是否有一种简单的方法来遍历列名和值对?
我的SQLAlchemy版本是0.5.6
下面是我尝试使用dict(row)的示例代码:
import sqlalchemy
from sqlalchemy import *
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
print "sqlalchemy version:",sqlalchemy.__version__
engine = create_engine('sqlite:///:memory:', echo=False)
metadata = MetaData()
users_table = Table('users', metadata,
Column('id', Integer, primary_key=True),
Column('name', String),
)
metadata.create_all(engine)
class User(declarative_base()):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
name = Column(String)
def __init__(self, name):
self.name = name
Session = sessionmaker(bind=engine)
session = Session()
user1 = User("anurag")
session.add(user1)
session.commit()
# uncommenting next line throws exception 'TypeError: 'User' object is not iterable'
#print dict(user1)
# this one also throws 'TypeError: 'User' object is not iterable'
for u in session.query(User).all():
print dict(u)
在我的系统输出上运行这段代码:
Traceback (most recent call last):
File "untitled-1.py", line 37, in <module>
print dict(u)
TypeError: 'User' object is not iterable
如OP所述，调用dict初始化器会引发一个异常，消息为“User”对象不可迭代。所以真正的问题是如何使一个SQLAlchemy模型可迭代?
We'll have to implement the special methods __iter__ and __next__, but if we inherit directly from the declarative_base model, we would still run into the undesirable "_sa_instance_state" key. What's worse, is we would have to loop through __dict__.keys() for every call to __next__ because the keys() method returns a View -- an iterable that is not indexed. This would increase the time complexity by a factor of N, where N is the number of keys in __dict__. Generating the dict would cost O(N^2). We can do better.
我们可以实现自己的基类，它实现所需的特殊方法，并存储可以通过索引访问的列名列表，从而降低生成O(N)字典的时间复杂性。这有一个额外的好处，我们可以定义一次逻辑，并在任何时候从基类继承，我们希望我们的模型类是可迭代的。
class IterableBase(declarative_base()):
__abstract__ = True
def _init_keys(self):
self._keys = [c.name for c in self.__table__.columns]
self._dict = {c.name: getattr(self, c.name) for c in self.__table__.columns}
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._init_keys()
def __setattr__(self, name, value):
super().__setattr__(name, value)
if name not in ('_dict', '_keys', '_n') and '_dict' in self.__dict__:
self._dict[name] = value
def __iter__(self):
self._n = 0
return self
def __next__(self):
if self._n >= len(self._keys):
raise StopIteration
self._n += 1
key = self._keys[self._n-1]
return (key, self._dict[key])
现在User类可以直接从IterableBase类继承。
class User(IterableBase):
__tablename__ = 'users'
id = Column(Integer, primary_key=True)
name = Column(String)
您可以确认，以User实例作为参数调用dict函数将返回所需的字典，没有"_sa_instance_state"。你可能已经注意到在IterableBase类中声明的__setattr__方法。这确保在初始化后属性发生变化或设置时更新_dict。
def main():
user1 = User('Bob')
print(dict(user1))
# outputs {'id': None, 'name': 'Bob'}
user1.id = 42
print(dict(user1))
# outputs {'id': 42, 'name': 'Bob'}
if __name__ == '__main__':
main()
在python 3.8+中，我们可以使用数据类和它附带的asdict方法来实现这一点:
from dataclasses import dataclass, asdict
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
from sqlalchemy import Column, String, Integer, create_engine
Base = declarative_base()
engine = create_engine('sqlite:///:memory:', echo=False)
@dataclass
class User(Base):
__tablename__ = 'users'
id: int = Column(Integer, primary_key=True)
name: str = Column(String)
email = Column(String)
def __init__(self, name):
self.name = name
self.email = 'hello@example.com'
Base.metadata.create_all(engine)
SessionMaker = sessionmaker(bind=engine)
session = SessionMaker()
user1 = User("anurag")
session.add(user1)
session.commit()
query_result = session.query(User).one() # type: User
print(f'{query_result.id=:}, {query_result.name=:}, {query_result.email=:}')
# query_result.id=1, query_result.name=anurag, query_result.email=hello@example.com
query_result_dict = asdict(query_result)
print(query_result_dict)
# {'id': 1, 'name': 'anurag'}
关键是使用@dataclass装饰器，并用它的类型(name: str = column (String)行的:str部分)注释每一列。
还要注意，由于电子邮件没有注释，因此它不包括在query_result_dict中。
