对Jackson的YAML序列化使用标量值的文字样式(Use literal style on scalar values for YAML serialization with Jackson)

 是的，一切都是对象。 但是，一切都是对象并不意味着一切都需要任意属性。 
 
 Python中的整数是对象，并且具有属性和方法（它们只是可调用的属性）： 
 
>>> x = 6
>>> x.real
6
>>> x.imag
0
>>> x.bit_length()
3
 
 要支持任意属性，对象需要具有__dict__映射。 整数没有这样的映射： 
 
>>> x.__dict__
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'int' object has no attribute '__dict__'
 
 其他对象与函数一样，例如： 
 
>>> def foo(): pass
...
>>> foo.__dict__
{}
>>> foo.bar = 'baz'
 
 但__dict__映射需要付出代价：这些对象的内存占用量更大。 由于Python使用了很多整数，因此为了节省内存而不给它们__dict__映射是有意义的。 无论如何，你很少需要给它们额外的属性。 
 
 您可以通过为类提供__slots__类变量来定义自己的类，这些类生成没有__dict__属性的实例; 这定义了实例支持的固定属性。 这可以让您从相同的内存节省中受益： 
 
>>> class Demo(object):
...     __slots__ = ('foo',)
...
>>> d = Demo()
>>> d.foo = 'bar'
>>> d.bar = 'foo'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'Demo' object has no attribute 'bar'
 
 反之亦然，如果你创建一个int的子类而不给你的子类一个__slots__变量，你可以向该子类添加任意属性： 
 
>>> class MyInt(int):
...     pass
...
>>> mi = MyInt(6)
>>> mi.foo = 'bar'

Yes, everything is an object. However, everything being an object does not mean that everything takes arbitrary attributes.
 
Integers in Python are objects, and have attributes and methods (which are just callable attributes):
 
>>> x = 6
>>> x.real
6
>>> x.imag
0
>>> x.bit_length()
3
 
To support arbitrary attributes, an object needs to have a __dict__ mapping. Integers don't have such a mapping:
 
>>> x.__dict__
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'int' object has no attribute '__dict__'
 
Other objects do, like functions, for example:
 
>>> def foo(): pass
...
>>> foo.__dict__
{}
>>> foo.bar = 'baz'
 
But a __dict__ mapping comes with a price: a larger memory footprint for such objects. Since Python uses a lot of integers, it makes sense to not give them a __dict__ mapping, to save memory. You very rarely would need to give them extra attributes anyway.
 
You can define your own classes that produce instances without a __dict__ attribute, by giving your class a __slots__ class variable; this defines the fixed attributes an instance supports. This lets you benefit from the same memory savings:
 
>>> class Demo(object):
...     __slots__ = ('foo',)
...
>>> d = Demo()
>>> d.foo = 'bar'
>>> d.bar = 'foo'
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: 'Demo' object has no attribute 'bar'
 
And vice-versa, if you create a subclass of int and not give your subclass a __slots__ variable, you can add arbitrary attributes to that subclass:
 
>>> class MyInt(int):
...     pass
...
>>> mi = MyInt(6)
>>> mi.foo = 'bar'