虽然我从来都不需要这样做,但我突然意识到用Python创建一个不可变对象可能有点棘手。你不能只是覆盖__setattr__,因为这样你甚至不能在__init__中设置属性。子类化一个元组是一个有效的技巧:

class Immutable(tuple):
    
    def __new__(cls, a, b):
        return tuple.__new__(cls, (a, b))

    @property
    def a(self):
        return self[0]
        
    @property
    def b(self):
        return self[1]

    def __str__(self):
        return "<Immutable {0}, {1}>".format(self.a, self.b)
    
    def __setattr__(self, *ignored):
        raise NotImplementedError

    def __delattr__(self, *ignored):
        raise NotImplementedError

但是你可以通过self[0]和self[1]访问a和b变量,这很烦人。

这在Pure Python中可行吗?如果不是,我该如何用C扩展来做呢?

(只能在python3中工作的答案是可以接受的)。

更新:

从Python 3.7开始,要使用的方法是使用@dataclass装饰器,参见最新接受的答案。


当前回答

第三方attr模块提供了此功能。

编辑:python 3.7已经通过@dataclass在stdlib中采用了这个想法。

$ pip install attrs
$ python
>>> @attr.s(frozen=True)
... class C(object):
...     x = attr.ib()
>>> i = C(1)
>>> i.x = 2
Traceback (most recent call last):
   ...
attr.exceptions.FrozenInstanceError: can't set attribute

Attr通过覆盖__setattr__来实现冻结类,根据文档,Attr在每次实例化时都有轻微的性能影响。

如果您习惯使用类作为数据类型,attr可能特别有用,因为它为您处理样板文件(但没有任何魔力)。特别地,它为你编写了9个dunder (__X__)方法(除非你关闭其中任何一个),包括repr, init, hash和所有比较函数。

Attr还为__slots__提供了一个帮助器。

其他回答

另一个想法是完全不允许__setattr__而使用object。构造函数中的__setattr__:

class Point(object):
    def __init__(self, x, y):
        object.__setattr__(self, "x", x)
        object.__setattr__(self, "y", y)
    def __setattr__(self, *args):
        raise TypeError
    def __delattr__(self, *args):
        raise TypeError

当然你可以用object。__setattr__(p, "x", 3)来修改一个Point实例p,但您的原始实现遭受同样的问题(尝试tuple。__setattr__(i, "x", 42)在一个不可变实例)。

您可以在原始实现中应用相同的技巧:去掉__getitem__(),并在属性函数中使用tuple.__getitem__()。

我通过重写__setattr__创建了不可变类,并且如果调用者是__init__,则允许该集合:

import inspect
class Immutable(object):
    def __setattr__(self, name, value):
        if inspect.stack()[2][3] != "__init__":
            raise Exception("Can't mutate an Immutable: self.%s = %r" % (name, value))
        object.__setattr__(self, name, value)

这还不够,因为它允许任何人的___init__来改变对象,但你懂的。

我使用了与Alex相同的想法:一个元类和一个“init marker”,但结合重写__setattr__:

>>> from abc import ABCMeta
>>> _INIT_MARKER = '_@_in_init_@_'
>>> class _ImmutableMeta(ABCMeta):
... 
...     """Meta class to construct Immutable."""
... 
...     def __call__(cls, *args, **kwds):
...         obj = cls.__new__(cls, *args, **kwds)
...         object.__setattr__(obj, _INIT_MARKER, True)
...         cls.__init__(obj, *args, **kwds)
...         object.__delattr__(obj, _INIT_MARKER)
...         return obj
...
>>> def _setattr(self, name, value):
...     if hasattr(self, _INIT_MARKER):
...         object.__setattr__(self, name, value)
...     else:
...         raise AttributeError("Instance of '%s' is immutable."
...                              % self.__class__.__name__)
...
>>> def _delattr(self, name):
...     raise AttributeError("Instance of '%s' is immutable."
...                          % self.__class__.__name__)
...
>>> _im_dict = {
...     '__doc__': "Mix-in class for immutable objects.",
...     '__copy__': lambda self: self,   # self is immutable, so just return it
...     '__setattr__': _setattr,
...     '__delattr__': _delattr}
...
>>> Immutable = _ImmutableMeta('Immutable', (), _im_dict)

注意:我直接调用元类,以使它在Python 2中都能工作。X和3.x。

>>> class T1(Immutable):
... 
...     def __init__(self, x=1, y=2):
...         self.x = x
...         self.y = y
...
>>> t1 = T1(y=8)
>>> t1.x, t1.y
(1, 8)
>>> t1.x = 7
AttributeError: Instance of 'T1' is immutable.

