RbbitMQ（消息队列）
#简单模式
服务端
import pika
#连接
connection = pika.BlockingConnection(pika.ConnectionParameters( host='localhost'))
连接通道
channel = connection.channel()
声明队列
channel.queue_declare(queue='hello')
发送数据
channel.basic_publish(exchange='',
routing_key='hello',
body='Hello World!')
print(" [x] Sent 'Hello World!'")
结束连接
connection.close()
# ########################## 客户端 ##########################
#获得连接对象
connection = pika.BlockingConnection(pika.ConnectionParameters(host='localhost'))
获得连接通道
channel = connection.channel()
#声明队列
channel.queue_declare(queue='hello')
回调函数
def callback(ch, method, properties, body):
print(" [x] Received %r" % body)
#从通道取出数据执行回调函数
channel.basic_consume( callback,
queue='hello', #队列名
no_ack=True)
print(' [*] Waiting for messages. To exit press CTRL+C')
在通道等待数据传递过来
channel.start_consuming()
#############################防止掉线客户端########################################
#no-ack ＝ False，如果消费者遇到情况挂掉了，那么，RabbitMQ会重新将该任务添加到队列中。
回调函数中的ch.basic_ack(delivery_tag=method.delivery_tag)
basic_comsume中的no_ack=False
import pika
#连接
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='10.211.55.4'))
连接通道
channel = connection.channel()
声明队列
channel.queue_declare(queue='hello')
def callback(ch, method, properties, body):
print(" [x] Received %r" % body)
import time
time.sleep(10)
print 'ok'
#执行这行代码之后，才把数据销毁
ch.basic_ack(delivery_tag = method.delivery_tag)
获得管道数据执行回调函数
channel.basic_consume(callback,
queue='hello',
no_ack=False)
print(' [*] Waiting for messages. To exit press CTRL+C')
等待
channel.start_consuming()
#########################durable ：消息不丢失（服务端）########################################3
import pika
连接
connection = pika.BlockingConnection(pika.ConnectionParameters(host='10.211.55.4'))
连接通道
channel = connection.channel()
声明队列
channel.queue_declare(queue='hello', durable=True)
push数据
channel.basic_publish(exchange='', #交换
routing_key='hello',
body='Hello World!',
基础属性
properties=pika.BasicProperties(
delivery_mode=2, # make message persistent
#让消息持久发送
))
print(" [x] Sent 'Hello World!'")
connection.close()
##################################消息不丢失（客户端）#############################################）#############################################
import pika
连接
connection = pika.BlockingConnection(pika.ConnectionParameters(host='10.211.55.4'))
通道
channel = connection.channel()
生成队列
channel.queue_declare(queue='hello', durable=True)
def callback(ch, method, properties, body):
print(" [x] Received %r" % body)
import time
time.sleep(10)
print 'ok'
#确认
ch.basic_ack(delivery_tag = method.delivery_tag)
基础消耗方法，执行回调
channel.basic_consume(callback,
queue='hello',
no_ack=False)
print(' [*] Waiting for messages. To exit press CTRL+C')
开始消耗
channel.start_consuming()
##################################
(3) 消息获取顺序
默认消息队列里的数据是按照顺序被消费者拿走，例如：消费者1 去队列中获取 奇数 序列的任务，消费者1去队列中获取 偶数 序列的任务。
channel.basic_qos(prefetch_count=1) 表示谁来谁取，不再按照奇偶数排列
################################客户端##################################
import pika
connection = pika.BlockingConnection(pika.ConnectionParameters(host='10.211.55.4'))
channel = connection.channel()
# make message persistent
channel.queue_declare(queue='hello')
def callback(ch, method, properties, body):
print(" [x] Received %r" % body)
import time
time.sleep(10)
print 'ok'
#确认，
ch.basic_ack(delivery_tag = method.delivery_tag)
#谁来谁取
channel.basic_qos(prefetch_count=1)
channel.basic_consume(callback,
queue='hello',
no_ack=False)
print(' [*] Waiting for messages. To exit press CTRL+C')
channel.start_consuming()
#############exchange模型#############
exchange type = fanout #交换类型
#############服务端########################
import pika
import sys
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='localhost'))
channel = connection.channel()
声明交流
channel.exchange_declare(exchange='logs',
type='fanout')
message = ' '.join(sys.argv[1:]) or "info: Hello World!"
