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]

这种方式不停止对象。__setattr__从工作，但我仍然发现它有用:

class A(object):

    def __new__(cls, children, *args, **kwargs):
        self = super(A, cls).__new__(cls)
        self._frozen = False  # allow mutation from here to end of  __init__
        # other stuff you need to do in __new__ goes here
        return self

    def __init__(self, *args, **kwargs):
        super(A, self).__init__()
        self._frozen = True  # prevent future mutation

    def __setattr__(self, name, value):
        # need to special case setting _frozen.
        if name != '_frozen' and self._frozen:
            raise TypeError('Instances are immutable.')
        else:
            super(A, self).__setattr__(name, value)

    def __delattr__(self, name):
        if self._frozen:
            raise TypeError('Instances are immutable.')
        else:
            super(A, self).__delattr__(name)

你可能需要根据用例重写更多的东西(比如__setitem__)。

从Python 3.7开始，你可以在你的类中使用@dataclass装饰器，它将像结构体一样是不可变的!不过，它可能会也可能不会将__hash__()方法添加到类中。引用:

hash() is used by built-in hash(), and when objects are added to hashed collections such as dictionaries and sets. Having a hash() implies that instances of the class are immutable. Mutability is a complicated property that depends on the programmer’s intent, the existence and behavior of eq(), and the values of the eq and frozen flags in the dataclass() decorator. By default, dataclass() will not implicitly add a hash() method unless it is safe to do so. Neither will it add or change an existing explicitly defined hash() method. Setting the class attribute hash = None has a specific meaning to Python, as described in the hash() documentation. If hash() is not explicit defined, or if it is set to None, then dataclass() may add an implicit hash() method. Although not recommended, you can force dataclass() to create a hash() method with unsafe_hash=True. This might be the case if your class is logically immutable but can nonetheless be mutated. This is a specialized use case and should be considered carefully.

下面是上面链接的文档中的例子:

@dataclass
class InventoryItem:
    '''Class for keeping track of an item in inventory.'''
    name: str
    unit_price: float
    quantity_on_hand: int = 0

    def total_cost(self) -> float:
        return self.unit_price * self.quantity_on_hand

我不认为这是完全可能的，除非使用一个元组或namedtuple。无论如何，如果你重写了__setattr__()，用户总是可以通过直接调用object.__setattr__()来绕过它。任何依赖__setattr__的解决方案都保证不起作用。

以下是不使用某种元组可以得到的最接近的结果:

class Immutable:
    __slots__ = ['a', 'b']
    def __init__(self, a, b):
        object.__setattr__(self, 'a', a)
        object.__setattr__(self, 'b', b)
    def __setattr__(self, *ignored):
        raise NotImplementedError
    __delattr__ = __setattr__

但如果你足够努力，它就会破裂:

>>> t = Immutable(1, 2)
>>> t.a
1
>>> object.__setattr__(t, 'a', 2)
>>> t.a
2

但Sven对namedtuple的使用确实是不可变的。

更新

由于这个问题已经更新为询问如何在C中正确地做这件事，下面是我关于如何在Cython中正确地做这件事的答案:

第一个immutable.pyx:

cdef class Immutable:
    cdef object _a, _b

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

    property a:
        def __get__(self):
            return self._a

    property b:
        def __get__(self):
            return self._b

    def __repr__(self):
        return "<Immutable {0}, {1}>".format(self.a, self.b)

和一个setup.py来编译它(使用命令setup.py build_ext——inplace:

from distutils.core import setup
from distutils.extension import Extension
from Cython.Distutils import build_ext

ext_modules = [Extension("immutable", ["immutable.pyx"])]

setup(
  name = 'Immutable object',
  cmdclass = {'build_ext': build_ext},
  ext_modules = ext_modules
)

然后试试吧:

>>> from immutable import Immutable
>>> p = Immutable(2, 3)
>>> p
<Immutable 2, 3>
>>> p.a = 1
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: attribute 'a' of 'immutable.Immutable' objects is not writable
>>> object.__setattr__(p, 'a', 1)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
AttributeError: attribute 'a' of 'immutable.Immutable' objects is not writable
>>> p.a, p.b
(2, 3)
>>>      

继承自以下Immutable类的类，在它们的__init__方法执行完成后，它们的实例也是不可变的。正如其他人指出的那样，因为它是纯python，所以没有什么可以阻止某人使用来自基对象和类型的特殊方法的突变，但这足以阻止任何人意外地突变类/实例。

它通过用元类劫持类创建过程来工作。

"""Subclasses of class Immutable are immutable after their __init__ has run, in
the sense that all special methods with mutation semantics (in-place operators,
setattr, etc.) are forbidden.

