码迷,mamicode.com
首页 > 数据库 > 详细

Python操作mysql之SQLAchemy(ORM框架)

时间:2016-08-11 15:39:27      阅读:1822      评论:0      收藏:0      [点我收藏+]

标签:

SQLAchemy

 

SQLAchemy

解析:

SQLAchemy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。

ORM框架的作用就是把数据库表的一行记录与一个对象互相做自动转换。 正确使用ORM的前提是了解关系数据库的原理。 ORM就是把数据库表的行与相应的对象建立关联,互相转换。 由于关系数据库的多个表还可以用外键实现一对多、多对多等关联,相应地, ORM框架也可以提供两个对象之间的一对多、多对多等功能。

安装:

pip3 install SQLALchemy

  

SQLAlchemy本身无法操作数据库,其必须以来pymsql等第三方插件,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://<user>:<password>@<host>[:<port>]/<dbname>
   

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

更多:

技术分享
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
View Code

 

 

一、内部处理

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。

技术分享
#!/usr/bin/env python
# -*- coding:utf-8 -*-
from sqlalchemy import create_engine
  
  
engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/t1", max_overflow=5)
  
# 执行SQL
# cur = engine.execute(
#     "INSERT INTO hosts (host, color_id) VALUES (‘1.1.1.22‘, 3)"
# )
  
# 新插入行自增ID
# cur.lastrowid
  
# 执行SQL
# cur = engine.execute(
#     "INSERT INTO hosts (host, color_id) VALUES(%s, %s)",[(1.1.1.22, 3),(1.1.1.221, 3),]
# )
  
  
# 执行SQL
# cur = engine.execute(
#     "INSERT INTO hosts (host, color_id) VALUES (%(host)s, %(color_id)s)",
#     host=1.1.1.99, color_id=3
# )
  
# 执行SQL
# cur = engine.execute(select * from hosts)
# 获取第一行数据
# cur.fetchone()
# 获取第n行数据
# cur.fetchmany(3)
# 获取所有数据
# cur.fetchall()
View Code

 

 

二、ORM功能使用

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。

1、创建表

技术分享
#!/usr/bin/env python
# -*- coding:utf-8 -*-
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index
from sqlalchemy.orm import sessionmaker, relationship
from sqlalchemy import create_engine
 
engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/t1", max_overflow=5)
 
Base = declarative_base()
 
# 创建单表
class Users(Base):
    __tablename__ = users
    id = Column(Integer, primary_key=True)
    name = Column(String(32))
    extra = Column(String(16))
 
    __table_args__ = (
    UniqueConstraint(id, name, name=uix_id_name),
        Index(ix_id_name, name, extra),
    )
 
 
# 一对多
class Favor(Base):
    __tablename__ = favor
    nid = Column(Integer, primary_key=True)
    caption = Column(String(50), default=red, unique=True)
 
 
class Person(Base):
    __tablename__ = person
    nid = Column(Integer, primary_key=True)
    name = Column(String(32), index=True, nullable=True)
    favor_id = Column(Integer, ForeignKey("favor.nid"))
 
 
# 多对多
class Group(Base):
    __tablename__ = group
    id = Column(Integer, primary_key=True)
    name = Column(String(64), unique=True, nullable=False)
    port = Column(Integer, default=22)
 
 
class Server(Base):
    __tablename__ = server
 
    id = Column(Integer, primary_key=True, autoincrement=True)
    hostname = Column(String(64), unique=True, nullable=False)
 
 
class ServerToGroup(Base):
    __tablename__ = servertogroup
    nid = Column(Integer, primary_key=True, autoincrement=True)
    server_id = Column(Integer, ForeignKey(server.id))
    group_id = Column(Integer, ForeignKey(group.id))
 
 
def init_db():
    Base.metadata.create_all(engine)
 
 
def drop_db():
    Base.metadata.drop_all(engine)
View Code

 

2、操作表

技术分享
#!/usr/bin/env python
# -*- coding:utf-8 -*-
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index
from sqlalchemy.orm import sessionmaker, relationship
from sqlalchemy import create_engine

engine = create_engine("mysql+pymysql://root:123@127.0.0.1:3306/t1", max_overflow=5)