push数据
channel.basic_publish(exchange='logs', #交流name
routing_key='',
body=message)
print(" [x] Sent %r" % message)
connection.close()
########################客户端##################################################
# 消费者
#!/usr/bin/env python
import pika
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='localhost'))
channel = connection.channel()
声明交流
channel.exchange_declare(exchange='logs',
type='fanout') #订阅
声明队列
result = channel.queue_declare(exclusive=True)
#队列名
queue_name = result.method.queue
与队列捆绑
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)
基本消耗
channel.basic_consume(callback,
queue=queue_name,
no_ack=True) #保护数据
#消耗通道
channel.start_consuming()
#######################关键字发送#################################
exchange type = direct
之前事例，发送消息时明确指定某个队列并向其中发送消息，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。
###########################客户端########################################
import pika
import sys
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='localhost'))
连接通道
channel = connection.channel()
声明交流
channel.exchange_declare(exchange='direct_logs',
type='direct') #直接
声明队列
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) 就是这个
print(' [*] Waiting for logs. To exit press CTRL+C')
def callback(ch, method, properties, body):
print(" [x] %r:%r" % (method.routing_key, body))
消耗，获取队列信息回调
channel.basic_consume(callback,
queue=queue_name,
no_ack=True)
开始消耗
channel.start_consuming()
#############################
在 topic 类型下，可以让队列绑定几个模糊的关键字，之后发送者将数据发送到exchange，exchange将传入”路由值“和 ”关键字“进行匹配，匹配成功，则将数据发送到指定队列。
# 表示可以匹配 0 个 或 多个 单词
* 表示只能匹配 一个 单词
##############################模糊查找############################################
import pika
import sys
连接
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='localhost'))
管道
channel = connection.channel()
交流
channel.exchange_declare(exchange='topic_logs',
type='topic') 话题
声明队列
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:
与队列捆绑
channel.queue_bind(exchange='topic_logs',
queue=queue_name,
routing_key=binding_key) #查找#
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()
################################ 基于RabbitMQ的RPC###############
一个客户端向服务器发送请求，服务器端处理请求后，将其处理结果保存在一个存储体中。而客户端为了获得处理结果，那么客户在向服务器发送请求时，同时发送一个回调队列地址reply_to。
###################################服务器####
# 建立连接，服务器地址为localhost，可指定ip地址
connection = pika.BlockingConnection(pika.ConnectionParameters(
host='localhost'))
# 建立会话
channel = connection.channel()
# 声明RPC请求队列
channel.queue_declare(queue='rpc_queue')
# 数据处理方法
def fib(n):
if n == 0:
return 0
elif n == 1:
return 1
else:
return fib(n-1) + fib(n-2)
# 对RPC请求队列中的请求进行处理
def on_request(ch, method, props, body):
n = int(body)
print(" [.] fib(%s)" % n)
# 调用数据处理方法
response = fib(n)
# 将处理结果(响应)发送到回调队列
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)
# 负载均衡，同一时刻发送给该服务器的请求不超过一个
channel.basic_qos(prefetch_count=1)
channel.basic_consume(on_request, queue='rpc_queue')
print(" [x] Awaiting RPC requests")
channel.start_consuming()
##################################################################
import pika
import uuid
class FibonacciRpcClient(object):
def __init__(self):
”“”
客户端启动时，创建回调队列，会开启会话用于发送RPC请求以及接受响应
“”“
# 建立连接，指定服务器的ip地址
self.connection = pika.BlockingConnection(pika.ConnectionParameters(
host='localhost'))
# 建立一个会话，每个channel代表一个会话任务
self.channel = self.connection.channel()
# 声明回调队列，再次声明的原因是，服务器和客户端可能先后开启，该声明是幂等的，多次声明，但只生效一次
result = self.channel.queue_declare(exclusive=True)
# 将次队列指定为当前客户端的回调队列
self.callback_queue = result.method.queue
# 客户端订阅回调队列，当回调队列中有响应时，调用`on_response`方法对响应进行处理;
self.channel.basic_consume(self.on_response, no_ack=True,
queue=self.callback_queue)
# 对回调队列中的响应进行处理的函数
def on_response(self, ch, method, props, body):
if self.corr_id == props.correlation_id:
self.response = body
# 发出RPC请求
def call(self, n):
# 初始化 response
self.response = None
#生成correlation_id
self.corr_id = str(uuid.uuid4())
# 发送RPC请求内容到RPC请求队列`rpc_queue`，同时发送的还有`reply_to`和`correlation_id`
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)
# 建立客户端
fibonacci_rpc = FibonacciRpcClient()
# 发送RPC请求
print(" [x] Requesting fib(30)")
response = fibonacci_rpc.call(30)
print(" [.] Got %r" % response)
