SQLAlchemy

#!/usr/bin/env python 2 # -*- coding:utf-8 -*- 3 4 from sqlalchemy import create_engine 5 6 7 engine = create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5) 8 9 engine.execute( 10 "INSERT INTO ts_test (a, b) VALUES (‘2‘, ‘v1‘)" 11 ) 12 13 engine.execute( 14 "INSERT INTO ts_test (a, b) VALUES (%s, %s)", 15 ((555, "v1"),(666, "v1"),) 16 ) 17 engine.execute( 18 "INSERT INTO ts_test (a, b) VALUES (%(id)s, %(name)s)", 19 id=999, name="v1" 20 ) 21 22 result = engine.execute(‘select * from ts_test‘) 23 result.fetchall() 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 #!/usr/bin/env python
 2 # -*- coding:utf-8 -*-
 3 
 4 from sqlalchemy import create_engine
 5 
 6 
 7 engine = create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
 8 
 9 
10 # 事务操作
11 with engine.begin() as conn:
12     conn.execute("insert into table (x, y, z) values (1, 2, 3)")
13     conn.execute("my_special_procedure(5)")
14     
15     
16 conn = engine.connect()
17 # 事务操作 
18 with conn.begin():
19        conn.execute("some statement", {‘x‘:5, ‘y‘:10})

事务

 

 1 ‘‘‘
 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。
 3 ‘‘‘
 4 
 5 
 6 #!/usr/bin/env python
 7 # -*- coding:utf-8 -*-
 8  
 9 from sqlalchemy import create_engine, Table, Column, Integer, String, MetaData, ForeignKey
10  
11 metadata = MetaData()
12  
13 user = Table(‘user‘, metadata,
14     Column(‘id‘, Integer, primary_key=True),
15     Column(‘name‘, String(20)),
16 )
17  
18 color = Table(‘color‘, metadata,
19     Column(‘id‘, Integer, primary_key=True),
20     Column(‘name‘, String(20)),
21 )
22 engine = create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
23  
24 metadata.create_all(engine)
25 # metadata.clear()
26 # metadata.remove()

2

#!/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

增删改查

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。

 1 #!/usr/bin/env python
 2 # -*- coding:utf-8 -*-
 3  
 4 from sqlalchemy.ext.declarative import declarative_base
 5 from sqlalchemy import Column, Integer, String
 6 from sqlalchemy.orm import sessionmaker
 7 from sqlalchemy import create_engine
 8  
 9 engine = create_engine("mysql+mysqldb://root:123@127.0.0.1:3306/s11", max_overflow=5)
10  
11 Base = declarative_base()
12  
13  
14 class User(Base):
15     __tablename__ = ‘users‘
16     id = Column(Integer, primary_key=True)
17     name = Column(String(50))
18  
19 # 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
20 # Base.metadata.create_all(engine)
21  
22 Session = sessionmaker(bind=engine)
23 session = Session()
24  
25  
26 # ########## 增 ##########
27 # u = User(id=2, name=‘sb‘)
28 # session.add(u)
29 # session.add_all([
30 #     User(id=3, name=‘sb‘),
31 #     User(id=4, name=‘sb‘)
32 # ])
33 # session.commit()
34  
35 # ########## 删除 ##########
36 # session.query(User).filter(User.id > 2).delete()
37 # session.commit()
38  
39 # ########## 修改 ##########
40 # session.query(User).filter(User.id > 2).update({‘cluster_id‘ : 0})
41 # session.commit()
42 # ########## 查 ##########
43 # ret = session.query(User).filter_by(name=‘sb‘).first()
44  
45 # ret = session.query(User).filter_by(name=‘sb‘).all()
46 # print ret
47  
48 # ret = session.query(User).filter(User.name.in_([‘sb‘,‘bb‘])).all()
49 # print ret
50  
51 # ret = session.query(User.name.label(‘name_label‘)).all()
52 # print ret,type(ret)
53  
54 # ret = session.query(User).order_by(User.id).all()
55 # print ret
56  
57 # ret = session.query(User).order_by(User.id)[1:3]
58 # print ret
59 # session.commit()

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。

 

SQLAlchemy

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