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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() |
#!/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。
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#!/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 ) 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()
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() |
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原文地址:http://www.cnblogs.com/zhaozhenguo666/p/5700848.html