下面是一个解决方案，它允许您选择希望在输出中包含的关系。 注意:这是一个完整的重写，将dict/str作为一个参数，而不是一个列表。修复了一些东西..

def deep_dict(self, relations={}):
    """Output a dict of an SA object recursing as deep as you want.

    Takes one argument, relations which is a dictionary of relations we'd
    like to pull out. The relations dict items can be a single relation
    name or deeper relation names connected by sub dicts

    Example:
        Say we have a Person object with a family relationship
            person.deep_dict(relations={'family':None})
        Say the family object has homes as a relation then we can do
            person.deep_dict(relations={'family':{'homes':None}})
            OR
            person.deep_dict(relations={'family':'homes'})
        Say homes has a relation like rooms you can do
            person.deep_dict(relations={'family':{'homes':'rooms'}})
            and so on...
    """
    mydict =  dict((c, str(a)) for c, a in
                    self.__dict__.items() if c != '_sa_instance_state')
    if not relations:
        # just return ourselves
        return mydict

    # otherwise we need to go deeper
    if not isinstance(relations, dict) and not isinstance(relations, str):
        raise Exception("relations should be a dict, it is of type {}".format(type(relations)))

    # got here so check and handle if we were passed a dict
    if isinstance(relations, dict):
        # we were passed deeper info
        for left, right in relations.items():
            myrel = getattr(self, left)
            if isinstance(myrel, list):
                mydict[left] = [rel.deep_dict(relations=right) for rel in myrel]
            else:
                mydict[left] = myrel.deep_dict(relations=right)
    # if we get here check and handle if we were passed a string
    elif isinstance(relations, str):
        # passed a single item
        myrel = getattr(self, relations)
        left = relations
        if isinstance(myrel, list):
            mydict[left] = [rel.deep_dict(relations=None)
                                 for rel in myrel]
        else:
            mydict[left] = myrel.deep_dict(relations=None)

    return mydict

举个关于person/family/homes/rooms的例子…把它转换成json，你只需要

json.dumps(person.deep_dict(relations={'family':{'homes':'rooms'}}))

我建议用棉花糖。它允许您创建序列化器来表示支持关系和嵌套对象的模型实例。

以下是他们文档中的一个删节的例子。以ORM模型为例，作者:

class Author(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    first = db.Column(db.String(80))
    last = db.Column(db.String(80))

该类的棉花糖模式是这样构造的:

class AuthorSchema(Schema):
    id = fields.Int(dump_only=True)
    first = fields.Str()
    last = fields.Str()
    formatted_name = fields.Method("format_name", dump_only=True)

    def format_name(self, author):
        return "{}, {}".format(author.last, author.first)

.．.并像这样使用:

author_schema = AuthorSchema()
author_schema.dump(Author.query.first())

.．.会产生这样的输出:

{
        "first": "Tim",
        "formatted_name": "Peters, Tim",
        "id": 1,
        "last": "Peters"
}

看看他们完整的Flask-SQLAlchemy示例。

一个名为marshmlow - SQLAlchemy的库专门集成了SQLAlchemy和marshmallow。在这个库中，上面描述的Author模型的模式如下所示:

class AuthorSchema(ModelSchema):
    class Meta:
        model = Author

该集成允许从SQLAlchemy Column类型推断字段类型。

marshmallow-sqlalchemy这里。

当使用sqlalchemy连接到db I时，这是一个高度可配置的简单解决方案。使用熊猫。

import pandas as pd
import sqlalchemy

#sqlalchemy engine configuration
engine = sqlalchemy.create_engine....

def my_function():
  #read in from sql directly into a pandas dataframe
  #check the pandas documentation for additional config options
  sql_DF = pd.read_sql_table("table_name", con=engine)

  # "orient" is optional here but allows you to specify the json formatting you require
  sql_json = sql_DF.to_json(orient="index")

  return sql_json

这并不是那么简单。我写了一些代码来做这件事。我还在开发中，它使用了MochiKit框架。它基本上使用代理和注册的JSON转换器在Python和Javascript之间转换复合对象。

数据库对象的浏览器端是db.js 它需要proxy.js中的基本Python代理源代码。

在Python方面，有基本代理模块。 最后是webserver.py中的SqlAlchemy对象编码器。 它还依赖于models.py文件中的元数据提取器。

在SQLAlchemy中使用内置序列化器:

from sqlalchemy.ext.serializer import loads, dumps
obj = MyAlchemyObject()
# serialize object
serialized_obj = dumps(obj)

# deserialize object
obj = loads(serialized_obj)

如果在会话之间传输对象，请记住使用session.expunge(obj)将对象从当前会话中分离出来。 要再次附加它，只需执行session.add(obj)。

Flask-JsonTools包为您的模型提供了JsonSerializableBase基类的实现。

用法:

from sqlalchemy.ext.declarative import declarative_base
from flask.ext.jsontools import JsonSerializableBase

Base = declarative_base(cls=(JsonSerializableBase,))

class User(Base):
    #...

现在User模型可以神奇地序列化了。

如果你的框架不是Flask，你可以抓取代码