Base = declarative_base()

# 创建单表
class Users(Base):
    __tablename__ = users
    id = Column(Integer, primary_key=True)
    name = Column(String(32))
    extra = Column(String(16))

    __table_args__ = (
    UniqueConstraint(id, name, name=uix_id_name),
        Index(ix_id_name, name, extra),
    )

    def __repr__(self):
        return "%s-%s" %(self.id, self.name)

# 一对多
class Favor(Base):
    __tablename__ = favor
    nid = Column(Integer, primary_key=True)
    caption = Column(String(50), default=red, unique=True)

    def __repr__(self):
        return "%s-%s" %(self.nid, self.caption)

class Person(Base):
    __tablename__ = person
    nid = Column(Integer, primary_key=True)
    name = Column(String(32), index=True, nullable=True)
    favor_id = Column(Integer, ForeignKey("favor.nid"))
    # 与生成表结构无关,仅用于查询方便
    favor = relationship("Favor", backref=pers)

# 多对多
class ServerToGroup(Base):
    __tablename__ = servertogroup
    nid = Column(Integer, primary_key=True, autoincrement=True)
    server_id = Column(Integer, ForeignKey(server.id))
    group_id = Column(Integer, ForeignKey(group.id))
    group = relationship("Group", backref=s2g)
    server = relationship("Server", backref=s2g)

class Group(Base):
    __tablename__ = group
    id = Column(Integer, primary_key=True)
    name = Column(String(64), unique=True, nullable=False)
    port = Column(Integer, default=22)
    # group = relationship(Group,secondary=ServerToGroup,backref=host_list)


class Server(Base):
    __tablename__ = server

    id = Column(Integer, primary_key=True, autoincrement=True)
    hostname = Column(String(64), unique=True, nullable=False)




def init_db():
    Base.metadata.create_all(engine)


def drop_db():
    Base.metadata.drop_all(engine)


Session = sessionmaker(bind=engine)
session = Session()

表结构 + 数据库连接
View Code

obj = Users(name=‘alex1‘, exeven=‘sd‘)
session.add(obj)
session.add_all([
    Users(name=‘alex2‘, exeven=‘sd‘),
    Users(name=‘alex3‘, exeven=‘sd‘),
])
session.commit()

session.query(users.id).filter(Users.id > 2).delete()
session.commit()  

session.query(Users).filter(Users.id > 2).update({"name" : "999"})
session.query(Users).filter(Users.id > 2).update({Users.name: Users.name + "099"}, 
synchronize_session=False)
session.query(Users).filter(Users.id > 2).update({"num": Users.num + 1}, synchronize_session="evaluate")
session.commit()

ret = session.query(Users).all()
ret = session.query(Users.name, Users.extra).all()
ret = session.query(Users).filter_by(name=‘alex‘).all()
ret = session.query(Users).filter_by(name=‘alex‘).first()

其他

# 条件
ret = session.query(Users).filter_by(name=‘alex‘).all()
ret = session.query(Users).filter(Users.id > 1, Users.name == ‘eric‘).all()
ret = session.query(Users).filter(Users.id.between(1, 3), Users.name == ‘eric‘).all()
ret = session.query(Users).filter(Users.id.in_([1,3,4])).all()
ret = session.query(Users).filter(~Users.id.in_([1,3,4])).all()
ret = session.query(Users).filter(Users.id.in_(session.query(Users.id).filter_by(name=‘eric‘))).all()
from sqlalchemy import and_, or_
ret = session.query(Users).filter(and_(Users.id > 3, Users.name == ‘eric‘)).all()
ret = session.query(Users).filter(or_(Users.id < 2, Users.name == ‘eric‘)).all()
ret = session.query(Users).filter(
    or_(
        Users.id < 2,
        and_(Users.name == ‘eric‘, Users.id > 3),
        Users.extra != ""
    )).all()


# 通配符
ret = session.query(Users).filter(Users.name.like(‘e%‘)).all()
ret = session.query(Users).filter(~Users.name.like(‘e%‘)).all()

