python的学习第十一天 rabbit redis

qq70191

rabbit
　　一个简单的实例

send端，生产端



#!/usr/bin/env python
# -*- coding:utf-8 -*-
__author__ = "tao"
import pika,time
# connection = pika.BaseConnection(pika.ConnectionParameters('192.168.142.129'))  #本地连接
credentials = pika.PlainCredentials('admin', 'admin')   #用户名和密码
# 这里可以连接远程IP，请记得打开远程端口
parameters = pika.ConnectionParameters('192.168.142.129', 5672, '/', credentials)
connection = pika.BlockingConnection(parameters)
channel = connection.channel()   #声明一个管道
# 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', #queue的名字
body='你好 美女！')  #消息内容
print(" [x] Sent '你好世界!'")
connection.close()   #直接关闭队列
receive端 消费端



#!/usr/bin/env python
# -*- coding:utf-8 -*-
__author__ = "tao"
import pika
# connection = pika.BaseConnection(pika.ConnectionParameters('192.168.142.129'))  #本地连接
credentials = pika.PlainCredentials('admin', 'admin')   #用户名和密码
# 这里可以连接远程IP，请记得打开远程端口
parameters = pika.ConnectionParameters('192.168.142.129', 5672, '/', credentials)
connection = pika.BlockingConnection(parameters)
channel = connection.channel()   #声明一个管道
#原因再次声明的：
#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):
#处理消息的方法
print(ch,method,properties)
print(" [x] Received %r" % body)

channel.basic_consume(callback,   #消费消息
queue='hello',
no_ack=True)
print('

Waiting for messages. To exit press CTRL+C')
channel.start_consuming()
工作模式
　　默认轮询，有确认机制，no_ack=Fals 打开True信息就会丢失,在这种模式下，RabbitMQ会默认把p发的消息公平的依次分发给各个消费者(c),跟负载均衡差不多

　　测试可以在callback方法里面定义sleep时间进行宕机丢失的测试



def callback(ch,method,properties,body):
print("->>",ch,method,properties)
time.sleep(10)              # 模拟处理时间，这样就可以宕机消息丢失的测试了
print("Received %r"%body)
ch.basic_ack(delivery_tag=method.delivery_tag)   #手动确认后才不丢失，确认
　　如果rabbit服务挂掉就管道都丢了要持久化



channel.queue_declare(queue='hello', durable=True) #声明queue的时候就声明持久化，队列持久了，消息还没持久化


channel.basic_publish(exchange='',
routing_key="task_queue",
body=message,
properties=pika.BasicProperties(
delivery_mode = 2, #  这样就把消息也持久化了
))
　　在rabbit服务器上直接运行 rabbitmqctl list_queues 可以查看队列和消息的信息
　　消息的公平分发
　　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。

　　生产者：



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

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



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

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

Publish\Subscribe(消息发布\订阅)
　　Exchange在定义的时候是有类型的，以决定到底是哪些Queue符合条件，可以接收消息
　　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

　　http://www.rabbitmq.com/tutorials/tutorial-three-python.html  官网的介绍
　　广播是实时的和收音机的广播一样



#!/usr/bin/env python
# -*- coding:utf-8 -*-
__author__ = "tao"
import pika
credentials = pika.PlainCredentials('admin', 'admin')
# 这里可以连接远程IP，请记得打开远程端口
parameters = pika.ConnectionParameters('192.168.142.129', 5672, '/', credentials)
connection = pika.BlockingConnection(parameters)
channel = connection.channel()
channel.exchange_declare(exchange='logs',type='fanout')
result = channel.queue_declare(exclusive=True)  #自动生成随机queue
queue_name = result.method.queue
print('random queuename',queue_name)
channel.queue_bind(exchange='logs',queue=queue_name)
print("发送完成")
connection.close()


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='',    #必须有个空
body=message)
print(" [x] Sent %r" % message)
connection.close()
　　routing模式：

　　RabbitMQ还支持根据关键字发送，即：队列绑定关键字，发送者将数据根据关键字发送到消息exchange，exchange根据 关键字 判定应该将数据发送至指定队列。
　　生产者：



import pika
import sys

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

channel.exchange_declare(exchange='direct_logs',
type='direct')

severity = sys.argv[1] if len(sys.argv) > 1 else 'info'
message = ' '.join(sys.argv[2:]) or 'Hello World!'
channel.basic_publish(exchange='direct_logs',
routing_key=severity,
body=message)
print(" [x] Sent %r:%r" % (severity, message))
connection.close()
　　消费者：



import pika
import sys

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

channel.exchange_declare(exchange='direct_logs',
type='direct')

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

severities = 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:
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,
no_ack=True)

channel.start_consuming()
Topic exchange

　　更细致的消息过滤，关键字等
　　生产者：



import pika
import sys

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

channel.exchange_declare(exchange='topic_logs',
type='topic')

routing_key = sys.argv[1] if len(sys.argv) > 1 else 'anonymous.info'
message = ' '.join(sys.argv[2:]) or 'Hello World!'
channel.basic_publish(exchange='topic_logs',
routing_key=routing_key,
body=message)
print(" [x] Sent %r:%r" % (routing_key, message))
connection.close()
　　消费者：



import pika
import sys

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

channel.exchange_declare(exchange='topic_logs',
type='topic')

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

binding_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,
no_ack=True)

channel.start_consuming()
Remote procedure call (RPC)

　　server端：



#_*_coding:utf-8_*_
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 == 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()
　　客户端：



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)
Memcached & Redis使用
　　http://www.cnblogs.com/wupeiqi/articles/5132791.html