Vars()很棒，但不适用于对象的嵌套对象

将对象的嵌套对象转换为dict:

def to_dict(self):
    return json.loads(json.dumps(self, default=lambda o: o.__dict__))

内置的dir会给你所有对象的属性，包括特殊的方法，如__str__， __dict__和一大堆你可能不想要的其他方法。但是你可以这样做:

>>> class Foo(object):
...     bar = 'hello'
...     baz = 'world'
...
>>> f = Foo()
>>> [name for name in dir(f) if not name.startswith('__')]
[ 'bar', 'baz' ]
>>> dict((name, getattr(f, name)) for name in dir(f) if not name.startswith('__')) 
{ 'bar': 'hello', 'baz': 'world' }

所以可以扩展它，只返回数据属性，而不返回方法，通过定义你的props函数:

import inspect

def props(obj):
    pr = {}
    for name in dir(obj):
        value = getattr(obj, name)
        if not name.startswith('__') and not inspect.ismethod(value):
            pr[name] = value
    return pr

在2021年，对于嵌套对象/dicts/json使用pydantic BaseModel -将嵌套dicts和嵌套json对象转换为python对象和json，反之亦然:

https://pydantic-docs.helpmanual.io/usage/models/

>>> class Foo(BaseModel):
...     count: int
...     size: float = None
... 
>>> 
>>> class Bar(BaseModel):
...     apple = 'x'
...     banana = 'y'
... 
>>> 
>>> class Spam(BaseModel):
...     foo: Foo
...     bars: List[Bar]
... 
>>> 
>>> m = Spam(foo={'count': 4}, bars=[{'apple': 'x1'}, {'apple': 'x2'}])

对象to dict

>>> print(m.dict())
{'foo': {'count': 4, 'size': None}, 'bars': [{'apple': 'x1', 'banana': 'y'}, {'apple': 'x2', 'banana': 'y'}]}

对象转换为JSON

>>> print(m.json())
{"foo": {"count": 4, "size": null}, "bars": [{"apple": "x1", "banana": "y"}, {"apple": "x2", "banana": "y"}]}

反对的词典

>>> spam = Spam.parse_obj({'foo': {'count': 4, 'size': None}, 'bars': [{'apple': 'x1', 'banana': 'y'}, {'apple': 'x2', 'banana': 'y2'}]})
>>> spam
Spam(foo=Foo(count=4, size=None), bars=[Bar(apple='x1', banana='y'), Bar(apple='x2', banana='y2')])

JSON到对象

>>> spam = Spam.parse_raw('{"foo": {"count": 4, "size": null}, "bars": [{"apple": "x1", "banana": "y"}, {"apple": "x2", "banana": "y"}]}')
>>> spam
Spam(foo=Foo(count=4, size=None), bars=[Bar(apple='x1', banana='y'), Bar(apple='x2', banana='y')])

如果你想列出部分属性，重写__dict__:

def __dict__(self):
    d = {
    'attr_1' : self.attr_1,
    ...
    }
    return d

# Call __dict__
d = instance.__dict__()

如果你的实例得到一些大的块数据，并且你想把d推到Redis消息队列中，这很有帮助。

Try:

from pprint import pformat
a_dict = eval(pformat(an_obj))

PYTHON 3:

class DateTimeDecoder(json.JSONDecoder):

   def __init__(self, *args, **kargs):
        JSONDecoder.__init__(self, object_hook=self.dict_to_object,
                         *args, **kargs)

   def dict_to_object(self, d):
       if '__type__' not in d:
          return d

       type = d.pop('__type__')
       try:
          dateobj = datetime(**d)
          return dateobj
       except:
          d['__type__'] = type
          return d

def json_default_format(value):
    try:
        if isinstance(value, datetime):
            return {
                '__type__': 'datetime',
                'year': value.year,
                'month': value.month,
                'day': value.day,
                'hour': value.hour,
                'minute': value.minute,
                'second': value.second,
                'microsecond': value.microsecond,
            }
        if isinstance(value, decimal.Decimal):
            return float(value)
        if isinstance(value, Enum):
            return value.name
        else:
            return vars(value)
    except Exception as e:
        raise ValueError

现在你可以在你自己的类中使用上面的代码:

class Foo():
  def toJSON(self):
        return json.loads(
            json.dumps(self, sort_keys=True, indent=4, separators=(',', ': '), default=json_default_format), cls=DateTimeDecoder)


Foo().toJSON()