Python学习路程day11

SqlAlchemy ORM　　

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：

 1 MySQL-Python
 2     mysql+mysqldb://<user>:<password>@<host>[:<port>]/<dbname>
 3   
 4 pymysql
 5     mysql+pymysql://<username>:<password>@<host>/<dbname>[?<options>]
 6   
 7 MySQL-Connector
 8     mysql+mysqlconnector://<user>:<password>@<host>[:<port>]/<dbname>
 9   
10 cx_Oracle
11     oracle+cx_oracle://user:pass@host:port/dbname[?key=value&key=value...]
12   
13 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。

 1 #!/usr/bin/env python
 2 # -*- coding:utf-8 -*-
 3   
 4 from sqlalchemy import create_engine
 5   
 6   
 7 engine = create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
 8   
 9 engine.execute(
10     "INSERT INTO ts_test (a, b) VALUES ('2', 'v1')"
11 )
12   
13 engine.execute(
14      "INSERT INTO ts_test (a, b) VALUES (%s, %s)",
15     ((555, "v1"),(666, "v1"),)
16 )
17 engine.execute(
18     "INSERT INTO ts_test (a, b) VALUES (%(id)s, %(name)s)",
19     id=999, name="v1"
20 )
21   
22 result = engine.execute('select * from ts_test')
23 result.fetchall()

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。

 1 #!/usr/bin/env python
 2 # -*- coding:utf-8 -*-
 3  
 4 from sqlalchemy import create_engine, Table, Column, Integer, String, MetaData, ForeignKey
 5  
 6 metadata = MetaData()
 7  
 8 user = Table('user', metadata,
 9     Column('id', Integer, primary_key=True),
10     Column('name', String(20)),
11 )
12  
13 color = Table('color', metadata,
14     Column('id', Integer, primary_key=True),
15     Column('name', String(20)),
16 )
17 engine = create_engine("mysql+mysqldb://root@localhost:3306/test", max_overflow=5)
18  
19 metadata.create_all(engine)

View Code

增删改查

 1 #!/usr/bin/env python
 2 # -*- coding:utf-8 -*-
 3  
 4 from sqlalchemy import create_engine, Table, Column, Integer, String, MetaData, ForeignKey
 5  
 6 metadata = MetaData()
 7  
 8 user = Table('user', metadata,
 9     Column('id', Integer, primary_key=True),
10     Column('name', String(20)),
11 )
12  
13 color = Table('color', metadata,
14     Column('id', Integer, primary_key=True),
15     Column('name', String(20)),
16 )
17 engine = create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
18  
19 conn = engine.connect()
20  
21 # 创建SQL语句，INSERT INTO "user" (id, name) VALUES (:id, :name)
22 conn.execute(user.insert(),{'id':7,'name':'seven'})
23 conn.close()
24  
25 # sql = user.insert().values(id=123, name='wu')
26 # conn.execute(sql)
27 # conn.close()
28  
29 # sql = user.delete().where(user.c.id > 1)
30  
31 # sql = user.update().values(fullname=user.c.name)
32 # sql = user.update().where(user.c.name == 'jack').values(name='ed')
33  
34 # sql = select([user, ])
35 # sql = select([user.c.id, ])
36 # sql = select([user.c.name, color.c.name]).where(user.c.id==color.c.id)
37 # sql = select([user.c.name]).order_by(user.c.name)
38 # sql = select([user]).group_by(user.c.name)
39  
40 # result = conn.execute(sql)
41 # print result.fetchall()
42 # conn.close()

