会迅速的将这个消息传递给其它的的消费者。这样就确保了消息没有丢失，即使这个消费者是偶尔挂了。

根本就没有超时时间一说，当那个消费者挂了，rabbitmq会重新转发那条消息。即使这个消息处理了很长时间都没关系。

rabbitmq消息确认默认是开启的(no_ack=Fault)。在之前的例子里我们显然用的no_ack=True。

队列及消息持久化

生产者

import pikacredentials = pika.PlainCredentials('zhou', '')
# connection = pika.BlockingConnection(pika.ConnectionParameters(host=url_1,
# credentials=credentials, ssl=ssl, port=port))
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.0.1.14',credentials=credentials))channel = connection.channel()# 声明queue,durable=True（队列持久化）
channel.queue_declare(queue='alex3',durable=True)# 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='alex3', #send msg to this queue
body='Hello World!23',
properties=pika.BasicProperties(
delivery_mode=2, # 消息持久化
)
)print(" [x] Sent 'Hello World!2'")
connection.close()

消费者

import pika
import time
credentials = pika.PlainCredentials('zhou', '')
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.0.1.14',credentials=credentials))channel = connection.channel()
# You may ask why we declare the queue again ‒ we have already declared it in our previous code.
# We could avoid that if we were sure that the queue already exists. For example if send.py program
# was run before. But we're not yet sure which program to run first. In such cases it's a good
# practice to repeat declaring the queue in both programs.channel.queue_declare(queue='alex3',durable=True)#队列持久化def callback(ch, method, properties, body):
print(ch, method, properties) print(" [x] Received %r" % body)
time.sleep(1)channel.basic_consume(callback,
queue='alex3',
no_ack=True
)
channel.basic_qos(prefetch_count=1)
print(' [*] Waiting for messages. To exit press CTRL+C')
channel.start_consuming()

消息公平分发

如果Rabbit只管按顺序把消息发到各个消费者身上，不考虑消费者负载的话，很可能出现，一个机器配置不高的消费者那里堆积了很多消息处理不完，同时配置高的消费者却一直很轻松。为解决此问题，可以在各个消费者端，配置perfetch=1,意思就是告诉RabbitMQ在我这个消费者当前消息还没处理完的时候就不要再给我发新消息了。

channel.basic_qos(prefetch_count=1)

生产者

import pika,syscredentials = pika.PlainCredentials('zhou', '')
# connection = pika.BlockingConnection(pika.ConnectionParameters(host=url_1,
# credentials=credentials, ssl=ssl, port=port))
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.0.1.14',credentials=credentials))channel = connection.channel()channel.queue_declare(queue='task_queue', durable=True)message = ' '.join(sys.argv[1:]) or "Hello World!"
channel.basic_publish(exchange='',
routing_key='task_queue',
body=message,
properties=pika.BasicProperties(
delivery_mode = 2, # make message persistent
))
print(" [x] Sent %r" % message)
connection.close()

消费者

import pika,time
credentials = pika.PlainCredentials('zhou', '')
# connection = pika.BlockingConnection(pika.ConnectionParameters(host=url_1,
# credentials=credentials, ssl=ssl, port=port))
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.0.1.14',credentials=credentials))
channel = connection.channel()
channel.queue_declare(queue='task_queue', durable=True)
print(' [*] Waiting for messages. To exit press CTRL+C')def callback(ch, method, properties, body):
print(" [x] Received %r" % body)
time.sleep(body.count(b'.'))
print(" [x] Done")
ch.basic_ack(delivery_tag = method.delivery_tag)channel.basic_qos(prefetch_count=1)
channel.basic_consume(callback,
queue='task_queue')channel.start_consuming()

rabbitmq消息发布\订阅(Publish\Subscribe)

当要采用广播发消息的时候就要用到exchange了。

exchange是一个很简单的东西，一端从生产者里接收消息，另一端把消息推送到队列里。exchange必须清除的知道它从生产者里接收的消息要发送给谁。接收到的消息是应该被追加到指定的queue里？还是应该追加到很多个queue里？或者是扔掉？这个规则都是根据exchange的类型来定义的。

exchange的类型：

fanout: 所有bind到此exchange的queue都可以接收消息
direct: 通过routingKey和exchange决定的那个唯一的queue可以接收消息
topic:所有符合routingKey(此时可以是一个表达式)的routingKey所bind的queue可以接收消息

表达式符号说明：#代表一个或多个字符，*代表任何字符
例：#.a会匹配a.a，aa.a，aaa.a等
*.a会匹配a.a，b.a，c.a等
注：使用RoutingKey为#，Exchange Type为topic的时候相当于使用fanout

headers: 通过headers 来决定把消息发给哪些queue

fanout实例

send端

recv端

import pikacredentials = pika.PlainCredentials('zhou', '')
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.0.1.14',credentials=credentials))channel = connection.channel()channel.exchange_declare(exchange='logs',type='fanout')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.queuechannel.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,
)
channel.start_consuming()

direct实例

send端

recv端

import pika
import syscredentials = pika.PlainCredentials('zhou', '')
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.0.1.14',credentials=credentials))
channel = connection.channel()channel.exchange_declare(exchange='direct_logs',type='direct')
result = channel.queue_declare(exclusive=True)
queue_name = result.method.queueseverities = 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: #[error info warning]
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,)
channel.start_consuming()

topic实例

send端

recv端

import pika
import syscredentials = pika.PlainCredentials('zhou', '')
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.0.1.14',credentials=credentials))channel = connection.channel()
channel.exchange_declare(exchange='topic_logs',type='topic')result = channel.queue_declare(exclusive=True)
queue_name = result.method.queuebinding_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)channel.start_consuming()