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  • SqlAlchemy ORM

    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：

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    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

    　　

    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。

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    #!/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)
      
    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()

    　　

    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。

    增删改查

    一个简单的完整例子

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    from sqlalchemy import create_engine
    from sqlalchemy.ext.declarative import declarative_base
    from sqlalchemy import Column, Integer, String
    from  sqlalchemy.orm import sessionmaker
     
    Base = declarative_base() #生成一个SqlORM 基类
     
     
    engine = create_engine("mysql+mysqldb://root@localhost:3306/test",echo=False)
     
     
    class Host(Base):
        __tablename__ = 'hosts'
        id = Column(Integer,primary_key=True,autoincrement=True)
        hostname = Column(String(64),unique=True,nullable=False)
        ip_addr = Column(String(128),unique=True,nullable=False)
        port = Column(Integer,default=22)
     
    Base.metadata.create_all(engine) #创建所有表结构
     
    if __name__ == '__main__':
        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
        session = SessionCls()
        #h1 = Host(hostname='localhost',ip_addr='127.0.0.1')
        #h2 = Host(hostname='ubuntu',ip_addr='192.168.2.243',port=20000)
        #h3 = Host(hostname='ubuntu2',ip_addr='192.168.2.244',port=20000)
        #session.add(h3)
        #session.add_all( [h1,h2])
        #h2.hostname = 'ubuntu_test' #只要没提交,此时修改也没问题
        #session.rollback()
        #session.commit() #提交
        res = session.query(Host).filter(Host.hostname.in_(['ubuntu2','localhost'])).all()
        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。

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    #!/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()
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    <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:

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    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:

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    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
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    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

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

    　　

    group by 查询

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    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

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    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

     
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  • 原文地址：https://www.cnblogs.com/xiajie/p/5343302.html
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