什么是"冻结的字典"？

Question

• 冻结集是冻结集.
• 冻结列表可以是元组.
• 冻结的词典会是什么？一个不可变的,可洗的字典.

我想它可能是类似的collections.namedtuple,但这更像是一个冻结的词典(一个半冻结的词典).不是吗？

A"frozendict"应该是一个冰冻的字典,它应该有keys,values,get,等,并支持in,for等等.

Answer 1

Python没有内置的frozendict类型.事实证明这不会经常使用(尽管它仍然可能更有用frozenset).

想要这种类型的最常见原因是当memoizing函数调用具有未知参数的函数时.最常见的解决方案是存储一个可清除的dict(其中值是可清除的)的类似的东西tuple(sorted(kwargs.iteritems())).

这取决于排序不是有点疯狂.Python不能肯定地承诺排序会在这里产生合理的结果.(但它不能承诺太多其他的东西,所以不要太过分.)

你可以轻松地制作某种类似于dict的包装器.它可能看起来像

import collections

class FrozenDict(collections.Mapping):
    """Don't forget the docstrings!!"""

    def __init__(self, *args, **kwargs):
        self._d = dict(*args, **kwargs)
        self._hash = None

    def __iter__(self):
        return iter(self._d)

    def __len__(self):
        return len(self._d)

    def __getitem__(self, key):
        return self._d[key]

    def __hash__(self):
        # It would have been simpler and maybe more obvious to 
        # use hash(tuple(sorted(self._d.iteritems()))) from this discussion
        # so far, but this solution is O(n). I don't know what kind of 
        # n we are going to run into, but sometimes it's hard to resist the 
        # urge to optimize when it will gain improved algorithmic performance.
        if self._hash is None:
            self._hash = 0
            for pair in self.iteritems():
                self._hash ^= hash(pair)
        return self._hash

它应该很棒:

>>> x = FrozenDict(a=1, b=2)
>>> y = FrozenDict(a=1, b=2)
>>> x is y
False
>>> x == y
True
>>> x == {'a': 1, 'b': 2}
True
>>> d = {x: 'foo'}
>>> d[y]
'foo'

Answer 2

奇怪的是,尽管我们frozenset在python中很少有用,但仍然没有冻结映射.该想法在PEP 416中被驳回.

所以python 2解决方案:

def foo(config={'a': 1}):
    ...

似乎仍然有些蹩脚:

def foo(config=None):
    if config is None:
        config = default_config = {'a': 1}
    ...

在python3您的选择这个:

from types import MappingProxyType

default_config = {'a': 1}
DEFAULTS = MappingProxyType(default_config)

def foo(config=DEFAULTS):
    ...

现在,默认配置可以动态更新,但是通过传递代理而不希望它是不可变的.

因此,更改将按预期default_config更新DEFAULTS,但您无法写入映射代理对象本身.

不可否认,它与"不可变的,可以清洗的字典"并不完全相同 - 但考虑到我们可能需要冻结的相同类型的用例,它是一个不错的替代品.

Answer 3

假设字典的键和值本身是不可变的(例如字符串),那么:

>>> d
{'forever': 'atones', 'minks': 'cards', 'overhands': 'warranted', 
 'hardhearted': 'tartly', 'gradations': 'snorkeled'}
>>> t = tuple((k, d[k]) for k in sorted(d.keys()))
>>> hash(t)
1524953596

Answer 4

没有fronzedict，但是您可以使用MappingProxyTypePython 3.3中添加到标准库中的：

>>> from types import MappingProxyType
>>> foo = MappingProxyType({'a': 1})
>>> foo
mappingproxy({'a': 1})
>>> foo['a'] = 2
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: 'mappingproxy' object does not support item assignment
>>> foo
mappingproxy({'a': 1})

Answer 5

这是我一直在使用的代码.我继承了冷冻集.其优点如下.

1. 这是一个真正不可改变的对象.不依赖于未来用户和开发人员的良好行为.
2. 在常规字典和冻结字典之间来回转换很容易.FrozenDict(orig_dict) - >冻结字典.dict(frozen_dict) - >常规字典.

2015年1月21日更新:我在2014年发布的原始代码使用for循环查找匹配的密钥.那非常慢.现在我已经整理了一个利用了freezeset的散列功能的实现.键值对存储在特殊容器中,其中__hash__和__eq__函数仅基于键.这段代码也经过了正式的单元测试,不像我在2014年8月发布的那样.

麻省理工学院式的许可证.

if 3 / 2 == 1:
    version = 2
elif 3 / 2 == 1.5:
    version = 3

def col(i):
    ''' For binding named attributes to spots inside subclasses of tuple.'''
    g = tuple.__getitem__
    @property
    def _col(self):
        return g(self,i)
    return _col

class Item(tuple):
    ''' Designed for storing key-value pairs inside
        a FrozenDict, which itself is a subclass of frozenset.
        The __hash__ is overloaded to return the hash of only the key.
        __eq__ is overloaded so that normally it only checks whether the Item's
        key is equal to the other object, HOWEVER, if the other object itself
        is an instance of Item, it checks BOTH the key and value for equality.