# 限制
ret = session.query(Users)[1:2]

# 排序
ret = session.query(Users).order_by(Users.name.desc()).all()
ret = session.query(Users).order_by(Users.name.desc(), Users.id.asc()).all()

# 分组
from sqlalchemy.sql import func

ret = session.query(Users).group_by(Users.extra).all()
ret = session.query(
    func.max(Users.id),
    func.sum(Users.id),
    func.min(Users.id)).group_by(Users.name).all()

ret = session.query(
    func.max(Users.id),
    func.sum(Users.id),
    func.min(Users.id)).group_by(Users.name).having(func.min(Users.id) >2).all()

# 连表

ret = session.query(Users, Favor).filter(Users.id == Favor.nid).all()

ret = session.query(Person).join(Favor).all()

ret = session.query(Person).join(Favor, isouter=True).all()


# 组合
q1 = session.query(Users.name).filter(Users.id > 2)
q2 = session.query(Favor.caption).filter(Favor.nid < 2)
ret = q1.union(q2).all()

q1 = session.query(Users.name).filter(Users.id > 2)
q2 = session.query(Favor.caption).filter(Favor.nid < 2)
ret = q1.union_all(q2).all()

  

三、单表与多表

1、一对多

# !/usr/bin/env python
# -*- coding:utf-8 -*-

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index
from sqlalchemy.orm import sessionmaker, relationship
from sqlalchemy import create_engine

engine = create_engine(‘mysql+pymysql://root:123456@127.0.0.1:3306/kong‘)  # 连接已存在的数据库

Base = declarative_base()  # 根据SQL创建一个基类

class Son(Base):
    __tablename__ = ‘son‘

    id = Column(Integer, primary_key=True)
    name = Column(String(32))
    age = Column(String(16))

    father_id = Column(Integer, ForeignKey(‘father.id‘))  # 外键(外键放在哪个类下,哪个就是多)

class Father(Base):
    __tablename__ = ‘father‘

    id = Column(Integer, primary_key=True)
    name = Column(String(32))
    age = Column(String(16))

    son = relationship(‘Son‘)  # 是取与son关联的数据(通过父关联子找)
    # son = relationship(‘Son‘, backfe="father")  # backfe="father"是(“backfe”是关键字通过子关联父找)

Base.metadata.create_all(engine)  # 创建所有的表
# Base.metadata.drop_all(engine)  # 删除表

Session = sessionmaker(bind=engine)
session = Session()
f1 = Father(name=‘alvin‘, age=50)
# session.commit()
w1 = Son(name=‘little alvin1‘, age=4)
w2 = Son(name=‘little alvin2‘, age=5)
w3 = Son(name=‘little alvin3‘, age=5)
f1.son = [w1, w2, w3]


session.add_all([f1, w1, w2])
session.commit()

 

关联查询(relationship)

#!/usr/bin/env python
#-*- coding:utf-8 -*-

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, ForeignKey, UniqueConstraint, Index
from sqlalchemy.orm import sessionmaker, relationship
from sqlalchemy import create_engine

engine = create_engine(‘mysql+pymysql://root@127.0.0.1:3306/kong‘)

Base = declarative_base()


class Son(Base):
    __tablename__ = ‘son‘
    id = Column(Integer, primary_key=True)
    name = Column(String(32))
    age= Column(String(16))

    father_id=Column(Integer,ForeignKey(‘father.id‘))  # 外键关系,关联两张表的关系(下面的关联查询)


class Father(Base):
    __tablename__ =‘father‘

    id = Column(Integer, primary_key=True)
    name = Column(String(32))
    age= Column(String(16))
    
	son=relationship(‘Son‘,backref=‘father‘)  # 相当于在father类下写father=relationship(‘father‘)和在son类下写son=relationship(‘son‘)一样的效果
											  # 通过儿子关联并找父亲的信息;通过父亲关联并找儿子的信息(这就是relationship的关系)

Base.metadata.create_all(engine)
# Base.metadata.drop_all(engine)
Session = sessionmaker(bind=engine)
session = Session()

# ret=session.query(Father.name.label(‘kkk‘),Son.name.label(‘ppp‘)).join(Son)  # (关联查询)关联儿子并拿出所有的符合条件的数据
# print(ret)								# Son.name.label(‘ppp‘)) 是给son.name起一个名字;label是关键字

