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
此解决方案是对epool提供的解决方案的改进,以满足OP以一致的方式访问嵌套字典的需求。epool的解决方案不允许访问嵌套字典。
class YAMLobj(dict):
def __init__(self, args):
super(YAMLobj, self).__init__(args)
if isinstance(args, dict):
for k, v in args.iteritems():
if not isinstance(v, dict):
self[k] = v
else:
self.__setattr__(k, YAMLobj(v))
def __getattr__(self, attr):
return self.get(attr)
def __setattr__(self, key, value):
self.__setitem__(key, value)
def __setitem__(self, key, value):
super(YAMLobj, self).__setitem__(key, value)
self.__dict__.update({key: value})
def __delattr__(self, item):
self.__delitem__(item)
def __delitem__(self, key):
super(YAMLobj, self).__delitem__(key)
del self.__dict__[key]
使用这个类,现在可以执行如下操作:A.B.C.D.
其他回答
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'
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"}
我试了一下:
class dotdict(dict):
def __getattr__(self, name):
return self[name]
你也可以尝试__getattribute__。
使每个字典都是一种类型的dotdict就足够了,如果你想从多层字典初始化它,也可以尝试实现__init__。
不是对OP问题的直接回答,但受到启发,也许对一些人有用。我已经创建了一个基于对象的解决方案使用内部__dict__(在任何方式优化代码)
payload = {
"name": "John",
"location": {
"lat": 53.12312312,
"long": 43.21345112
},
"numbers": [
{
"role": "home",
"number": "070-12345678"
},
{
"role": "office",
"number": "070-12345679"
}
]
}
class Map(object):
"""
Dot style access to object members, access raw values
with an underscore e.g.
class Foo(Map):
def foo(self):
return self.get('foo') + 'bar'
obj = Foo(**{'foo': 'foo'})
obj.foo => 'foobar'
obj._foo => 'foo'
"""
def __init__(self, *args, **kwargs):
for arg in args:
if isinstance(arg, dict):
for k, v in arg.iteritems():
self.__dict__[k] = v
self.__dict__['_' + k] = v
if kwargs:
for k, v in kwargs.iteritems():
self.__dict__[k] = v
self.__dict__['_' + k] = v
def __getattribute__(self, attr):
if hasattr(self, 'get_' + attr):
return object.__getattribute__(self, 'get_' + attr)()
else:
return object.__getattribute__(self, attr)
def get(self, key):
try:
return self.__dict__.get('get_' + key)()
except (AttributeError, TypeError):
return self.__dict__.get(key)
def __repr__(self):
return u"<{name} object>".format(
name=self.__class__.__name__
)
class Number(Map):
def get_role(self):
return self.get('role')
def get_number(self):
return self.get('number')
class Location(Map):
def get_latitude(self):
return self.get('lat') + 1
def get_longitude(self):
return self.get('long') + 1
class Item(Map):
def get_name(self):
return self.get('name') + " Doe"
def get_location(self):
return Location(**self.get('location'))
def get_numbers(self):
return [Number(**n) for n in self.get('numbers')]
# Tests
obj = Item({'foo': 'bar'}, **payload)
assert type(obj) == Item
assert obj._name == "John"
assert obj.name == "John Doe"
assert type(obj.location) == Location
assert obj.location._lat == 53.12312312
assert obj.location._long == 43.21345112
assert obj.location.latitude == 54.12312312
assert obj.location.longitude == 44.21345112
for n in obj.numbers:
assert type(n) == Number
if n.role == 'home':
assert n.number == "070-12345678"
if n.role == 'office':
assert n.number == "070-12345679"