一、对象映射关系（ORM）
orm英文全称object relational mapping,就是对象映射关系程序，简单来说我们类似python这种面向对象的程序来说一切皆对象，但是我们使用的数据库却都是关系型的，为了保证一致的使用习惯，通过orm将编程语言的对象模型和数据库的关系模型建立映射关系，这样我们在使用编程语言对数据库进行操作的时候可以直接使用编程语言的对象模型进行操作就可以了，而不用直接使用sql语言
优点：
- 隐藏了数据访问细节，“封闭”的通用数据库交互，ORM的核心。他使得我们的通用数据库交互变得简单易行，并且完全不用考虑该死的SQL语句。快速开发，由此而来
- ORM使我们构造固化数据结构变得简单易行
缺点：
- 无可避免的，自动化意味着映射和关联管理，代价是牺牲性能（早期，这是所有不喜欢ORM人的共同点）。现在的各种ORM框架都在尝试使用各种方法来减轻这块（LazyLoad，Cache），效果还是很显著的
二、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。
在Python中，最有名的ORM框架是SQLAlchemy。用户包括openstack＼Dropbox等知名公司或应用
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>] 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注：支持连接MySQL、Oracles数据库
安装：
pip install SQLAlchemypip install pymysql #由于mysqldb依然不支持py3，所以这里我们用pymysql与sqlalchemy交互步骤一：
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 -*-from sqlalchemy import create_engineengine = 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：
#!/usr/bin/env python
# -*- coding:utf-8 -*-
from sqlalchemy import create_engine
engine = create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
# 事务操作
with engine.begin() as conn:
conn.execute("insert into table (x, y, z) values (1, 2, 3)")
conn.execute("my_special_procedure(5)")
conn = engine.connect()
# 事务操作
with conn.begin():
conn.execute("some statement", {'x':5, 'y':10})
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 -*-from sqlalchemy import create_engine, Table, Column, Integer, String, MetaData, ForeignKeymetadata = 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()#!/usr/bin/env python # -*- coding:utf-8 -*- from sqlalchemy import create_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) conn = engine.connect() # 创建SQL语句，INSERT INTO "user" (id, name) VALUES (:id, :name) conn.execute(user.insert(),{'id':7,'name':'seven'}) conn.close() # sql = user.insert().values(id=123, name='wu') # conn.execute(sql) # conn.close() # sql = user.delete().where(user.c.id > 1) # sql = user.update().values(fullname=user.c.name) # sql = user.update().where(user.c.name == 'jack').values(name='ed') # sql = select([user, ]) # sql = select([user.c.id, ]) # sql = select([user.c.name, color.c.name]).where(user.c.id==color.c.id) # sql = select([user.c.name]).order_by(user.c.name) # sql = select([user]).group_by(user.c.name) # result = conn.execute(sql) # print result.fetchall() # conn.close()
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_basefrom sqlalchemy import Column, Integer, Stringfrom sqlalchemy.orm import sessionmakerfrom sqlalchemy import create_engineengine = 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()1、基本使用
CREATE TABLE user ( id INTEGER NOT NULL AUTO_INCREMENT, name VARCHAR(32), password VARCHAR(64), PRIMARY KEY (id))这只是最简单的sql表，如果再加上外键关联什么的，一般程序员的脑容量是记不住那些sql语句的，于是有了orm,实现上面同样的功能，代码如下：
# 创建表结构import sqlalchemyfrom sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import Column,Integer,Stringengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8",echo=True) #echo=True 打印程序运行详细信息Base = declarative_base() #生成orm基类class User(Base): __tablename__ = "user" #表名 id = Column(Integer,primary_key=True) name = Column(String(32)) password = Column(String(64))Base.metadata.create_all(engine) #创建表结构# 打印输出# 2016-10-26 08:42:02,619 INFO sqlalchemy.engine.base.Engine SHOW VARIABLES LIKE 'sql_mode'# 2016-10-26 08:42:02,619 INFO sqlalchemy.engine.base.Engine {}# 2016-10-26 08:42:02,622 INFO sqlalchemy.engine.base.Engine SELECT