上下文管理、redis发布订阅、RabbitMQ发布订阅、SQLAlchemy

一、上下文管理

 

import  contextlib
@contextlib.contextmanager
def work_state(state_list,worker_thread):
    state_list.append(worker_thread)
    try:
        yield
    finally:
        state_list.remove(worker_thread)
free_list=[]
current_thread="alex"
with work_state(free_list,current_thread):
    print(123)
    print(456)

#以下为执行结果：
123
456

 

代码执行步骤

 

 

上下文用于需要 close()方法的模块

 

import  contextlib
import  socket

@contextlib.contextmanager
def context_socket(host,port):
    sk=socket.socket()
    sk.bind((host,port))
    sk.listen(5)
    try:
        yield sk
    finally:
        sk.close()
with context_socket('127.0.0.1',8888) as sock:
    print(sock)

#以下为执行结果:
<socket.socket fd=224, family=AddressFamily.AF_INET, type=SocketKind.SOCK_STREAM, proto=0, laddr=('127.0.0.1', 8888)>

 

 

 

二、redis 发布订阅

#redis2.py 主程序


import  redis
class RedisHelper:
    def __init__(self):
        self.__conn=redis.Redis(host='192.168.11.87')


    def public(self,msg,chan):
        self.__conn.publish(chan,msg)
        return  True
    def subscribe(self,chan):
        pub=self.__conn.pubsub()
        pub.subscribe(chan)
        pub.parse_response()
        return  pub

 

 

订阅

import redis2

obj= redis2.RedisHelper()
data=obj.subscribe('fm111.7')
print(data.parse_response())

#接收到发布信息:
[b'message', b'fm111.7', b'aaaaaa']

 

发布

import redis2

obj= redis2.RedisHelper()
obj.public('alex_db','f111.7')

 

 

三、RabbitMQ

import pika

#生产者 发布
connection =pika.BlockingConnection(pika.ConnectionParameters(host='192.168.11.87'))

channel = connection.channel()
channel.queue_declare(queue='hello_wuwenyu')                 #创建队列，存在则忽略

channel.basic_publish(exchange='', routing_key='hello_wuwenyu', body='Hello World') print("[x] Sent 'Hello World!'") connection.close

 

 

import pika

#消费者 订阅
connection = pika.BlockingConnection(pika.ConnectionParameters(host='192.168.11.87'))
channel = connection.channel()
channel.queue_declare(queue='hello_wuwenyu')  #
def callback(ch,method,properties,body):
    print(" [x] Received %r" % body)
channel.basic_consume(callback,
                      queue='hello_wuwenyu',
                      no_ack=True)
print(' [*] Waiting for messages. To exit press CTRL+C')
channel.start_consuming()

#接收到生产者发来的消息：
[*] Waiting for messages. To exit press CTRL+C
[x] Received b'Hello World'

 

　　2 exchange 绑定多个队列

#

import pika

#生产者 发布
import pika
import sys

connection = pika.BlockingConnection(pika.ConnectionParameters(
        host='192.168.11.87'))
channel = connection.channel()

channel.exchange_declare(exchange='logs_fanout',
                         type='fanout')

message = '456'
channel.basic_publish(exchange='logs_fanout',
                      routing_key='',
                      body=message)
print(" [x] Sent %r" % message)
connection.close()

 

import pika

#订阅
connection = pika.BlockingConnection(pika.ConnectionParameters(
        host='192.168.11.87'))
channel = connection.channel()

channel.exchange_declare(exchange='logs_fanout',
                         type='fanout')

# 随机创建队列
result = channel.queue_declare(exclusive=True)
queue_name = result.method.queue
# 绑定
channel.queue_bind(exchange='logs_fanout',
                   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()

#执行多次消费端，随机产生多个队列，每个队列都接收到消息：
[*] Waiting for logs. To exit press CTRL+C
 [x] b'456'

 

 关键字

#生产者  severity = 'info'      severity = 'errer'   执行两次
import pika
import sys

connection = pika.BlockingConnection(pika.ConnectionParameters(
        host='192.168.11.87'))
channel = connection.channel()

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

severity = 'info'     
# severity = 'errer'
message = '123'
channel.basic_publish(exchange='direct_logs_wuwenyu',
                      routing_key=severity,
                      body=message)
print(" [x] Sent %r:%r" % (severity, message))
connection.close()

