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

使用__getattr__,非常简单,适用于 Python 3.4.3

class myDict(dict):
    def __getattr__(self,val):
        return self[val]


blockBody=myDict()
blockBody['item1']=10000
blockBody['item2']="StackOverflow"
print(blockBody.item1)
print(blockBody.item2)

输出:

10000
StackOverflow

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'

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。

我不喜欢在(超过)10年前的火灾中添加另一个日志,但我也会检查dotwiz库,它是我最近发布的——实际上就在今年。

它是一个相对较小的库,在基准测试中,它在get(访问)和设置(创建)时间方面也表现得非常好,至少与其他备选方案相比是这样。

通过pip安装dotwiz

pip install dotwiz

它能做你想让它做的所有事情,并继承dict的子类,所以它的操作就像一个普通的字典:

from dotwiz import DotWiz

dw = DotWiz()
dw.hello = 'world'
dw.hello
dw.hello += '!'
# dw.hello and dw['hello'] now both return 'world!'
dw.val = 5
dw.val2 = 'Sam'

最重要的是,你可以将它转换为dict对象:

d = dw.to_dict()
dw = DotWiz(d) # automatic conversion in constructor

这意味着如果你想访问的东西已经是dict形式的,你可以把它变成一个dotwz来方便访问:

import json
json_dict = json.loads(text)
data = DotWiz(json_dict)
print data.location.city

最后,我正在做的一些令人兴奋的事情是一个现有的特性请求,这样它就会自动创建新的子DotWiz实例,这样你就可以做这样的事情:

dw = DotWiz()
dw['people.steve.age'] = 31

dw
# ✫(people=✫(steve=✫(age=31)))

与点图比较

我在下面添加了一个快速而粗略的性能比较。

首先,用pip安装两个库:

pip install dotwiz dotmap

为了进行基准测试,我编写了以下代码:

from timeit import timeit

from dotwiz import DotWiz
from dotmap import DotMap


d = {'hey': {'so': [{'this': {'is': {'pretty': {'cool': True}}}}]}}

dw = DotWiz(d)
# ✫(hey=✫(so=[✫(this=✫(is=✫(pretty={'cool'})))]))

dm = DotMap(d)
# DotMap(hey=DotMap(so=[DotMap(this=DotMap(is=DotMap(pretty={'cool'})))]))

assert dw.hey.so[0].this['is'].pretty.cool == dm.hey.so[0].this['is'].pretty.cool

n = 100_000

print('dotwiz (create):  ', round(timeit('DotWiz(d)', number=n, globals=globals()), 3))
print('dotmap (create):  ', round(timeit('DotMap(d)', number=n, globals=globals()), 3))
print('dotwiz (get):  ', round(timeit("dw.hey.so[0].this['is'].pretty.cool", number=n, globals=globals()), 3))
print('dotmap (get):  ', round(timeit("dm.hey.so[0].this['is'].pretty.cool", number=n, globals=globals()), 3))

结果,在我的M1 Mac上运行Python 3.10:

dotwiz (create):   0.189
dotmap (create):   1.085
dotwiz (get):   0.014
dotmap (get):   0.335

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
def dict_to_object(dick):
    # http://stackoverflow.com/a/1305663/968442

    class Struct:
        def __init__(self, **entries):
            self.__dict__.update(entries)

    return Struct(**dick)

如果一个人决定永久地将字典转换为对象,这应该做到。您可以在访问之前创建一个丢弃对象。

d = dict_to_object(d)