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

当前回答

def to_dict(row):
    return {column.name: getattr(row, row.__mapper__.get_property_by_column(column).key) for column in row.__table__.columns}


for u in session.query(User).all():
    print(to_dict(u))

这个函数可能会有帮助。 当属性名与列名不同时,我找不到更好的解决方案来解决问题。

其他回答

有了这段代码,您还可以添加到您的查询“过滤器”或“连接”,这工作!

query = session.query(User)
def query_to_dict(query):
        def _create_dict(r):
            return {c.get('name'): getattr(r, c.get('name')) for c in query.column_descriptions}

    return [_create_dict(r) for r in query]

我们可以在dict中得到一个对象列表:

def queryset_to_dict(query_result):
   query_columns = query_result[0].keys()
   res = [list(ele) for ele in query_result]
   dict_list = [dict(zip(query_columns, l)) for l in res]
   return dict_list

query_result = db.session.query(LanguageMaster).all()
dictvalue=queryset_to_dict(query_result)

@zzzeek在评论中写道:

注意,这是现代版本的正确答案 SQLAlchemy,假设“row”是核心行对象,而不是orm映射对象 实例。

for row in resultproxy:
    row_as_dict = row._mapping  # SQLAlchemy 1.4 and greater
    # row_as_dict = dict(row)  # SQLAlchemy 1.3 and earlier

行背景。_mapping, SQLAlchemy 1.4新增:https://docs.sqlalchemy.org/en/stable/core/connections.html#sqlalchemy.engine.Row._mapping

如果你的模型表列不需要mysql列。

例如:

class People:
    id: int = Column(name='id', type_=Integer, primary_key=True)
    createdTime: datetime = Column(name='create_time', type_=TIMESTAMP,
                               nullable=False,
                               server_default=text("CURRENT_TIMESTAMP"),
                               default=func.now())
    modifiedTime: datetime = Column(name='modify_time', type_=TIMESTAMP,
                                server_default=text("CURRENT_TIMESTAMP"),
                                default=func.now())

需要使用:

 from sqlalchemy.orm import class_mapper 
 def asDict(self):
        return {x.key: getattr(self, x.key, None) for x in
            class_mapper(Application).iterate_properties}

如果你使用这种方式,你可以得到modify_time和create_time都是None

{'id': 1, 'create_time': None, 'modify_time': None}


    def to_dict(self):
        return {c.name: getattr(self, c.name, None)
         for c in self.__table__.columns}

因为类属性名称不等于列存储在mysql

Elixir是这样做的。这个解决方案的价值在于,它允许递归地包括关系的字典表示。

def to_dict(self, deep={}, exclude=[]):
    """Generate a JSON-style nested dict/list structure from an object."""
    col_prop_names = [p.key for p in self.mapper.iterate_properties \
                                  if isinstance(p, ColumnProperty)]
    data = dict([(name, getattr(self, name))
                 for name in col_prop_names if name not in exclude])
    for rname, rdeep in deep.iteritems():
        dbdata = getattr(self, rname)
        #FIXME: use attribute names (ie coltoprop) instead of column names
        fks = self.mapper.get_property(rname).remote_side
        exclude = [c.name for c in fks]
        if dbdata is None:
            data[rname] = None
        elif isinstance(dbdata, list):
            data[rname] = [o.to_dict(rdeep, exclude) for o in dbdata]
        else:
            data[rname] = dbdata.to_dict(rdeep, exclude)
    return data