DATABASE()# 2016-10-26 08:42:02,622 INFO sqlalchemy.engine.base.Engine {}# 2016-10-26 08:42:02,624 INFO sqlalchemy.engine.base.Engine show collation where `Charset` = 'utf8' and `Collation` = 'utf8_bin'# 2016-10-26 08:42:02,624 INFO sqlalchemy.engine.base.Engine {}# 2016-10-26 08:42:02,649 INFO sqlalchemy.engine.base.Engine SELECT CAST('test plain returns' AS CHAR(60)) AS anon_1# 2016-10-26 08:42:02,649 INFO sqlalchemy.engine.base.Engine {}# 2016-10-26 08:42:02,651 INFO sqlalchemy.engine.base.Engine SELECT CAST('test unicode returns' AS CHAR(60)) AS anon_1# 2016-10-26 08:42:02,651 INFO sqlalchemy.engine.base.Engine {}# 2016-10-26 08:42:02,652 INFO sqlalchemy.engine.base.Engine SELECT CAST('test collated returns' AS CHAR CHARACTER SET utf8) # COLLATE utf8_bin AS anon_1# 2016-10-26 08:42:02,652 INFO sqlalchemy.engine.base.Engine {}# 2016-10-26 08:42:02,655 INFO sqlalchemy.engine.base.Engine DESCRIBE `user`# 2016-10-26 08:42:02,655 INFO sqlalchemy.engine.base.Engine {}# 2016-10-26 08:42:02,657 INFO sqlalchemy.engine.base.Engine ROLLBACK# 2016-10-26 08:42:02,660 INFO sqlalchemy.engine.base.Engine# CREATE TABLE user (# id INTEGER NOT NULL AUTO_INCREMENT,# name VARCHAR(32),# password VARCHAR(64),# PRIMARY KEY (id)# )### 2016-10-26 08:42:02,660 INFO sqlalchemy.engine.base.Engine {}# 2016-10-26 08:42:02,904 INFO sqlalchemy.engine.base.Engine COMMITmysql> desc user;+----------+-------------+------+-----+---------+----------------+| Field | Type | Null | Key | Default | Extra |+----------+-------------+------+-----+---------+----------------+| id | int(11) | NO | PRI | NULL | auto_increment || name | varchar(32) | YES | | NULL | || password | varchar(64) | YES | | NULL | |+----------+-------------+------+-----+---------+----------------+3 rows in set (0.01 sec)
2、创建数据
最基本的表我们创建好了，那我们开始用orm创建一条数据试试
# 创建表数据from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Integer,Columnfrom sqlalchemy.orm import sessionmakerengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8")Base = declarative_base() #生成orm基类class User(Base): __tablename__ = "user" #表名 id = Column(Integer,primary_key=True) name = Column(String(32)) password = Column(String(64))#Base.metadata.create_all(engine) #创建表结构Session_class = sessionmaker(bind=engine) #Session_class现在不是实例，而是类Session = Session_class() #生成Session实例user_obj = User(name="lzl",password="123456") #生成你要创建的数据对象print(user_obj.name,user_obj.id) #此时还没创建对象呢，不信你打印一下id发现还是NoneSession.add(user_obj) #把要创建的数据对象添加到这个session里， 一会统一创建print(user_obj.name,user_obj.id) #此时也依然还没创建Session.commit() #现此才统一提交，创建数据3、查询数据
# 查询from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Integer,Columnfrom sqlalchemy.orm import sessionmakerengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8")Base = declarative_base() #生成orm基类class User(Base): __tablename__ = "user" #表名 id = Column(Integer,primary_key=True) name = Column(String(32)) password = Column(String(64))Session_class = sessionmaker(bind=engine) #Session_class现在不是实例，而是类Session = Session_class() #生成Session实例my_user = Session.query(User).filter_by(name="lzl").first()print(my_user) #my_user此时是一个对象#<__main__.User object at 0x03EFC6D0>print(my_user.id,my_user.name,my_user.password)多条件查询：
from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Integer,Columnfrom sqlalchemy.orm import sessionmakerfrom sqlalchemy import funcengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8")Base = declarative_base() #生成orm基类class User(Base): __tablename__ = "user" #表名 id = Column(Integer,primary_key=True) name = Column(String(32)) password = Column(String(64)) def __repr__(self): return "<User(name='%s', password='%s')>" % ( self.name, self.password)Session_class = sessionmaker(bind=engine) #Session_class现在不是实例，而是类Session = Session_class() #生成Session实例objs = Session.query(User).filter(User.id>3).filter(User.id<8).all()print(objs)统计：
