API例子
import sqlalchemyfrom sqlalchemy import create_enginefrom sqlalchemy.ext.declarative import declarative_basefrom sqlalchemy import Column, Integer, Stringfrom sqlalchemy.orm import sessionmakerprint(sqlalchemy.__version__)# # examples of connection http://docs.sqlalchemy.org/en/rel_1_0/core/engines.html#sqlalchemy.create_engineengine = 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 " " % (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_usersession.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 " " % 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
import sqlalchemyprint(sqlalchemy.__version__)from sqlalchemy import create_enginefrom sqlalchemy import Table, Column, Integer, String, MetaData, ForeignKeyengine = 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([users])# result = conn.execute(s)# for row in result:# print(row)# s = select([users, addresses]).where(users.c.id == addresses.c.user_id)# for row in conn.execute(s):# print rowfrom sqlalchemy.sql import texts = 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。
在Python 3.0中已经不支持反引号了，所以还是坚持用repr()函数吧
参考文章：Python repr() 或str() 函数, 反引号