#f1=session.query(Father).filter_by(id=1).first()  # 查询父亲的信息
# print(f1.son)
# s1=session.query(Son).filter_by(id=2).first()  # # 查询儿子的信息;filter_by是键值对形式的查询;filter是条件的形式查询
# print(s1.father.name,s1.name)

f1=session.query(Father).filter_by(id=1).first()  # 不加first这类的索引只能得到sql语句不能得到具体的数据。
w4=Son(name=‘little alvin4‘,age=5)  # 创建一条数据(这就是relationship内部帮实现的)
f1.son.append(w4)  # 插入这一条信息


session.add(f1)
session.commit()

  

2、多对多  

# !/usr/bin/env python
# -*- coding:utf-8 -*-


from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String, ForeignKey
from sqlalchemy.orm import sessionmaker, relationship
from sqlalchemy import create_engine

engine = create_engine(‘mysql+pymysql://root:123456@127.0.0.1:3306/kong?charset=utf8‘)  # 连接已存在的数据库; 插入汉子就要添加编码解析?charset=utf8

Base = declarative_base()  # 根据SQL创建ORM的基类

class Men_to_Wemon(Base):
    __tablename__ = ‘men_to_wemon‘
    nid = Column(Integer, primary_key=True)
    id = Column(Integer, primary_key=True)
    men_id = Column(Integer, ForeignKey(‘men.id‘))
    women_id = Column(Integer, ForeignKey(‘women.id‘))

class Men(Base):
    __tablename__ = ‘men‘
    id = Column(Integer, primary_key=True)
    name = Column(String(32))
    age = Column(String(16))
    # gf = relationship("Women", secondary=Men_to_Wemon.__table__)  # 可以在下面的backref=‘gf‘替代,表示关联;
                                                                    # secondary如果有第三张表会自动关联必须加__table__,

class Women(Base):
    __tablename__ = ‘women‘
    id = Column(Integer, primary_key=True)
    name = Column(String(32))
    age = Column(String(16))
    bf = relationship("Men", secondary=Men_to_Wemon.__table__, backref=‘gf‘)

Base.metadata.create_all(engine)  # 在数据库生成表
Session = sessionmaker(bind=engine)  # 通过激活sessionmaker的__call__方法来return一个Session实例(Session类下提供了增删改查的具体方法)
session = Session()

# 下面是插入数据
# m1 = Men(name=‘alex‘, age=18)
# m2 = Men(name=‘wusir‘, age=18)
# w1 = Women(name=‘如花‘, age=26)
# w2 = Women(name=‘铁蛋‘, age=30)
# session.add_all([m1, m2, w1, w2])
# session.commit()  # 提交添加的数据

# t1 = Men_to_Wemon(men_id=1, women_id=2)  # 第三张表,让之前的两张表创建一个对应关系



m1 = session.query(Men).filter_by(id=2).first()  # 查询Men的信息是(列表)
w1 = session.query(Women).all()  # 查询Women的信息是(列表)
m1.gf = w1  # 让查询的信息创建关系

session.add_all([m1])
session.commit()

# 需要注意的地方:
#    1 查询时如果不加all,first等,得到的是sql语句,加上后,才是具体的结果;而all的结果是一个列表。
#    2 m1.gf是一个列表,里面存放着符合条件的对象。
#    3 filter与filter_by的区别:filter是拿键值对的参数,filter_by是拿条件判断的参数。

  

  

 更多详情:http://www.cnblogs.com/yuanchenqi/articles/5638282.html

     http://www.cnblogs.com/wupeiqi/articles/5713330.html

 实例:http://www.cnblogs.com/yuanchenqi/articles/5736332.html

  

Python操作mysql之SQLAchemy(ORM框架)

标签:

原文地址:http://www.cnblogs.com/kongqi816-boke/p/5752510.html

(0)
(0)
   
举报
评论 一句话评论(0
登录后才能评论!
© 2014 mamicode.com 版权所有  联系我们:gaon5@hotmail.com
迷上了代码!