"""  

# Enumerate the mutating special methods
mutation_methods = set()
# Arithmetic methods with in-place operations
iarithmetic = '''add sub mul div mod divmod pow neg pos abs bool invert lshift
                 rshift and xor or floordiv truediv matmul'''.split()
for op in iarithmetic:
    mutation_methods.add('__i%s__' % op)
# Operations on instance components (attributes, items, slices)
for verb in ['set', 'del']:
    for component in '''attr item slice'''.split():
        mutation_methods.add('__%s%s__' % (verb, component))
# Operations on properties
mutation_methods.update(['__set__', '__delete__'])


def checked_call(_self, name, method, *args, **kwargs):
    """Calls special method method(*args, **kw) on self if mutable."""
    self = args[0] if isinstance(_self, object) else _self
    if not getattr(self, '__mutable__', True):
        # self told us it's immutable, so raise an error
        cname= (self if isinstance(self, type) else self.__class__).__name__
        raise TypeError('%s is immutable, %s disallowed' % (cname, name))
    return method(*args, **kwargs)


def method_wrapper(_self, name):
    "Wrap a special method to check for mutability."
    method = getattr(_self, name)
    def wrapper(*args, **kwargs):
        return checked_call(_self, name, method, *args, **kwargs)
    wrapper.__name__ = name
    wrapper.__doc__ = method.__doc__
    return wrapper


def wrap_mutating_methods(_self):
    "Place the wrapper methods on mutative special methods of _self"
    for name in mutation_methods:
        if hasattr(_self, name):
            method = method_wrapper(_self, name)
            type.__setattr__(_self, name, method)


def set_mutability(self, ismutable):
    "Set __mutable__ by using the unprotected __setattr__"
    b = _MetaImmutable if isinstance(self, type) else Immutable
    super(b, self).__setattr__('__mutable__', ismutable)


class _MetaImmutable(type):

    '''The metaclass of Immutable. Wraps __init__ methods via __call__.'''

    def __init__(cls, *args, **kwargs):
        # Make class mutable for wrapping special methods
        set_mutability(cls, True)
        wrap_mutating_methods(cls)
        # Disable mutability
        set_mutability(cls, False)

    def __call__(cls, *args, **kwargs):
        '''Make an immutable instance of cls'''
        self = cls.__new__(cls)
        # Make the instance mutable for initialization
        set_mutability(self, True)
        # Execute cls's custom initialization on this instance
        self.__init__(*args, **kwargs)
        # Disable mutability
        set_mutability(self, False)
        return self

    # Given a class T(metaclass=_MetaImmutable), mutative special methods which
    # already exist on _MetaImmutable (a basic type) cannot be over-ridden
    # programmatically during _MetaImmutable's instantiation of T, because the
    # first place python looks for a method on an object is on the object's
    # __class__, and T.__class__ is _MetaImmutable. The two extant special
    # methods on a basic type are __setattr__ and __delattr__, so those have to
    # be explicitly overridden here.

    def __setattr__(cls, name, value):
        checked_call(cls, '__setattr__', type.__setattr__, cls, name, value)

    def __delattr__(cls, name, value):
        checked_call(cls, '__delattr__', type.__delattr__, cls, name, value)


class Immutable(object):

    """Inherit from this class to make an immutable object.

    __init__ methods of subclasses are executed by _MetaImmutable.__call__,
    which enables mutability for the duration.

    """

    __metaclass__ = _MetaImmutable


class T(int, Immutable):  # Checks it works with multiple inheritance, too.

    "Class for testing immutability semantics"

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

    @classmethod
    def class_mutation(cls):
        cls.a = 5

    def instance_mutation(self):
        self.c = 1

    def __iadd__(self, o):
        pass

    def not_so_special_mutation(self):
        self +=1

def immutabilityTest(f, name):
    "Call f, which should try to mutate class T or T instance."
    try:
        f()
    except TypeError, e:
        assert 'T is immutable, %s disallowed' % name in e.args
    else:
        raise RuntimeError('Immutability failed!')

immutabilityTest(T.class_mutation, '__setattr__')
immutabilityTest(T(6).instance_mutation, '__setattr__')
immutabilityTest(T(6).not_so_special_mutation, '__iadd__')

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()