        WARNING: Do not use this class for any purpose other than to contain
        key value pairs inside FrozenDict!!!!

        The __eq__ operator is overloaded in such a way that it violates a
        fundamental property of mathematics. That property, which says that
        a == b and b == c implies a == c, does not hold for this object.
        Here's a demonstration:
            [in]  >>> x = Item(('a',4))
            [in]  >>> y = Item(('a',5))
            [in]  >>> hash('a')
            [out] >>> 194817700
            [in]  >>> hash(x)
            [out] >>> 194817700
            [in]  >>> hash(y)
            [out] >>> 194817700
            [in]  >>> 'a' == x
            [out] >>> True
            [in]  >>> 'a' == y
            [out] >>> True
            [in]  >>> x == y
            [out] >>> False
    '''

    __slots__ = ()
    key, value = col(0), col(1)
    def __hash__(self):
        return hash(self.key)
    def __eq__(self, other):
        if isinstance(other, Item):
            return tuple.__eq__(self, other)
        return self.key == other
    def __ne__(self, other):
        return not self.__eq__(other)
    def __str__(self):
        return '%r: %r' % self
    def __repr__(self):
        return 'Item((%r, %r))' % self

class FrozenDict(frozenset):
    ''' Behaves in most ways like a regular dictionary, except that it's immutable.
        It differs from other implementations because it doesn't subclass "dict".
        Instead it subclasses "frozenset" which guarantees immutability.
        FrozenDict instances are created with the same arguments used to initialize
        regular dictionaries, and has all the same methods.
            [in]  >>> f = FrozenDict(x=3,y=4,z=5)
            [in]  >>> f['x']
            [out] >>> 3
            [in]  >>> f['a'] = 0
            [out] >>> TypeError: 'FrozenDict' object does not support item assignment

        FrozenDict can accept un-hashable values, but FrozenDict is only hashable if its values are hashable.
            [in]  >>> f = FrozenDict(x=3,y=4,z=5)
            [in]  >>> hash(f)
            [out] >>> 646626455
            [in]  >>> g = FrozenDict(x=3,y=4,z=[])
            [in]  >>> hash(g)
            [out] >>> TypeError: unhashable type: 'list'

        FrozenDict interacts with dictionary objects as though it were a dict itself.
            [in]  >>> original = dict(x=3,y=4,z=5)
            [in]  >>> frozen = FrozenDict(x=3,y=4,z=5)
            [in]  >>> original == frozen
            [out] >>> True

        FrozenDict supports bi-directional conversions with regular dictionaries.
            [in]  >>> original = {'x': 3, 'y': 4, 'z': 5}
            [in]  >>> FrozenDict(original)
            [out] >>> FrozenDict({'x': 3, 'y': 4, 'z': 5})
            [in]  >>> dict(FrozenDict(original))
            [out] >>> {'x': 3, 'y': 4, 'z': 5}   '''

    __slots__ = ()
    def __new__(cls, orig={}, **kw):
        if kw:
            d = dict(orig, **kw)
            items = map(Item, d.items())
        else:
            try:
                items = map(Item, orig.items())
            except AttributeError:
                items = map(Item, orig)
        return frozenset.__new__(cls, items)

    def __repr__(self):
        cls = self.__class__.__name__
        items = frozenset.__iter__(self)
        _repr = ', '.join(map(str,items))
        return '%s({%s})' % (cls, _repr)

    def __getitem__(self, key):
        if key not in self:
            raise KeyError(key)
        diff = self.difference
        item = diff(diff({key}))
        key, value = set(item).pop()
        return value

    def get(self, key, default=None):
        if key not in self:
            return default
        return self[key]

    def __iter__(self):
        items = frozenset.__iter__(self)
        return map(lambda i: i.key, items)

    def keys(self):
        items = frozenset.__iter__(self)
        return map(lambda i: i.key, items)

    def values(self):
        items = frozenset.__iter__(self)
        return map(lambda i: i.value, items)

    def items(self):
        items = frozenset.__iter__(self)
        return map(tuple, items)

    def copy(self):
        cls = self.__class__
        items = frozenset.copy(self)
        dupl = frozenset.__new__(cls, items)
        return dupl

