如果你已经在使用pandas，你可以构造一个pandas Series或DataFrame，从中你可以通过点语法访问项目:

1级字典:

import pandas as pd

my_dictionary = pd.Series({
  'key1': 'value1',
  'key2': 'value2'
})

print(my_dictionary.key1)
# Output: value1

2级字典:

import pandas as pd

my_dictionary = pd.DataFrame({
  'key1': {
    'inner_key1': 'value1'
  },
  'key2': {
    'inner_key2': 'value2'
  }
})

print(my_dictionary.key1.inner_key1)
# Output: value1

请注意，这可能在规范化数据结构(其中每个字典条目都具有相同的结构)下工作得更好。在上面的第二个例子中，得到的DataFrame是:

              key1    key2
inner_key1  value1     NaN
inner_key2     NaN  value2

我最近遇到了“Box”库，它也做同样的事情。

安装命令:pip install python-box

例子:

from box import Box

mydict = {"key1":{"v1":0.375,
                    "v2":0.625},
          "key2":0.125,
          }
mydict = Box(mydict)

print(mydict.key1.v1)

我发现它比其他现有的库(如dotmap)更有效，当你有大量嵌套字典时，dotmap会产生python递归错误。

链接到图书馆和详细信息:https://pypi.org/project/python-box/

我的观点:出于我自己的目的，我开发了minydra，一个简单的命令行解析器，包括一个自定义类MinyDict(灵感来自addict):

In [1]: from minydra import MinyDict

In [2]: args = MinyDict({"foo": "bar", "yes.no.maybe": "idontknow"}).pretty_print(); args
╭──────────────────────────────╮
│ foo          : bar           │
│ yes.no.maybe : idontknow     │
╰──────────────────────────────╯
Out[2]: {'foo': 'bar', 'yes.no.maybe': 'idontknow'}

In [3]: args.resolve().pretty_print(); args
╭──────────────────────────╮
│ foo : bar                │
│ yes                      │
│ │no                      │
│ │ │maybe : idontknow     │
╰──────────────────────────╯
Out[3]: {'foo': 'bar', 'yes': {'no': {'maybe': 'idontknow'}}}

In [4]: args.yes.no.maybe
Out[4]: "idontknow"

In [5]: "foo" in args
Out[5]: True

In [6]: "rick" in args
Out[6]: False

In [7]: args.morty is None
Out[7]: True

In [8]: args.items()
Out[8]: dict_items([('foo', 'bar'), ('yes', {'no': {'maybe': 'idontknow'}})])

它通过向json yaml和pickle添加转储/加载方法来上瘾，并且在MinyDict.update()中也有一个严格的模式来防止创建新键(这对于防止命令行中的错字很有用)

基于Kugel的回答，并考虑到Mike Graham的警告，如果我们制作一个包装器呢?

class DictWrap(object):
  """ Wrap an existing dict, or create a new one, and access with either dot 
    notation or key lookup.

    The attribute _data is reserved and stores the underlying dictionary.
    When using the += operator with create=True, the empty nested dict is 
    replaced with the operand, effectively creating a default dictionary
    of mixed types.

    args:
      d({}): Existing dict to wrap, an empty dict is created by default
      create(True): Create an empty, nested dict instead of raising a KeyError

    example:
      >>>dw = DictWrap({'pp':3})
      >>>dw.a.b += 2
      >>>dw.a.b += 2
      >>>dw.a['c'] += 'Hello'
      >>>dw.a['c'] += ' World'
      >>>dw.a.d
      >>>print dw._data
      {'a': {'c': 'Hello World', 'b': 4, 'd': {}}, 'pp': 3}

  """

  def __init__(self, d=None, create=True):
    if d is None:
      d = {}
    supr = super(DictWrap, self)  
    supr.__setattr__('_data', d)
    supr.__setattr__('__create', create)

  def __getattr__(self, name):
    try:
      value = self._data[name]
    except KeyError:
      if not super(DictWrap, self).__getattribute__('__create'):
        raise
      value = {}
      self._data[name] = value

    if hasattr(value, 'items'):
      create = super(DictWrap, self).__getattribute__('__create')
      return DictWrap(value, create)
    return value

  def __setattr__(self, name, value):
    self._data[name] = value  

  def __getitem__(self, key):
    try:
      value = self._data[key]
    except KeyError:
      if not super(DictWrap, self).__getattribute__('__create'):
        raise
      value = {}
      self._data[key] = value

    if hasattr(value, 'items'):
      create = super(DictWrap, self).__getattribute__('__create')
      return DictWrap(value, create)
    return value

  def __setitem__(self, key, value):
    self._data[key] = value

  def __iadd__(self, other):
    if self._data:
      raise TypeError("A Nested dict will only be replaced if it's empty")
    else:
      return other

这是我对@derek73的回答。我用字典。__getitem__作为__getattr__，因此它仍然抛出KeyError，并且im重命名字典公共方法以“”前缀(“”包围导致特殊方法名称冲突，如__get__将被视为一个描述符方法)。无论如何，由于关键的dict基方法，您无法将键作为属性获得完全清晰的命名空间，因此解决方案并不完美，但您可以拥有键属性，如get, pop, items等。

class DotDictMeta(type):                                                          
    def __new__(                                                                  
        cls,                                                                      
        name,                                                                     
        bases,                                                                    
        attrs,                                         
        rename_method=lambda n: f'__{n}__',                            
        **custom_methods,                                                         
    ):                                                                            
        d = dict                                                                  
        attrs.update(                                                             
            cls.get_hidden_or_renamed_methods(rename_method),           
            __getattr__=d.__getitem__,                                            
            __setattr__=d.__setitem__,                                            
            __delattr__=d.__delitem__,                                            
            **custom_methods,                                                     
        )                                                                         
        return super().__new__(cls, name, bases, attrs)                           
                                                                                  
    def __init__(self, name, bases, attrs, **_):                                  
        super().__init__(name, bases, attrs)                                      
                                                                                  
    @property                                                                     
    def attribute_error(self):                                                    
        raise AttributeError                                                      
                                                                                  
    @classmethod                                                                  
    def get_hidden_or_renamed_methods(cls, rename_method=None):                  
        public_methods = tuple(                                                   
            i for i in dict.__dict__.items() if not i[0].startswith('__')         
        )                                                                         
        error = cls.attribute_error                                               
        hidden_methods = ((k, error) for k, v in public_methods)                  
        yield from hidden_methods                                                 
        if rename_method:                                                       
            renamed_methods = ((rename_method(k), v) for k, v in public_methods) 
            yield from renamed_methods                                             
                                                                                  
                                                                                  
class DotDict(dict, metaclass=DotDictMeta):                                       
    pass  

                                                                    
                                                                              

你可以从DotDict命名空间中删除dict方法，并继续使用dict类方法，当你想操作其他dict实例并希望使用相同的方法而不需要额外检查它是否为DotDict时，它也很有用。

dct = dict(a=1)
dot_dct = DotDict(b=2)
foo = {c: i for i, c in enumerate('xyz')}
for d in (dct, dot_dct):
    # you would have to use dct.update and dot_dct.__update methods
    dict.update(d, foo)
    
assert dict.get(dot, 'foo', 0) is 0

我喜欢Munch，它提供了很多方便的选项在点访问。

进口蒙克 Temp_1 = {'person': {' fname': 'senthil'， 'lname': 'ramalingam'}} Dict_munch = munch.munchify(temp_1) dict_munch.person.fname