• Python全栈之路-MySQL(七)


    1 面向对象回顾

    函数编程:数据和逻辑分离
    面向对象:数据和逻辑(属性和行为)组合在一起

    类的特殊方法: __call__ __getitem__ __setitem__ __delitem__
    

    2 SQLAlchemy

    ORM 框架:SQLAlchemy
    ORM框架原理:
    目的是让用户不在写SQL语句,而是通过ORM框架内的类和对象的方式以及ORM内部提供的方法来进行数据库操作,ORM框架进行转换SQL语句,并执行结果返回给用户

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

    类 --> 数据表 对象 --> 数据行

    2.1 作用

    • 提供简单的规则
    • 自动转换成SQL语句

    2.2 DB first / Code first

    DB first:手动创建数据库以及表 --> ORM框架 --> 自动生成类
    Code first:手动创建类和数据库 --> ORM框架 --> 自动生成表

    SQLAlchemy默认支持Code first

    SQLAlchemy功能:

    • 创建数据库表
      • 连接数据库(非SQLAlchemy做的,SQLAlchemy借助DBAPI(pymysql)做的)
      • 类转换SQL语句

    2.3 SQLAlchemy实战

    #!/usr/bin/env python
    # __Author__: "wanyongzhen"
    # Date: 2017/6/14
    
    from sqlalchemy.ext.declarative import declarative_base
    from sqlalchemy import Column,Integer,String,ForeignKey,UniqueConstraint,Index,CHAR,VARCHAR
    from sqlalchemy.orm import sessionmaker, relationship
    from sqlalchemy import create_engine
    
    # 封装了SQLAlchemy的功能的类
    Base = declarative_base()
    
    # 创建单表
    class UserType(Base):
        __tablename__ = 'usertype'
        id = Column(Integer, primary_key=True, autoincrement=True)
        user_type_name = Column(String(32), nullable=True, index=True)
    
    class Users(Base):
        __tablename__ = 'users'
        id = Column(Integer, primary_key=True, autoincrement=True)
        name = Column(String(32), nullable=True, default='df', index=True)
        email = Column(String(16), unique=True)
        user_type_id = Column(Integer, ForeignKey('usertype.id'))
        __table_args__ = (
            UniqueConstraint('id', 'name', name='unique_id_name'), # 联合唯一索引
            Index('index_name_email', 'name', 'email'),            # 联合索引
        )
        user_type = relationship("UserType",backref="xxoo")  # 建立关系
    
    def init_db():
        Base.metadata.create_all(engine)  # 找到当前页面所有的表(继承了Base的类)进行创建
    
    def drop_db():
        Base.metadata.drop_all(engine)    # 找到当前页面所有的表(继承了Base的类)进行删除
    
    
    
    # 调用pymysql创建连接 最大连接数为5
    engine = create_engine("mysql+pymysql://root:123456@127.0.0.1:3306/db02?charset=utf8", max_overflow=5)
    # drop_db()
    # init_db()
    
    Session = sessionmaker(bind=engine)
    session = Session()
    
    # 添加单条数据
    # obj1 = UserType(user_type_name='黑金用户')
    # session.add(obj1)
    
    # 添加多条数据
    # objs = [
    #     UserType(user_type_name='白金用户'),
    #     UserType(user_type_name='绿金用户'),
    #     UserType(user_type_name='黄金用户'),
    # ]
    # session.add_all(objs)
    
    # 查询
    # user_type_list = session.query(UserType).all() # session.query(UserType)返回SQL语句,后面加.all()返回SQL语句执行得到的数据
    # print(type(user_type_list))   # list类型
    # print(user_type_list)    # list里面存放了多个UserType对象
    # for row in user_type_list:
    #     print(row.id,row.user_type_name)
    
    # filter 想当于where条件
    user_type_list = session.query(UserType).filter(UserType.id > 2)
    print(type(user_type_list))
    print(user_type_list)
    for row in user_type_list:
        print(row.id, row.user_type_name)
    
    # 删除
    # delete()
    # session.query(UserType).filter(UserType.id > 2).delete()
    
    # 修改
    # update()
    session.query(UserType).filter(UserType.id > 2).update({UserType.user_type_name: '粉金用户'})
    # session.query(UserType).filter(UserType.id > 2).update({UserType.user_type_name: UserType.user_type_name + "099"}, synchronize_session=False) # 处理字符串
    # session.query(UserType).filter(UserType.id > 2).update({"num": Users.num + 1}, synchronize_session="evaluate") # 处理数字
    
    # 连表(通过外键)
    session.query(Users).join(UserType).all()  # inner join
    session.query(Users).join(UserType, isouter=True).all()  # left join
    
    # 子查询
    # select * from (select * from tb) as B
    # q1 = session.query(UserType).filter(UserType.id > 0).subquery()
    # result = session.query(q1).all()
    # print(result)
    # select id,(select id from where id=x) from xxx;
    # result = session.query(UserType.id, session.query(Users.name).filter(Users.user_type_id == UserType.id).as_scalar()).all()
    # print(result)
    
    # 问题1:获取用户欣欣以及与其关联的用户类型名称
    user_list = session.query(Users.name, UserType.user_type_name).join(UserType, isouter=True).all()
    # user_list = session.query(Users, UserType).join(UserType, isouter=True)
    # 加all()获取到所有数据,不加all()是迭代器
    
    print(type(user_list))
    for row in user_list:
        # print(row[0].id, row[0].name, row[0].user_type_id, row[1].user_type_name)
        print(row[0], row[1], row.name, row.user_type_name) # 通过索引和属性都可以获取
    # 建立relationship后  正向操作
    user_list = session.query(Users)
    for row in user_list:
        print(row.name, row.id, row.user_type, row.user_type.user_type_name)  # row.user_type是一个对象
    
    # 问题2:获取用户类型,并获取有哪些用户
    # 传统方式
    # type_list = session.query(UserType)
    # for row in type_list:
    #     print(row.id, row.user_type_name, session.query(Users).filter(Users.user_type_id == row.id).all())
    # backref方式  反向操作
    type_list = session.query(UserType)
    for row in type_list:
        print(row.id, row.user_type_name, row.xxoo)
    
    
    session.commit()
    session.close()
    

    2.4 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 limit 
    ret = session.query(Users)[1:2]
    
    # 排序 order by 
    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group by 
    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()
    
    
    # 组合union
    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()
    
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  • 原文地址:https://www.cnblogs.com/wanyuetian/p/7018544.html
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