知乎： sqlalchemy 的 Core 方式操作数据是一种怎样的体验？
答： 爽！
本文基于：win 10 + python 3.4 + sqlalchemy 1.0.13
基本步骤如下：
1. 绑定数据库
from sqlalchemy import create_engine
engine = create_engine('sqlite:///:memory:', echo=True)
2. 连接数据库
conn = engine.connect()
3. 元数据
from sqlalchemy import MetaData metadata = MetaData(engine)
4. 定义表
from sqlalchemy import Table, Column, Integer, String, ForeignKey, Sequence
users = Table('users', metadata,
Column('id', Integer, Sequence('user_id_seq'), primary_key=True),
Column('name', String),
Column('fullname', String),
) addresses = Table('addresses', metadata,
Column('id', Integer, primary_key=True),
Column('user_id', None, ForeignKey('users.id')),
Column('email_address', String, nullable=False)
)
5. 创建表
# metadata.drop_all()
metadata.create_all()
6. 插入
# 方式一
ins = users.insert().values(name='jack', fullname='Jack Jones')
conn.execute(ins) # 方式二
conn.execute(users.insert(), id=2, name='wendy', fullname='Wendy Williams') # 方式三
conn.execute(addresses.insert(), [
{'user_id': 1, 'email_address' : 'jack@yahoo.com'},
{'user_id': 1, 'email_address' : 'jack@msn.com'},
{'user_id': 2, 'email_address' : 'www@www.org'},
{'user_id': 2, 'email_address' : 'wendy@aol.com'},
])
7. 查询
from sqlalchemy.sql import select
for row in conn.execute(select([users])):
print("name:", row[users.c.name], "; fullname:", row[users.c.fullname]) for row in conn.execute(select([users, addresses])):
print(row) for row in conn.execute(select([users, addresses]).where(users.c.id == addresses.c.user_id)):
print(row) from sqlalchemy.sql import and_, or_, not_
s = select([(users.c.fullname +
", " + addresses.c.email_address).
label('title')]).\
where(
and_(
users.c.id == addresses.c.user_id,
users.c.name.between('m', 'z'),
or_(
addresses.c.email_address.like('%@aol.com'),
addresses.c.email_address.like('%@msn.com')
)
)
)
conn.execute(s).fetchall()
8. 完整代码
# 绑定数据库
from sqlalchemy import create_engine
engine = create_engine('sqlite:///:memory:', echo=True) # 连接数据库
conn = engine.connect() # 元数据
from sqlalchemy import MetaData
metadata = MetaData(engine) # 定义表
from sqlalchemy import Table, Column, Integer, String, ForeignKey, Sequence
users = Table('users', metadata,
Column('id', Integer, Sequence('user_id_seq'), primary_key=True),
Column('name', String),
Column('fullname', String),
) addresses = Table('addresses', metadata,
Column('id', Integer, primary_key=True),
Column('user_id', None, ForeignKey('users.id')),
Column('email_address', String, nullable=False)
) # 创建表
# metadata.drop_all()
metadata.create_all() # 插入
# 方式一
ins = users.insert().values(name='jack', fullname='Jack Jones')
result = conn.execute(ins)
# 方式二
conn.execute(users.insert(), id=2, name='wendy', fullname='Wendy Williams')
# 方式三
conn.execute(addresses.insert(), [
{'user_id': 1, 'email_address' : 'jack@yahoo.com'},
{'user_id': 1, 'email_address' : 'jack@msn.com'},
{'user_id': 2, 'email_address' : 'www@www.org'},
{'user_id': 2, 'email_address' : 'wendy@aol.com'},
]) # 查询
from sqlalchemy.sql import select
for row in conn.execute(select([users])):
print("name:", row[users.c.name], "; fullname:", row[users.c.fullname]) for row in conn.execute(select([users, addresses])):
print(row) for row in conn.execute(select([users, addresses]).where(users.c.id == addresses.c.user_id)):
print(row) from sqlalchemy.sql import and_, or_, not_
s = select([(users.c.fullname +
", " + addresses.c.email_address).
label('title')]).\
where(
and_(
users.c.id == addresses.c.user_id,
users.c.name.between('m', 'z'),
or_(
addresses.c.email_address.like('%@aol.com'),
addresses.c.email_address.like('%@msn.com')
)
)
)
conn.execute(s).fetchall()