它也适用于插槽…:

>>> class T2(Immutable):
... 
...     __slots__ = 's1', 's2'
... 
...     def __init__(self, s1, s2):
...         self.s1 = s1
...         self.s2 = s2
...
>>> t2 = T2('abc', 'xyz')
>>> t2.s1, t2.s2
('abc', 'xyz')
>>> t2.s1 += 'd'
AttributeError: Instance of 'T2' is immutable.

... 和多重继承:

>>> class T3(T1, T2):
... 
...     def __init__(self, x, y, s1, s2):
...         T1.__init__(self, x, y)
...         T2.__init__(self, s1, s2)
...
>>> t3 = T3(12, 4, 'a', 'b')
>>> t3.x, t3.y, t3.s1, t3.s2
(12, 4, 'a', 'b')
>>> t3.y -= 3
AttributeError: Instance of 'T3' is immutable.

但是请注意,可变属性仍然是可变的:

>>> t3 = T3(12, [4, 7], 'a', 'b')
>>> t3.y.append(5)
>>> t3.y
[4, 7, 5]

下面的基本解决方案针对以下场景:

__init__()可以像往常一样访问属性。 在此之后,对象仅冻结属性更改:

其思想是覆盖__setattr__方法,并在每次对象冻结状态改变时替换其实现。

因此,我们需要一些方法(_freeze)来存储这两个实现,并在请求时在它们之间切换。

这个机制可以在用户类内部实现,也可以从一个特殊的freeze类继承,如下所示:

class Freezer:
    def _freeze(self, do_freeze=True):
        def raise_sa(*args):            
            raise AttributeError("Attributes are frozen and can not be changed!")
        super().__setattr__('_active_setattr', (super().__setattr__, raise_sa)[do_freeze])

    def __setattr__(self, key, value):        
        return self._active_setattr(key, value)

class A(Freezer):    
    def __init__(self):
        self._freeze(False)
        self.x = 10
        self._freeze()

..如何在C中“正确地”做这件事?

你可以使用Cython为Python创建一个扩展类型:

cdef class Immutable:
    cdef readonly object a, b
    cdef object __weakref__ # enable weak referencing support

    def __init__(self, a, b):
        self.a, self.b = a, b

它既适用于Python 2。X和3。

测试

# compile on-the-fly
import pyximport; pyximport.install() # $ pip install cython
from immutable import Immutable

o = Immutable(1, 2)
assert o.a == 1, str(o.a)
assert o.b == 2

try: o.a = 3
except AttributeError:
    pass
else:
    assert 0, 'attribute must be readonly'

try: o[1]
except TypeError:
    pass
else:
    assert 0, 'indexing must not be supported'

try: o.c = 1
except AttributeError:
    pass
else:
    assert 0, 'no new attributes are allowed'

o = Immutable('a', [])
assert o.a == 'a'
assert o.b == []

o.b.append(3) # attribute may contain mutable object
assert o.b == [3]

try: o.c
except AttributeError:
    pass
else:
    assert 0, 'no c attribute'

o = Immutable(b=3,a=1)
assert o.a == 1 and o.b == 3

try: del o.b
except AttributeError:
    pass
else:
    assert 0, "can't delete attribute"

d = dict(b=3, a=1)
o = Immutable(**d)
assert o.a == d['a'] and o.b == d['b']

o = Immutable(1,b=3)
assert o.a == 1 and o.b == 3

try: object.__setattr__(o, 'a', 1)
except AttributeError:
    pass
else:
    assert 0, 'attributes are readonly'

try: object.__setattr__(o, 'c', 1)
except AttributeError:
    pass
else:
    assert 0, 'no new attributes'

try: Immutable(1,c=3)
except TypeError:
    pass
else:
    assert 0, 'accept only a,b keywords'

for kwd in [dict(a=1), dict(b=2)]:
    try: Immutable(**kwd)
    except TypeError:
        pass
    else:
        assert 0, 'Immutable requires exactly 2 arguments'

如果你不介意索引支持,那么@Sven Marnach建议的collections.namedtuple是更可取的:

Immutable = collections.namedtuple("Immutable", "a b")