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
这是我从很久以前的一个项目里挖出来的。它可能还可以再优化一点,但就是这样了。
class DotNotation(dict):
__setattr__= dict.__setitem__
__delattr__= dict.__delitem__
def __init__(self, data):
if isinstance(data, str):
data = json.loads(data)
for name, value in data.items():
setattr(self, name, self._wrap(value))
def __getattr__(self, attr):
def _traverse(obj, attr):
if self._is_indexable(obj):
try:
return obj[int(attr)]
except:
return None
elif isinstance(obj, dict):
return obj.get(attr, None)
else:
return attr
if '.' in attr:
return reduce(_traverse, attr.split('.'), self)
return self.get(attr, None)
def _wrap(self, value):
if self._is_indexable(value):
# (!) recursive (!)
return type(value)([self._wrap(v) for v in value])
elif isinstance(value, dict):
return DotNotation(value)
else:
return value
@staticmethod
def _is_indexable(obj):
return isinstance(obj, (tuple, list, set, frozenset))
if __name__ == "__main__":
test_dict = {
"dimensions": {
"length": "112",
"width": "103",
"height": "42"
},
"meta_data": [
{
"id": 11089769,
"key": "imported_gallery_files",
"value": [
"https://example.com/wp-content/uploads/2019/09/unnamed-3.jpg",
"https://example.com/wp-content/uploads/2019/09/unnamed-2.jpg",
"https://example.com/wp-content/uploads/2019/09/unnamed-4.jpg"
]
}
]
}
dotted_dict = DotNotation(test_dict)
print(dotted_dict.dimensions.length) # => '112'
print(getattr(dotted_dict, 'dimensions.length')) # => '112'
print(dotted_dict.meta_data[0].key) # => 'imported_gallery_files'
print(getattr(dotted_dict, 'meta_data.0.key')) # => 'imported_gallery_files'
print(dotted_dict.meta_data[0].value) # => ['link1','link2','link2']
print(getattr(dotted_dict, 'meta_data.0.value')) # => ['link1','link2','link3']
print(dotted_dict.meta_data[0].value[2]) # => 'link3'
print(getattr(dotted_dict, 'meta_data.0.value.2')) # => 'link3'
其他回答
一个很微妙的解
class DotDict(dict):
__setattr__ = dict.__setitem__
__delattr__ = dict.__delitem__
def __getattr__(self, key):
def typer(candidate):
if isinstance(candidate, dict):
return DotDict(candidate)
if isinstance(candidate, str): # iterable but no need to iter
return candidate
try: # other iterable are processed as list
return [typer(item) for item in candidate]
except TypeError:
return candidate
return candidate
return typer(dict.get(self, key))
你可以用我刚做的这个类来做。对于这个类,您可以像使用另一个字典(包括json序列化)一样使用Map对象,或者使用点表示法。希望对大家有所帮助:
class Map(dict):
"""
Example:
m = Map({'first_name': 'Eduardo'}, last_name='Pool', age=24, sports=['Soccer'])
"""
def __init__(self, *args, **kwargs):
super(Map, self).__init__(*args, **kwargs)
for arg in args:
if isinstance(arg, dict):
for k, v in arg.iteritems():
self[k] = v
if kwargs:
for k, v in kwargs.iteritems():
self[k] = v
def __getattr__(self, attr):
return self.get(attr)
def __setattr__(self, key, value):
self.__setitem__(key, value)
def __setitem__(self, key, value):
super(Map, self).__setitem__(key, value)
self.__dict__.update({key: value})
def __delattr__(self, item):
self.__delitem__(item)
def __delitem__(self, key):
super(Map, self).__delitem__(key)
del self.__dict__[key]
使用例子:
m = Map({'first_name': 'Eduardo'}, last_name='Pool', age=24, sports=['Soccer'])
# Add new key
m.new_key = 'Hello world!'
# Or
m['new_key'] = 'Hello world!'
print m.new_key
print m['new_key']
# Update values
m.new_key = 'Yay!'
# Or
m['new_key'] = 'Yay!'
# Delete key
del m.new_key
# Or
del m['new_key']
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。
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'
这是一个老问题,但我最近发现sklearn有一个可通过键访问的实现版本字典,即Bunch https://scikit-learn.org/stable/modules/generated/sklearn.utils.Bunch.html#sklearn.utils.Bunch