Python的ORM框架SQLAlchemy
API例子1
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import sqlalchemy
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, Integer, String
from sqlalchemy.orm import sessionmaker
print(sqlalchemy.__version__)
# # examples of connection http://docs.sqlalchemy.org/en/rel_1_0/core/engines.html#sqlalchemy.create_engine
engine = create_engine('sqlite:///foo.db', echo=True)
Base = declarative_base()
class User(Base):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
name = Column(String)
fullname = Column(String)
password = Column(String)
def __repr__(self):
return "<User(name='%s', fullname='%s', password='%s')>" % (self.name, self.fullname, self.password)
Base.metadata.create_all(engine)
ed_user = User(name='ed', fullname='Ed Jones', password='edspassword')
print(ed_user)
Session = sessionmaker(bind=engine)
session = Session()
session.add(ed_user)
our_user = session.query(User).filter_by(name='ed').first()
# SELECT * FROM users WHERE name="ed" LIMIT 1;
print our_user
session.add_all([
User(name='wendy', fullname='Wendy Williams', password='foobar'),
User(name='mary', fullname='Mary Contrary', password='xxg527'),
User(name='fred', fullname='Fred Flinstone', password='blah')])
session.commit()
print(session.query(User).filter_by(name='ed').first())
print(session.query(User).all())
for row in session.query(User).order_by(User.id):
print(row)
for row in session.query(User).filter(User.name.in_(['ed', 'wendy', 'jack'])):
print(row)
# for row in session.query(User).filter(~User.name.in_(['ed', 'wendy', 'jack'])):
# print(row)
# print(session.query(User).filter(User.name == 'ed').count())
#
# from sqlalchemy import and_, or_
# for row in session.query(User).filter(and_(User.name == 'ed', User.fullname == 'Ed Jones')):
# print(row)
# for row in session.query(User).filter(or_(User.name == 'ed', User.name == 'wendy')):
# print(row)
#
# from sqlalchemy import ForeignKey
# from sqlalchemy.orm import relationship, backref
#
# class Address(Base):
# __tablename__ = 'addresses'
# id = Column(Integer, primary_key=True)
# email_address = Column(String, nullable=False)
# user_id = Column(Integer, ForeignKey('users.id'))
#
# user = relationship("User", backref=backref('addresses', order_by=id))
#
# def __repr__(self):
# return "<Address(email_address='%s')>" % self.email_address
# # Base.metadata.create_all(engine)
# #
# jack = User(name='jack', fullname='Jack Bean', password='gjffdd')
# jack.addresses = [
# Address(email_address='jack@google.com'),
# Address(email_address='j25@yahoo.com')]
# session.add(jack)
# session.commit()
#
# for u, a in session.query(User, Address).\
# filter(User.id==Address.user_id).\
# filter(Address.email_address=='jack@google.com').\
# all():
# print u, a
SQLAlchemy Core 相当于底层实现，很少使用
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import sqlalchemy
print(sqlalchemy.__version__)
from sqlalchemy import create_engine
from sqlalchemy import Table, Column, Integer, String, MetaData, ForeignKey
engine = create_engine('sqlite:///foo.db', echo=True)
metadata = MetaData()
users = Table('users', metadata,
Column('id', Integer, 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)
)
metadata.create_all(engine)
conn = engine.connect()
# conn.execute(users.insert(), [dict(name='jack', fullname='Jack Jones'),
# dict(name='wendy', fullname='Wendy Williams')])
# 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'},
# ])
from sqlalchemy.sql import select
# s = select()
# result = conn.execute(s)
# for row in result:
# print(row)
# s = select().where(users.c.id == addresses.c.user_id)
# for row in conn.execute(s):
# print row
from sqlalchemy.sql import text
s = text(
"SELECT users.fullname || ', ' || addresses.email_address AS title "
"FROM users, addresses "
"WHERE users.id = addresses.user_id "
"AND users.name BETWEEN :x AND :y "
"AND (addresses.email_address LIKE :e1 "
"OR addresses.email_address LIKE :e2)")
print(conn.execute(s, x='m', y='z', e1='%@aol.com', e2='%@msn.com').fetchall())
__repr__是python类的专用方法:你可以通过定义类的__repr__方法来控制你的对象在被repr函数调用的时候返回的内容。
Python 有办法将任意值转为字符串：将它传入repr() 或str() 函数。函数str() 用于将值转化为适于人阅读的形式，而repr() 转化为供解释器读取的形式（如果没有等价的语法，则会发生SyntaxError 异常） 某对象没有适于人阅读的解释形式的话， str() 会返回与repr()等同的值。很多类型，诸如数值或链表、字典这样的结构，针对各函数都有着统一的解读方式。字符串和浮点数，有着独特的解读方式。
repr函数用来取得对象的规范字符串表示。反引号（也称转换符）可以完成相同的功能。注意，在大多数时候有eval(repr(object)) == object。
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