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.

为了给答案增加一些变化，sci-kit learn将其实现为一串:

class Bunch(dict):                                                              
    """ Scikit Learn's container object                                         

    Dictionary-like object that exposes its keys as attributes.                 
    >>> b = Bunch(a=1, b=2)                                                     
    >>> b['b']                                                                  
    2                                                                           
    >>> b.b                                                                     
    2                                                                           
    >>> b.c = 6                                                                 
    >>> b['c']                                                                  
    6                                                                           
    """                                                                         

    def __init__(self, **kwargs):                                               
        super(Bunch, self).__init__(kwargs)                                     

    def __setattr__(self, key, value):                                          
        self[key] = value                                                       

    def __dir__(self):                                                          
        return self.keys()                                                      

    def __getattr__(self, key):                                                 
        try:                                                                    
            return self[key]                                                    
        except KeyError:                                                        
            raise AttributeError(key)                                           

    def __setstate__(self, state):                                              
        pass                       

您所需要的是获取setattr和getattr方法—getattr检查字典键，然后继续检查实际属性。setstaet是针对pickle /unpickling“bunch”的修复-如果感兴趣，请检查https://github.com/scikit-learn/scikit-learn/issues/6196

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)

我根据这个线程的输入创建了这个。我需要使用odect，所以我必须覆盖get和设置attr。我认为这应该适用于大多数特殊用途。

用法如下:

# Create an ordered dict normally...
>>> od = OrderedAttrDict()
>>> od["a"] = 1
>>> od["b"] = 2
>>> od
OrderedAttrDict([('a', 1), ('b', 2)])

# Get and set data using attribute access...
>>> od.a
1
>>> od.b = 20
>>> od
OrderedAttrDict([('a', 1), ('b', 20)])

# Setting a NEW attribute only creates it on the instance, not the dict...
>>> od.c = 8
>>> od
OrderedAttrDict([('a', 1), ('b', 20)])
>>> od.c
8

类:

class OrderedAttrDict(odict.OrderedDict):
    """
    Constructs an odict.OrderedDict with attribute access to data.

    Setting a NEW attribute only creates it on the instance, not the dict.
    Setting an attribute that is a key in the data will set the dict data but 
    will not create a new instance attribute
    """
    def __getattr__(self, attr):
        """
        Try to get the data. If attr is not a key, fall-back and get the attr
        """
        if self.has_key(attr):
            return super(OrderedAttrDict, self).__getitem__(attr)
        else:
            return super(OrderedAttrDict, self).__getattr__(attr)


    def __setattr__(self, attr, value):
        """
        Try to set the data. If attr is not a key, fall-back and set the attr
        """
        if self.has_key(attr):
            super(OrderedAttrDict, self).__setitem__(attr, value)
        else:
            super(OrderedAttrDict, self).__setattr__(attr, value)

这是一个非常酷的模式，已经在线程中提到了，但如果你只是想把字典转换成一个在IDE中使用自动完成的对象，等等:

class ObjectFromDict(object):
    def __init__(self, d):
        self.__dict__ = d

这不是一个“好”的答案，但我认为这是俏皮的(它不处理嵌套字典在当前形式)。简单地将dict包装在函数中:

def make_funcdict(d=None, **kwargs)
    def funcdict(d=None, **kwargs):
        if d is not None:
            funcdict.__dict__.update(d)
        funcdict.__dict__.update(kwargs)
        return funcdict.__dict__
    funcdict(d, **kwargs)
    return funcdict

现在你的语法略有不同。访问dict项就像访问属性f.key一样。要以通常的方式访问dict项(和其他dict方法)，请执行f()['key']，我们可以通过使用关键字参数和/或字典调用f来方便地更新dict

例子

d = {'name':'Henry', 'age':31}
d = make_funcdict(d)
>>> for key in d():
...     print key
... 
age
name
>>> print d.name
... Henry
>>> print d.age
... 31
>>> d({'Height':'5-11'}, Job='Carpenter')
... {'age': 31, 'name': 'Henry', 'Job': 'Carpenter', 'Height': '5-11'}

就是这样。如果有人提出这种方法的优点和缺点，我会很高兴。

编辑:NeoBunch是废弃的，Munch(上面提到过)可以作为一个替代品。不过，我把这个解决方案留在这里，它可能对某些人有用。

正如Doug所指出的，有一个Bunch包，你可以使用它来实现obj。关键功能。实际上有一个更新的版本叫做

尼奥邦克·蒙克

它有一个伟大的功能，通过neobunchify函数将你的字典转换为NeoBunch对象。我经常使用Mako模板，将数据作为NeoBunch对象传递使它们更具可读性，所以如果你碰巧在你的Python程序中使用了一个普通的字典，但想要在Mako模板中使用点符号，你可以这样使用:

from mako.template import Template
from neobunch import neobunchify

mako_template = Template(filename='mako.tmpl', strict_undefined=True)
data = {'tmpl_data': [{'key1': 'value1', 'key2': 'value2'}]}
with open('out.txt', 'w') as out_file:
    out_file.write(mako_template.render(**neobunchify(data)))

Mako模板看起来像这样:

% for d in tmpl_data:
Column1     Column2
${d.key1}   ${d.key2}
% endfor