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
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
其他回答
这也适用于嵌套字典，并确保后面追加的字典行为相同:
class DotDict(dict):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
# Recursively turn nested dicts into DotDicts
for key, value in self.items():
if type(value) is dict:
self[key] = DotDict(value)
def __setitem__(self, key, item):
if type(item) is dict:
item = DotDict(item)
super().__setitem__(key, item)
__setattr__ = __setitem__
__getattr__ = dict.__getitem__
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()
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
获得点访问(但不是数组访问)的一个简单方法是在Python中使用一个普通对象。是这样的:
class YourObject:
def __init__(self, *args, **kwargs):
for k, v in kwargs.items():
setattr(self, k, v)
.．.像这样使用它:
>>> obj = YourObject(key="value")
>>> print(obj.key)
"value"
．.． 把它转换成字典:
>>> print(obj.__dict__)
{"key": "value"}
使用namedtuple允许点访问。
它就像一个轻量级对象，也具有元组的属性。
它允许定义属性并使用点操作符访问它们。
from collections import namedtuple
Data = namedtuple('Data', ['key1', 'key2'])
dataObj = Data(val1, key2=val2) # can instantiate using keyword arguments and positional arguments
使用点运算符访问
dataObj.key1 # Gives val1
datObj.key2 # Gives val2
使用元组索引进行访问
dataObj[0] # Gives val1
dataObj[1] # Gives val2
但记住这是一个元组;不是字典。因此下面的代码将给出错误
dataObj['key1'] # Gives TypeError: tuple indices must be integers or slices, not str
参考:namedtuple
推荐文章
- 输入对象的datetime。Datetime没有Datetime属性
- numpy数组的Python内存使用情况
- NumPy或Pandas:保持数组类型为整数，同时具有NaN值
- 列表理解条件中的' elif '
- Python的“property”和“attribute”有什么区别?
- 在Python中格式化多行字典的正确方法是什么?
- 向异常添加信息?
- Sphinx autodoc不够自动
- 如何限制Django模型中数值字段的最大值?
- 访问对象内存地址
- 为什么在Python方法中需要显式地有“self”参数?
- 如何升级Windows 10下的Python安装?
- tqdm在Jupyter笔记本重复打印新的进度条
- 如何在for循环中注释类型?
- 如何替换一个Pandas数据框架的字符串列中的文本?
