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()
