SQLAlchemy(ORM框架)
SQLAlchemy
SQLAlchemy概述
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(特定的语法代替SQL语句)。
Dialect用于和DBAPI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:
1 2 3 4 5 6 7 8 9 10 11 12 13 | 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 |
数据库操作的几种方式:
1、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。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | from sqlalchemy import create_engine #max_overflow是在初始线程数量的基础上,还能最多建立几个进程 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:
1 2 3 4 5 6 7 8 9 10 11 12 13 | from sqlalchemy import create_engine # 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 }) |
在mysql里用命令“show status like 'Threads%';”,能观察到连接线程数‘Threads_connected’的变化。
2、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。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | 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 )), ) metadata.create_all(engine) # metadata.clear() # metadata.remove() |
增删改查:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | 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 )), ) 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() |
更多内容详见:
中文:http://www.jianshu.com/p/e6bba189fcbd
英文:http://docs.sqlalchemy.org/en/latest/core/expression_api.html (比中文的全面)
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。
3、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。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | 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() |
更多功能参见文档,猛击这里下载PDF
来源:武sir博客http://www.cnblogs.com/wupeiqi/