# 统计from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Integer,Columnfrom sqlalchemy.orm import sessionmakerfrom sqlalchemy import funcengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8")Base = declarative_base() #生成orm基类class User(Base): __tablename__ = "user" #表名 id = Column(Integer,primary_key=True) name = Column(String(32)) password = Column(String(64)) def __repr__(self): return "<User(name='%s', password='%s')>" % ( self.name, self.password)Session_class = sessionmaker(bind=engine) #Session_class现在不是实例，而是类Session = Session_class() #生成Session实例分组：
# 分组from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Integer,Columnfrom sqlalchemy.orm import sessionmakerfrom sqlalchemy import funcengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8")Base = declarative_base() #生成orm基类class User(Base): __tablename__ = "user" #表名 id = Column(Integer,primary_key=True) name = Column(String(32)) password = Column(String(64)) def __repr__(self): return "<User(name='%s', password='%s')>" % ( self.name, self.password)Session_class = sessionmaker(bind=engine) #Session_class现在不是实例，而是类Session = Session_class() #生成Session实例print(Session.query(func.count(User.name),User.name).group_by(User.name).all())4、修改
# 修改from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Integer,Columnfrom sqlalchemy.orm import sessionmakerengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8")Base = declarative_base() #生成orm基类class User(Base): __tablename__ = "user" #表名 id = Column(Integer,primary_key=True) name = Column(String(32)) password = Column(String(64)) def __str__(self): return "<User(name='%s', password='%s')>" % ( self.name, self.password)Session_class = sessionmaker(bind=engine) #Session_class现在不是实例，而是类Session = Session_class() #生成Session实例my_user = Session.query(User).filter_by(name="ljb").first()print(my_user)#<User(name='ljb', password='123456')>my_user.name = "lijiabao"Session.commit() #提交数据5、回滚
# 回滚from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Integer,Columnfrom sqlalchemy.orm import sessionmakerengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8")Base = declarative_base() #生成orm基类class User(Base): __tablename__ = "user" #表名 id = Column(Integer,primary_key=True) name = Column(String(32)) password = Column(String(64)) def __repr__(self): return "<User(name='%s', password='%s')>" % ( self.name, self.password)Session_class = sessionmaker(bind=engine) #Session_class现在不是实例，而是类Session = Session_class() #生成Session实例my_user = Session.query(User).filter_by(id = 1).first()my_user.name = "Jack"print(my_user)# <User(name='Jack', password='123456')>Rain_user = User(name="Rain",password="12345")Session.add(Rain_user)print(Session.query(User).filter(User.name.in_(["Jack","Rain"])).all()) # 这时看session里有你刚添加和修改的数据#[<User(name='Jack', password='123456')>, <User(name='Rain', password='12345')>]Session.rollback()print(Session.query(User).filter(User.name.in_(["Jack","Rain"])).all()) #再查就发现刚才添加的数据没有了。6、外键关联
我们先创建个study_record表与student进行关联
