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
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
其他回答
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'
kaggle_environments使用的实现是一个名为structify的函数。
class Struct(dict):
def __init__(self, **entries):
entries = {k: v for k, v in entries.items() if k != "items"}
dict.__init__(self, entries)
self.__dict__.update(entries)
def __setattr__(self, attr, value):
self.__dict__[attr] = value
self[attr] = value
# Added benefit of cloning lists and dicts.
def structify(o):
if isinstance(o, list):
return [structify(o[i]) for i in range(len(o))]
elif isinstance(o, dict):
return Struct(**{k: structify(v) for k, v in o.items()})
return o
https://github.com/Kaggle/kaggle-environments/blob/master/kaggle_environments/utils.py
这可能有助于在《ConnectX》等游戏中测试AI模拟代理
from kaggle_environments import structify
obs = structify({ 'remainingOverageTime': 60, 'step': 0, 'mark': 1, 'board': [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]})
conf = structify({ 'timeout': 2, 'actTimeout': 2, 'agentTimeout': 60, 'episodeSteps': 1000, 'runTimeout': 1200, 'columns': 7, 'rows': 6, 'inarow': 4, '__raw_path__': '/kaggle_simulations/agent/main.py' })
def agent(obs, conf):
action = obs.step % conf.columns
return action
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
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'
用于无限级别的字典、列表、字典的列表和列表的字典的嵌套。
它还支持酸洗
这是这个答案的延伸。
class DotDict(dict):
# https://stackoverflow.com/a/70665030/913098
"""
Example:
m = Map({'first_name': 'Eduardo'}, last_name='Pool', age=24, sports=['Soccer'])
Iterable are assumed to have a constructor taking list as input.
"""
def __init__(self, *args, **kwargs):
super(DotDict, self).__init__(*args, **kwargs)
args_with_kwargs = []
for arg in args:
args_with_kwargs.append(arg)
args_with_kwargs.append(kwargs)
args = args_with_kwargs
for arg in args:
if isinstance(arg, dict):
for k, v in arg.items():
self[k] = v
if isinstance(v, dict):
self[k] = DotDict(v)
elif isinstance(v, str) or isinstance(v, bytes):
self[k] = v
elif isinstance(v, Iterable):
klass = type(v)
map_value: List[Any] = []
for e in v:
map_e = DotDict(e) if isinstance(e, dict) else e
map_value.append(map_e)
self[k] = klass(map_value)
def __getattr__(self, attr):
return self.get(attr)
def __setattr__(self, key, value):
self.__setitem__(key, value)
def __setitem__(self, key, value):
super(DotDict, self).__setitem__(key, value)
self.__dict__.update({key: value})
def __delattr__(self, item):
self.__delitem__(item)
def __delitem__(self, key):
super(DotDict, self).__delitem__(key)
del self.__dict__[key]
def __getstate__(self):
return self.__dict__
def __setstate__(self, d):
self.__dict__.update(d)
if __name__ == "__main__":
import pickle
def test_map():
d = {
"a": 1,
"b": {
"c": "d",
"e": 2,
"f": None
},
"g": [],
"h": [1, "i"],
"j": [1, "k", {}],
"l":
[
1,
"m",
{
"n": [3],
"o": "p",
"q": {
"r": "s",
"t": ["u", 5, {"v": "w"}, ],
"x": ("z", 1)
}
}
],
}
map_d = DotDict(d)
w = map_d.l[2].q.t[2].v
assert w == "w"
pickled = pickle.dumps(map_d)
unpickled = pickle.loads(pickled)
assert unpickled == map_d
kwargs_check = DotDict(a=1, b=[dict(c=2, d="3"), 5])
assert kwargs_check.b[0].d == "3"
kwargs_and_args_check = DotDict(d, a=1, b=[dict(c=2, d="3"), 5])
assert kwargs_and_args_check.l[2].q.t[2].v == "w"
assert kwargs_and_args_check.b[0].d == "3"
test_map()