View Code

一个简单的完整例子

 1 #!/usr/bin/env python
 2 #-*- coding:utf-8 -*-
 3 
 4 from sqlalchemy import create_engine
 5 from sqlalchemy.ext.declarative import declarative_base
 6 from sqlalchemy import Column,Integer,String
 7 from sqlalchemy.orm import sessionmaker
 8 
 9 Base = declarative_base()       #生成一个SqlORM 基类
10 
11 engine = create_engine("mysql+mysqldb://root@localhost:3306/test",echo=False)
12 
13 class Host(Base):
14     __tablename__ = 'hosts'
15     id = Column(Integer,primary_key=True,autoincrement=True)
16     hostname = Column(String(64),unique=True,nullable=False)
17     ip_addr = Column(String(128),unique=True,nullable=False)
18     port = Column(Integer,default=22)
19 
20 Base.metadata.create_all(engine)    #创建所有表结构
21 
22 if __name__ == '__main__':
23     SessionCls = sessionmaker(bind=engine)      #创建与数据库的会话session class，注意，这里返回给session的是个class，不是实例
24     session = SessionCls()
25     #h1 = Host(hostname='localhost',ip_addr='127.0.0.1')
26     #h2 = Host(hostname='ubuntu',ip_addr='192.168.2.243',port=20000)
27     #h3 = Host(hostname='ubuntu2',ip_addr='192.168.2.244',port=20000)
28     #session.add(h3)
29     #session.add_all([h1,h2])
30     #h2.hostname = 'ubuntu_test'       #只要没提交，此时修改也没问题
31     #session.rollback()
32     #session.rollback()
33     #session.commit()     #提交
34     #update   #更新
35     #res = session.query(Host).filter(Host.hostname.in_(['ubuntu2','localhost'])).all()
36     #res = session.query(Host).filter(Host,hostname=='localhost').all()
37     #res.hostname = "test server"
38     #delete    删除
39     #session.delete(obj)
40     print(res)

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 -*-
  
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()

外键关联

A one to many relationship places a foreign key on the child table referencing the parent.relationship() is then specified on the parent, as referencing a collection of items represented by the child

from sqlalchemy import Table, Column, Integer, ForeignKey
from sqlalchemy.orm import relationship
from sqlalchemy.ext.declarative import declarative_base

Base = declarative_base()

<br>class Parent(Base):
    __tablename__ = 'parent'
    id = Column(Integer, primary_key=True)
    children = relationship("Child")
 
class Child(Base):
    __tablename__ = 'child'
    id = Column(Integer, primary_key=True)
    parent_id = Column(Integer, ForeignKey('parent.id'))

To establish a bidirectional relationship in one-to-many, where the “reverse” side is a many to one, specify an additional relationship() and connect the two using therelationship.back_populates parameter:

class Parent(Base):
    __tablename__ = 'parent'
    id = Column(Integer, primary_key=True)
    children = relationship("Child", back_populates="parent")
 
class Child(Base):
    __tablename__ = 'child'
    id = Column(Integer, primary_key=True)
    parent_id = Column(Integer, ForeignKey('parent.id'))
    parent = relationship("Parent", back_populates="children")

Child will get a parent attribute with many-to-one semantics.

Alternatively, the backref option may be used on a single relationship() instead of usingback_populates:

class Parent(Base):
    __tablename__ = 'parent'
    id = Column(Integer, primary_key=True)
    children = relationship("Child", backref="parent")

附，原生sql join查询

几个Join的区别 http://stackoverflow.com/questions/38549/difference-between-inner-and-outer-joins

INNER JOIN: Returns all rows when there is at least one match in BOTH tables
LEFT JOIN: Return all rows from the left table, and the matched rows from the right table
RIGHT JOIN: Return all rows from the right table, and the matched rows from the left table

select host.id,hostname,ip_addr,port,host_group.name from host right join host_group on host.id = host_group.host_id

in SQLAchemy

session.query(Host).join(Host.host_groups).filter(HostGroup.name=='t1').group_by("Host").all()

group by 查询

select name,count(host.id) as NumberOfHosts from host right join host_group on host.id= host_group.host_id group by name;

in SQLAchemy

from sqlalchemy import func
session.query(HostGroup, func.count(HostGroup.name )).group_by(HostGroup.name).all()
 
#another example
session.query(func.count(User.name), User.name).group_by(User.name).all() SELECT count(users.name) AS count_1, users.name AS users_name
FROM users GROUP BY users.name

更多具体内容：

https://files.cnblogs.com/files/wupeiqi/sqlalchemy.pdf.zip

发表于 2016-04-13 23:24 leo.ling 阅读(166) 评论(0) 编辑收藏举报

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