# 外键关联from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Column,Integer,ForeignKey,DATEfrom sqlalchemy.orm import sessionmaker,relationshipengine = create_engine("mysql+pymysql://root:zyw@123@192.168.0.59/lzl", encoding="utf-8")Base = declarative_base()class Student(Base): __tablename__ ="student" id = Column(Integer,primary_key=True) name = Column(String(32),nullable=False) register_date = Column(DATE,nullable=False) def __repr__(self): return "<%s name:%s>"%(self.id,self.name)class StudyRecord(Base): __tablename__ = "study_record" id = Column(Integer,primary_key=True) day = Column(Integer,nullable=False) status = Column(String(32),nullable=False) stu_id = Column(Integer,ForeignKey("student.id")) #关联student表里的id my_student = relationship("Student",backref="my_study_record") # Student为关联的类def __repr__(self):
return "<%s name:%s>" % (self.id, self.name)Base.metadata.create_all(engine)Session_class = sessionmaker(bind=engine)session = Session_class()s2 = Student(name="alex",register_date="2015-10-26")s3 = Student(name="eric",register_date="2014-10-26")s4 = Student(name="rain",register_date="2013-10-26")r1 = StudyRecord(day=1,status="YES",stu_id=1)r2 = StudyRecord(day=2,status="No",stu_id=1)r3 = StudyRecord(day=3,status="YES",stu_id=1)r4 = StudyRecord(day=1,status="YES",stu_id=2)session.add_all([s1,s2,s3,s4,r1,r2,r3,r4])session.commit()注：my_student = relationship("Student",backref="my_study_record")这个nb，允许你在user表里通过backref字段反向查出所有它在addresses表里的关联项
查询：
# 外键查询from sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import String,Column,Integer,ForeignKey,DATEfrom sqlalchemy.orm import sessionmaker,relationshipengine = create_engine("mysql+pymysql://root:zyw@123@192.168.0.59/lzl", encoding="utf-8")Base = declarative_base()class Student(Base): __tablename__ ="student" id = Column(Integer,primary_key=True) name = Column(String(32),nullable=False) register_date = Column(DATE,nullable=False) def __repr__(self): return "<id:%s name:%s>"%(self.id,self.name)class StudyRecord(Base): __tablename__ = "study_record" id = Column(Integer,primary_key=True) day = Column(Integer,nullable=False) status = Column(String(32),nullable=False) stu_id = Column(Integer,ForeignKey("student.id")) #关联student表里的id my_student = relationship("Student",backref="my_study_record") # Student为关联的类 def __repr__(self): return "<name:%s day:%s status:%s>" % (self.my_student.name,self.day,self.status)Base.metadata.create_all(engine)Session_class = sessionmaker(bind=engine)session = Session_class()stu_obj = session.query(Student).filter(Student.name=="ljb").first()print(stu_obj) print(stu_obj.my_study_record)7、多外键关联
下表中，Customer表有2个字段都关联了Address表，首先先创建表结构
# 多外键关联from sqlalchemy import create_enginefrom sqlalchemy import Integer,String,Column,ForeignKeyfrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy.orm import sessionmaker,relationshipengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8",echo= True)Base = declarative_base()class Customer(Base): __tablename__ = "customer" id = Column(Integer,primary_key=True) name = Column(String(32)) billing_address_id = Column(Integer,ForeignKey("address.id")) shipping_address_id = Column(Integer, ForeignKey("address.id")) billing_address = relationship("Address",foreign_keys=[billing_address_id]) #必须写foreign_keys shipping_address = relationship("Address",foreign_keys=[shipping_address_id])class Address(Base): __tablename__ = 'address' id = Column(Integer, primary_key=True) street = Column(String(32)) city = Column(String(32)) state = Column(String(32))Base.metadata.create_all(engine)生成数据：
Session = sessionmaker(bind=engine)session = Session()a1 = Address(street="Tiantongyuan",city="ChangPing",state="BJ")a2 = Address(street="Wudaokou",city="HaiDian",state="BJ")a3 = Address(street="Yanjiao",city="LangFang",state="HB")session.add_all([a1,a2,a3])c1 = Customer(name="lzl",billing_address_id=1,shipping_address_id=2)c2 = Customer(name="Alex",billing_address_id=3,shipping_address_id=3)session.add_all([c1,c2])session.commit()查询数据：
class Customer(Base): __tablename__ = "customer" id = Column(Integer,primary_key=True) name = Column(String(32)) billing_address_id = Column(Integer,ForeignKey("address.id")) shipping_address_id = Column(Integer, ForeignKey("address.id")) billing_address = relationship("Address",foreign_keys=[billing_address_id]) #必须写foreign_keys shipping_address = relationship("Address",foreign_keys=[shipping_address_id]) def __repr__(self): return "<name:%s billing_add:%s shipping_add:%s>"%(self.name,self.billing_address.street, self.shipping_address.street)#Base.metadata.create_all(engine)Session = sessionmaker(bind=engine)session = Session()cus_obj = session.query(Customer).filter_by(name="ljb").first()print(cus_obj)8、多对多关联
现在来设计一个能描述“图书”与“作者”的关系的表结构，需求是
- 一本书可以有好几个作者一起出版
- 一个作者可以写好几本书
创建表结构：
#一本书可以有多个作者，一个作者又可以出版多本书from sqlalchemy import Table, Column, Integer,String,DATE, ForeignKeyfrom sqlalchemy.orm import relationshipfrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import create_enginefrom sqlalchemy.orm import sessionmakerengine = create_engine("mysql+pymysql://root:zyw@123@192.168.20.219/lzl", encoding="utf-8")Base = declarative_base()#创建book_m2m_author表，表不用用户操作，系统自动维护，自动添加数据book_m2m_author = Table('book_m2m_author', Base.metadata, Column('book_id',Integer,ForeignKey('books.id')), Column('author_id',Integer,ForeignKey('authors.id')), )class Book(Base): __tablename__ = 'books' id = Column(Integer,primary_key=True) name = Column(String(64)) pub_date = Column(DATE) #关联Author类，secondary表示通过book_m2m_author表进行查询关联数据，backref反向查询也一样 authors = relationship('Author',secondary=book_m2m_author,backref='books') def __repr__(self): return self.nameclass Author(Base): __tablename__ = 'authors' id = Column(Integer, primary_key=True) name = Column(String(32)) def __repr__(self): return self.nameBase.metadata.create_all(engine)创建表数据：
#创建数据Session = sessionmaker(bind=engine)session = Session()b1 = Book(name="learn python with Alex",pub_date="2014-05-02")b2 = Book(name="learn linux with Alex",pub_date="2015-05-02")b3 = Book(name="learn go with Alex",pub_date="2016-05-02")a1 = Author(name="Alex")a2 = Author(name="Jack")a3 = Author(name="Rain")#关键来了，创建关联关系b1.authors = [a1,a3]b3.authors = [a1,a2,a3]session.add_all([b1,b2,b3,a1,a2,a3])session.commit()查询：
author_obj = session.query(Author).filter_by(name="Alex").first()print(author_obj,author_obj.books)book_obj = session.query(Book).filter_by(id=2).first()print(book_obj,book_obj.authors)9、多对多删除
删除数据时不用管boo_m2m_authors ， sqlalchemy会自动帮你把对应的数据删除
通过书删除作者
author_obj =s.query(Author).filter_by(name="Jack").first() book_obj = s.query(Book).filter_by(name="跟Alex学把妹").first() book_obj.authors.remove(author_obj) #从一本书里删除一个作者s.commit()直接删除作者
删除作者时，会把这个作者跟所有书的关联关系数据也自动删除
author_obj =s.query(Author).filter_by(name="Alex").first()# print(author_obj.name , author_obj.books)s.delete(author_obj)s.commit()