    @classmethod
    def fromkeys(cls, keys, value):
        d = dict.fromkeys(keys,value)
        return cls(d)

    def __hash__(self):
        kv = tuple.__hash__
        items = frozenset.__iter__(self)
        return hash(frozenset(map(kv, items)))

    def __eq__(self, other):
        if not isinstance(other, FrozenDict):
            try:
                other = FrozenDict(other)
            except Exception:
                return False
        return frozenset.__eq__(self, other)

    def __ne__(self, other):
        return not self.__eq__(other)


if version == 2:
    #Here are the Python2 modifications
    class Python2(FrozenDict):
        def __iter__(self):
            items = frozenset.__iter__(self)
            for i in items:
                yield i.key

        def iterkeys(self):
            items = frozenset.__iter__(self)
            for i in items:
                yield i.key

        def itervalues(self):
            items = frozenset.__iter__(self)
            for i in items:
                yield i.value

        def iteritems(self):
            items = frozenset.__iter__(self)
            for i in items:
                yield (i.key, i.value)

        def has_key(self, key):
            return key in self

        def viewkeys(self):
            return dict(self).viewkeys()

        def viewvalues(self):
            return dict(self).viewvalues()

        def viewitems(self):
            return dict(self).viewitems()

    #If this is Python2, rebuild the class
    #from scratch rather than use a subclass
    py3 = FrozenDict.__dict__
    py3 = {k: py3[k] for k in py3}
    py2 = {}
    py2.update(py3)
    dct = Python2.__dict__
    py2.update({k: dct[k] for k in dct})

    FrozenDict = type('FrozenDict', (frozenset,), py2)

Answer 6

子类化dict

我在野外看到了这种模式（github）并想提一下：

class FrozenDict(dict):
    def __init__(self, *args, **kwargs):
        self._hash = None
        super(FrozenDict, self).__init__(*args, **kwargs)

    def __hash__(self):
        if self._hash is None:
            self._hash = hash(tuple(sorted(self.items())))  # iteritems() on py2
        return self._hash

    def _immutable(self, *args, **kws):
        raise TypeError('cannot change object - object is immutable')

    # makes (deep)copy alot more efficient
    def __copy__(self):
        return self

    def __deepcopy__(self, memo=None):
        if memo is not None:
            memo[id(self)] = self
        return self

    __setitem__ = _immutable
    __delitem__ = _immutable
    pop = _immutable
    popitem = _immutable
    clear = _immutable
    update = _immutable
    setdefault = _immutable

用法示例：

d1 = FrozenDict({'a': 1, 'b': 2})
d2 = FrozenDict({'a': 1, 'b': 2})
d1.keys() 
assert isinstance(d1, dict)
assert len(set([d1, d2])) == 1  # hashable

优点

• 支持get(), keys(), items()（在 py2 上）以及所有开箱即用的iteritems()好东西，无需明确实现它们dict
• 内部使用dict意味着性能（dict在 CPython 中用 c 编写）
• 优雅简约，没有黑魔法
• isinstance(my_frozen_dict, dict)返回 True - 尽管 python 鼓励鸭式输入许多包的用途isinstance()，但这可以节省许多调整和定制

缺点

• 任何子类都可以覆盖它或在内部访问它（你不能真正 100% 保护 python 中的某些东西，你应该信任你的用户并提供良好的文档）。
• 如果你关心速度，你可能想做得__hash__更快一点。

Answer 7

安装frozendict

pip install frozendict

用它！

from frozendict import frozendict

def smth(param = frozendict({})):
    pass

Answer 8

我每次编写这样的函数时都会想到frozendict:

def do_something(blah, optional_dict_parm=None):
    if optional_dict_parm is None:
        optional_dict_parm = {}

Answer 9

其主要缺点namedtuple是需要在使用前指定，因此对于单一用途的情况不太方便。

然而，有一个实用的解决方法可以用来处理许多此类情况。假设您想要拥有以下字典的不可变等价物：

MY_CONSTANT = {
    'something': 123,
    'something_else': 456
}

可以这样模拟：

from collections import namedtuple

MY_CONSTANT = namedtuple('MyConstant', 'something something_else')(123, 456)

甚至可以编写一个辅助函数来自动执行此操作：

def freeze_dict(data):
    from collections import namedtuple
    keys = sorted(data.keys())
    frozen_type = namedtuple(''.join(keys), keys)
    return frozen_type(**data)

a = {'foo':'bar', 'x':'y'}
fa = freeze_dict(data)
assert a['foo'] == fa.foo

当然，这仅适用于平面字典，但实现递归版本应该不会太困难。

Answer 10

您可以使用frozendictfromutilspie包作为：

>>> from utilspie.collectionsutils import frozendict

>>> my_dict = frozendict({1: 3, 4: 5})
>>> my_dict  # object of `frozendict` type
frozendict({1: 3, 4: 5})

# Hashable
>>> {my_dict: 4}
{frozendict({1: 3, 4: 5}): 4}

# Immutable
>>> my_dict[1] = 5
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/mquadri/workspace/utilspie/utilspie/collectionsutils/collections_utils.py", line 44, in __setitem__
    self.__setitem__.__name__, type(self).__name__))
AttributeError: You can not call '__setitem__()' for 'frozendict' object

根据文件：

frozendict(dict_obj) : 接受 dict 类型的 obj 并返回一个可散列且不可变的dict