SqlAlchemy ORM
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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 + 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...] |
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.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 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 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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