我如何使Python字典成员访问通过点“。”?
例如,我想写mydict.val而不是mydict['val']。
我还想以这种方式访问嵌套字典。例如
mydict.mydict2.val
会提到
mydict = { 'mydict2': { 'val': ... } }
我如何使Python字典成员访问通过点“。”?
例如,我想写mydict.val而不是mydict['val']。
我还想以这种方式访问嵌套字典。例如
mydict.mydict2.val
会提到
mydict = { 'mydict2': { 'val': ... } }
当前回答
可以使用dotsi来支持完整列表、dict和递归,并使用一些扩展方法
pip install dotsi
and
>>> import dotsi
>>>
>>> d = dotsi.Dict({"foo": {"bar": "baz"}}) # Basic
>>> d.foo.bar
'baz'
>>> d.users = [{"id": 0, "name": "Alice"}] # List
>>> d.users[0].name
'Alice'
>>> d.users.append({"id": 1, "name": "Becca"}); # Append
>>> d.users[1].name
'Becca'
>>> d.users += [{"id": 2, "name": "Cathy"}]; # `+=`
>>> d.users[2].name
'Cathy'
>>> d.update({"tasks": [{"id": "a", "text": "Task A"}]});
>>> d.tasks[0].text
'Task A'
>>> d.tasks[0].tags = ["red", "white", "blue"];
>>> d.tasks[0].tags[2];
'blue'
>>> d.tasks[0].pop("tags") # `.pop()`
['red', 'white', 'blue']
>>>
>>> import pprint
>>> pprint.pprint(d)
{'foo': {'bar': 'baz'},
'tasks': [{'id': 'a', 'text': 'Task A'}],
'users': [{'id': 0, 'name': 'Alice'},
{'id': 1, 'name': 'Becca'},
{'id': 2, 'name': 'Cathy'}]}
>>>
>>> type(d.users) # dotsi.Dict (AKA dotsi.DotsiDict)
<class 'dotsi.DotsiList'>
>>> type(d.users[0]) # dotsi.List (AKA dotsi.DotsiList)
<class 'dotsi.DotsiDict'>
>>>
其他回答
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
I ended up trying BOTH the AttrDict and the Bunch libraries and found them to be way to slow for my uses. After a friend and I looked into it, we found that the main method for writing these libraries results in the library aggressively recursing through a nested object and making copies of the dictionary object throughout. With this in mind, we made two key changes. 1) We made attributes lazy-loaded 2) instead of creating copies of a dictionary object, we create copies of a light-weight proxy object. This is the final implementation. The performance increase of using this code is incredible. When using AttrDict or Bunch, these two libraries alone consumed 1/2 and 1/3 respectively of my request time(what!?). This code reduced that time to almost nothing(somewhere in the range of 0.5ms). This of course depends on your needs, but if you are using this functionality quite a bit in your code, definitely go with something simple like this.
class DictProxy(object):
def __init__(self, obj):
self.obj = obj
def __getitem__(self, key):
return wrap(self.obj[key])
def __getattr__(self, key):
try:
return wrap(getattr(self.obj, key))
except AttributeError:
try:
return self[key]
except KeyError:
raise AttributeError(key)
# you probably also want to proxy important list properties along like
# items(), iteritems() and __len__
class ListProxy(object):
def __init__(self, obj):
self.obj = obj
def __getitem__(self, key):
return wrap(self.obj[key])
# you probably also want to proxy important list properties along like
# __iter__ and __len__
def wrap(value):
if isinstance(value, dict):
return DictProxy(value)
if isinstance(value, (tuple, list)):
return ListProxy(value)
return value
参见https://stackoverflow.com/users/704327/michael-merickel的原始实现。
另一件需要注意的事情是,这个实现非常简单,并且没有实现您可能需要的所有方法。您需要根据需要在DictProxy或ListProxy对象上写入这些内容。
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
最简单的解决方案。
定义一个只有pass语句的类。为该类创建对象并使用点表示法。
class my_dict:
pass
person = my_dict()
person.id = 1 # create using dot notation
person.phone = 9999
del person.phone # Remove a property using dot notation
name_data = my_dict()
name_data.first_name = 'Arnold'
name_data.last_name = 'Schwarzenegger'
person.name = name_data
person.name.first_name # dot notation access for nested properties - gives Arnold
我一直把它保存在util文件中。您也可以在自己的类中使用它作为mixin。
class dotdict(dict):
"""dot.notation access to dictionary attributes"""
__getattr__ = dict.get
__setattr__ = dict.__setitem__
__delattr__ = dict.__delitem__
mydict = {'val':'it works'}
nested_dict = {'val':'nested works too'}
mydict = dotdict(mydict)
mydict.val
# 'it works'
mydict.nested = dotdict(nested_dict)
mydict.nested.val
# 'nested works too'