 

 

#订阅 消费 客户端1
import pika
import sys

connection = pika.BlockingConnection(pika.ConnectionParameters(
        host='192.168.11.87'))
channel = connection.channel()

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

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

severities =  ['error','info','warning']

for severity in severities:
    channel.queue_bind(exchange='direct_logs_wuwenyu',
                       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()

#接受到的消息：
 [*] Waiting for logs. To exit press CTRL+C
 [x] 'error':b'123'
 [x] 'info':b'123'

 

 

#订阅 消费 客户端2
import pika
import sys

connection = pika.BlockingConnection(pika.ConnectionParameters(
        host='192.168.11.87'))
channel = connection.channel()

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

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

severities =  ['error',]

for severity in severities:
    channel.queue_bind(exchange='direct_logs_wuwenyu',
                       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()
#接受到的消息：
 [*] Waiting for logs. To exit press CTRL+C
 [x] 'info':b'123'

 

四、SQLAlchemy

SQLAlchemy是Python编程语言下的一款ORM框架，该框架建立在数据库API之上，使用关系对象映射进行数据库操作，简言之便是：将对象转换成SQL，然后使用数据API执行SQL并获取执行结果。

Dialect用于和数据API进行交流，根据配置文件的不同调用不同的数据库API，从而实现对数据库的操作，如：

MySQL-Python
mysql+mysqldb://:@[:]/
 
pymysql
mysql+pymysql://:@/[?]
 
MySQL-Connector
mysql+mysqlconnector://:@[:]/
 
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

 

步骤一：

使用 Engine/ConnectionPooling/Dialect 进行数据库操作，Engine使用ConnectionPooling连接数据库，然后再通过Dialect执行SQL语句。

#!/usr/bin/env python
# -*- coding:utf-8 -*-
 
fromsqlalchemy importcreate_engine
 
 
engine =create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
 
engine.execute(
"INSERT INTO ts_test (a, b) VALUES ('2', 'v1')"
)
 
engine.execute(
"INSERT INTO ts_test (a, b) VALUES (%s, %s)",
((555, "v1"),(666, "v1"),)
)
engine.execute(
"INSERT INTO ts_test (a, b) VALUES (%(id)s, %(name)s)",
id=999, name="v1"
)
 
result =engine.execute('select * from ts_test')
result.fetchall()

 

事务操作

注：查看数据库连接：show status like 'Threads%';

步骤二：

使用 Schema Type/SQL Expression Language/Engine/ConnectionPooling/Dialect 进行数据库操作。Engine使用Schema Type创建一个特定的结构对象，之后通过SQL Expression Language将该对象转换成SQL语句，然后通过 ConnectionPooling 连接数据库，再然后通过 Dialect 执行SQL，并获取结果。

#!/usr/bin/env python
# -*- coding:utf-8 -*-
 
fromsqlalchemy importcreate_engine, Table, Column, Integer, String, MetaData, ForeignKey
 
metadata =MetaData()
 
user =Table('user', metadata,
Column('id', Integer, primary_key=True),
Column('name', String(20)),
)
 
color =Table('color', metadata,
Column('id', Integer, primary_key=True),
Column('name', String(20)),
)
engine =create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
 
metadata.create_all(engine)
# metadata.clear()
# metadata.remove()

 

增删改查

更多内容详见：

    http://www.jianshu.com/p/e6bba189fcbd

    http://docs.sqlalchemy.org/en/latest/core/expression_api.html

注：SQLAlchemy无法修改表结构，如果需要可以使用SQLAlchemy开发者开源的另外一个软件Alembic来完成。

步骤三：

使用 ORM/Schema Type/SQL Expression Language/Engine/ConnectionPooling/Dialect 所有组件对数据进行操作。根据类创建对象，对象转换成SQL，执行SQL。

#!/usr/bin/env python
# -*- coding:utf-8 -*-
 
fromsqlalchemy.ext.declarative importdeclarative_base
fromsqlalchemy importColumn, Integer, String
fromsqlalchemy.orm importsessionmaker
fromsqlalchemy importcreate_engine
 
engine =create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
 
Base =declarative_base()
 
 
classUser(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()