SQLAlchemy使用笔记--SQLAlchemy ORM(二)
參考:
http://docs.sqlalchemy.org/en/rel_1_0/orm/tutorial.html#building-a-relationship
http://docs.sqlalchemy.org/en/rel_1_0/orm/tutorial.html#working-with-related-objects
建立表之间带关系
建立外建
在address加入user的外键
from sqlalchemy import ForeignKey, Column, String, Integer
from sqlalchemy.orm import relationship
class User(Base):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
name = Column(String)
fullname = Column(String)
password = Column(String)
class Address(Base):
__tablename__ = 'addresses'
id = Column(Integer, primary_key=True)
email_address = Column(String, nullable=False)
user_id = Column(Integer, ForeignKey('users.id'))
user = relationship('User', backref=backref('addresses', order_by=id))
relationship中的backref參数使用形式:
backref="addresses" #直接使用表名的字符串
backref=backref('addresses') #使用backref函数
backref=backref('addresses', order_by=id)) #brackref函数能够加入參数,详见http://docs.sqlalchemy.org/en/rel_1_0/orm/backref.html#backref-arguments
能够使用user.addresses 从user获取address 和,使用address.users 虫address获取user
backref 会在User跟Address上都加上关系,它本质是:
from sqlalchemy import Integer, ForeignKey, String, Column
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import relationship
Base = declarative_base()
class User(Base):
__tablename__ = 'user'
id = Column(Integer, primary_key=True)
name = Column(String)
addresses = relationship("Address", back_populates="user")
class Address(Base):
__tablename__ = 'address'
id = Column(Integer, primary_key=True)
email = Column(String)
user_id = Column(Integer, ForeignKey('user.id'))
user = relationship("User", back_populates="addresses")
relationship中的
加入
>>> jack.addresses = [
... Address(email_address='jack@google.com'),
... Address(email_address='j25@yahoo.com')]
获取
>>> jack.addresses[1]
<Address(email_address='j25@yahoo.com')>
>>> jack.addresses[1].user
<User(name='jack', fullname='Jack Bean', password='gjffdd')>
commit
session.add(jack)
session.commit()
address 会自己主动的加入
one to many 关系
class Parent(Base):
__tablename__ = 'parent'
id = Column(Integer, primary_key=True)
children = relationship("Child", backref="parent")
class Child(Base):
__tablename__ = 'child'
id = Column(Integer, primary_key=True)
parent_id = Column(Integer, ForeignKey('parent.id'))
many to one 关系
class Parent(Base):
__tablename__ = 'parent'
id = Column(Integer, primary_key=True)
child_id = Column(Integer, ForeignKey('child.id'))
child = relationship("Child", backref="parents")
class Child(Base):
__tablename__ = 'child'
id = Column(Integer, primary_key=True)
one to one 关系
from sqlalchemy.orm import backref
class Parent(Base):
__tablename__ = 'parent'
id = Column(Integer, primary_key=True)
child_id = Column(Integer, ForeignKey('child.id'))
child = relationship("Child", backref=backref("parent", uselist=False))
class Child(Base):
__tablename__ = 'child'
id = Column(Integer, primary_key=True)
many to many 关系
须要一个中间表和在relatonship 加入secondary參数
association_table = Table('association', Base.metadata,
Column('left_id', Integer, ForeignKey('left.id')),
Column('right_id', Integer, ForeignKey('right.id'))
)
class Parent(Base):
__tablename__ = 'left'
id = Column(Integer, primary_key=True)
children = relationship("Child",
secondary=association_table,
backref="parents")
class Child(Base):
__tablename__ = 'right'
id = Column(Integer, primary_key=True)
这样在child加入删除parent或者parent加入删除child时,无需对中间表进行操作。直接加入删除就可以。
parent.children.append(child)
child.parents.append(parent)
也能够 使用类来创建中间表,这样能够在中间表中保存一些其它的信息。可是就不能想前面一样自己主动对中间表进行操作。
class Association(Base):
__tablename__ = 'association'
left_id = Column(Integer, ForeignKey('left.id'), primary_key=True)
right_id = Column(Integer, ForeignKey('right.id'), primary_key=True)
extra_data = Column(String(50))
child = relationship("Child", back_populates="parents")
parent = relationship("Parent", back_populates="children")
class Parent(Base):
__tablename__ = 'left'
id = Column(Integer, primary_key=True)
children = relationship("Association", back_populates="parent")
class Child(Base):
__tablename__ = 'right'
id = Column(Integer, primary_key=True)
parents = relationship("Association", back_populates="child")
join 操作
能够使用Query.join()
>>> session.query(User).join(Address).\
... filter(Address.email_address=='jack@google.com').\
... all()
[<User(name='jack', fullname='Jack Bean', password='gjffdd')>]
在User上能够直接使用join(Address) 由于仅仅有一个外建在User和Address之间,其它join形式:
query.join(Address, User.id==Address.user_id) # explicit condition
query.join(User.addresses) # specify relationship from left to right
query.join(Address, User.addresses) # same, with explicit target
query.join('addresses') # same, using a string
使用外链接
query.outerjoin(User.addresses) # 默认是左外连接。
当query中有多个实体点使用,使用join默认join追左边的那个,
比如:
query = session.query(User, Address).join(User) # 报错
query = session.query(Address, User).join(User) # 正确
假设想自定使用join那个表。能够使用select_form
query = Session.query(User, Address).select_from(Address).join(User)
alias 别名
假设想join自己,能够使用别名
from sqlalchemy.orm import aliased
adalias1 = aliased(Address)
adalias2 = aliased(Address)
for username, email1, email2 in \
session.query(User.name, adalias1.email_address, adalias2.email_address).\
join(adalias1, User.addresses).\
join(adalias2, User.addresses).\
filter(adalias1.email_address=='jack@google.com').\
filter(adalias2.email_address=='j25@yahoo.com'):
print(username, email1, email2)
使用子查询
直接看官方文档的样例:
>>> from sqlalchemy.sql import func
>>> stmt = session.query(Address.user_id, func.count('*').\
... label('address_count')).\
... group_by(Address.user_id).subquery()
>>> for u, count in session.query(User, stmt.c.address_count).\
... outerjoin(stmt, User.id==stmt.c.user_id).order_by(User.id):
... print(u, count)
<User(name='ed', fullname='Ed Jones', password='f8s7ccs')> None
<User(name='wendy', fullname='Wendy Williams', password='foobar')> None
<User(name='mary', fullname='Mary Contrary', password='xxg527')> None
<User(name='fred', fullname='Fred Flinstone', password='blah')> None
<User(name='jack', fullname='Jack Bean', password='gjffdd')> 2
使用EXISTS
看官方文档的样例:
>>> from sqlalchemy.sql import exists
>>> stmt = exists().where(Address.user_id==User.id)
SQL>>> for name, in session.query(User.name).filter(stmt):
... print(name)
jack
等价于:
>>> for name, in session.query(User.name).\
... filter(User.addresses.any()):
... print(name)
jack
user.addresses 能够像user中其它属性一样在filter使用==、!=、any等等。
query.filter(Address.user == someuser)
query.filter(Address.user != someuser)
query.filter(Address.user == None)
query.filter(User.addresses.contains(someaddress))
query.filter(User.addresses.any(Address.email_address == 'bar'))# also takes keyword arguments:
query.filter(User.addresses.any(email_address='bar'))
query.filter(Address.user.has(name='ed'))
session.query(Address).with_parent(someuser, 'addresses')
posted on 2017-08-03 11:48 cynchanpin 阅读(249) 评论(0) 编辑 收藏 举报