我发现它更方便访问字典键作为obj。foo而不是obj['foo'],所以我写了这个片段:

class AttributeDict(dict):
    def __getattr__(self, attr):
        return self[attr]
    def __setattr__(self, attr, value):
        self[attr] = value

然而,我认为一定有一些原因,Python没有提供开箱即用的功能。以这种方式访问字典键的注意事项和缺陷是什么?


当前回答

这就是我用的

args = {
        'batch_size': 32,
        'workers': 4,
        'train_dir': 'train',
        'val_dir': 'val',
        'lr': 1e-3,
        'momentum': 0.9,
        'weight_decay': 1e-4
    }
args = namedtuple('Args', ' '.join(list(args.keys())))(**args)

print (args.lr)

其他回答

这个答案摘自Luciano Ramalho的《流利的Python》一书。这要归功于那个家伙。

class AttrDict:
    """A read-only façade for navigating a JSON-like object
    using attribute notation
    """

    def __init__(self, mapping):
        self._data = dict(mapping)

    def __getattr__(self, name):
        if hasattr(self._data, name):
            return getattr(self._data, name)
        else:
            return AttrDict.build(self._data[name])

    @classmethod
    def build(cls, obj):
        if isinstance(obj, Mapping):
            return cls(obj)
        elif isinstance(obj, MutableSequence):
            return [cls.build(item) for item in obj]
        else:
            return obj

in the init we are taking the dict and making it a dictionary. when getattr is used we try to get the attribute from the dict if the dict already has that attribute. or else we are passing the argument to a class method called build. now build does the intresting thing. if the object is dict or a mapping like that, the that object is made an attr dict itself. if it's a sequence like list, it's passed to the build function we r on right now. if it's anythin else, like str or int. return the object itself.

这并没有解决最初的问题,但是对于像我这样在这里寻找提供此功能的库的人来说应该是有用的。

Addict是一个很棒的库:https://github.com/mewwts/addict它照顾了前面的答案中提到的许多问题。

文档中的一个例子:

body = {
    'query': {
        'filtered': {
            'query': {
                'match': {'description': 'addictive'}
            },
            'filter': {
                'term': {'created_by': 'Mats'}
            }
        }
    }
}

成瘾者:

from addict import Dict
body = Dict()
body.query.filtered.query.match.description = 'addictive'
body.query.filtered.filter.term.created_by = 'Mats'

由于以下原因,我对现有的选项不满意,于是我开发了MetaDict。它的行为完全类似于dict,但支持点表示法和IDE自动补全,而没有其他解决方案的缺点和潜在的名称空间冲突。所有功能和使用示例都可以在GitHub上找到(见上面的链接)。

完全披露:我是MetaDict的作者。

我在尝试其他解决方案时遇到的缺点/限制:

Addict No key autocompletion in IDE Nested key assignment cannot be turned off Newly assigned dict objects are not converted to support attribute-style key access Shadows inbuilt type Dict Prodict No key autocompletion in IDE without defining a static schema (similar to dataclass) No recursive conversion of dict objects when embedded in list or other inbuilt iterables AttrDict No key autocompletion in IDE Converts list objects to tuple behind the scenes Munch Inbuilt methods like items(), update(), etc. can be overwritten with obj.items = [1, 2, 3] No recursive conversion of dict objects when embedded in list or other inbuilt iterables EasyDict Only strings are valid keys, but dict accepts all hashable objects as keys Inbuilt methods like items(), update(), etc. can be overwritten with obj.items = [1, 2, 3] Inbuilt methods don't behave as expected: obj.pop('unknown_key', None) raises an AttributeError

下面是一个使用内置collection .namedtuple的不可变记录的简短示例:

def record(name, d):
    return namedtuple(name, d.keys())(**d)

还有一个用法示例:

rec = record('Model', {
    'train_op': train_op,
    'loss': loss,
})

print rec.loss(..)

没有必要自己写 Setattr()和getattr()已经存在。

类对象的优势可能在类定义和继承中发挥作用。