对于RabbitMQ来说，生产和消费不再针对内存里的一个Queue对象，而是某台服务器上的RabbitMQ Server实现的消息队列。

#!/usr/bin/env python

import pika

# ######################### 生产者 #########################

connection = pika.BlockingConnection(pika.ConnectionParameters(

        host='localhost'))

channel = connection.channel()

channel.queue_declare(queue='hello')

channel.basic_publish(exchange='',

                      routing_key='hello',

                      body='Hello World!')

print(" [x] Sent 'Hello World!'")

connection.close()

#!/usr/bin/env python

import pika

# ########################## 消费者 ##########################

connection = pika.BlockingConnection(pika.ConnectionParameters(

        host='localhost'))

channel = connection.channel()

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()

1、acknowledgment 消息不丢失

no-ack ＝ False，如果生产者遇到情况(its channel is closed, connection is closed, or TCP connection is lost)挂掉了，那么，RabbitMQ会重新将该任务添加到队列中。

import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(

        host='10.211.55.4'))

channel = connection.channel()

channel.queue_declare(queue='hello')

def callback(ch, method, properties, body):

    print(" [x] Received %r" % body)

    import time

    time.sleep(10)

    print 'ok'

    ch.basic_ack(delivery_tag = method.delivery_tag)

channel.basic_consume(callback,

                      queue='hello',

                      no_ack=False)

print(' [*] Waiting for messages. To exit press CTRL+C')

channel.start_consuming()

2、durable   消息不丢失
生产者

#!/usr/bin/env python

import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(host='10.211.55.4'))

channel = connection.channel()

# make message persistent

channel.queue_declare(queue='hello', durable=True)

channel.basic_publish(exchange='',

                      routing_key='hello',

                      body='Hello World!',

                      properties=pika.BasicProperties(

                          delivery_mode=2, # make message persistent

                      ))

print(" [x] Sent 'Hello World!'")

connection.close()

消费者
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(host='10.211.55.4'))
channel = connection.channel()

# make message persistent
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'
    ch.basic_ack(delivery_tag = method.delivery_tag)

channel.basic_consume(callback,
                      queue='hello',
                      no_ack=False)

print(' [*] Waiting for messages. To exit press CTRL+C')
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

消费者

#!/usr/bin/env python
# -*- coding:utf-8 -*-
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'
    ch.basic_ack(delivery_tag = method.delivery_tag)

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()

4、发布订阅

发布订阅和简单的消息队列区别在于，发布订阅会将消息发送给所有的订阅者，而消息队列中的数据被消费一次便消失。所以，RabbitMQ实现发布和订阅时，会为每一个订阅者创建一个队列，而发布者发布消息时，会将消息放置在所有相关队列中。

exchange type = fanout

发布者

#!/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()

订阅者
#!/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()

5、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。

消费者

#!/usr/bin/env python
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()

生产者
#!/usr/bin/env python
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()

6、模糊匹配

exchange type = topic

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

生产者

#!/usr/bin/env python
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()

• MySQL-Python
•     mysql+mysqldb://<user>:<password>@<host>[:<port>]/<dbname>

• pymysql
•     mysql+pymysql://<username>:<password>@<host>/<dbname>[?<options>]

• MySQL-Connector
•     mysql+mysqlconnector://<user>:<password>@<host>[:<port>]/<dbname>

• cx_Oracle
•     oracle+cx_oracle://user:pass@host:port/dbname[?key=value&key=value...]

• 更多详见：http://docs.sqlalchemy.org/en/latest/dialects/index.html

#!/usr/bin/env python

# -*- coding:utf-8 -*-

from sqlalchemy.ext.declarative import declarative_base

from sqlalchemy import Column, Integer, String

from sqlalchemy.orm import sessionmaker

from sqlalchemy import create_engine

engine = create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)

Base = declarative_base()

class User(Base):

    __tablename__ = 'users'

    id = Column(Integer, primary_key=True)

    name = Column(String(50))

# 寻找Base的所有子类，按照子类的结构在数据库中生成对应的数据表信息

# Base.metadata.create_all(engine)

Session = sessionmaker(bind=engine)

session = Session()

# ########## 增 ##########

# u = User(id=2, name='sb')

# session.add(u)

# session.add_all([

#     User(id=3, name='sb'),

#     User(id=4, name='sb')

# ])

# session.commit()

# ########## 删除 ##########

# session.query(User).filter(User.id > 2).delete()

# session.commit()

# ########## 修改 ##########

# session.query(User).filter(User.id > 2).update({'cluster_id' : 0})

# session.commit()

# ########## 查 ##########

# ret = session.query(User).filter_by(name='sb').first()

# ret = session.query(User).filter_by(name='sb').all()

# print ret

# ret = session.query(User).filter(User.name.in_(['sb','bb'])).all()

# print ret

# ret = session.query(User.name.label('name_label')).all()

# print ret,type(ret)

# ret = session.query(User).order_by(User.id).all()

# print ret

# ret = session.query(User).order_by(User.id)[1:3]

# print ret

# session.commit()