我正在寻找一种优雅的方式来获得数据使用属性访问字典与一些嵌套的字典和列表(即javascript风格的对象语法)。

例如:

>>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}

应该以这样的方式访问:

>>> x = dict2obj(d)
>>> x.a
1
>>> x.b.c
2
>>> x.d[1].foo
bar

我想,如果没有递归,这是不可能的,但是有什么更好的方法来获得字典的对象样式呢?


当前回答

如果你想访问dict键作为一个对象(或作为一个dict难键),做递归,也能够更新原来的dict,你可以这样做:

class Dictate(object):
    """Object view of a dict, updating the passed in dict when values are set
    or deleted. "Dictate" the contents of a dict...: """

    def __init__(self, d):
        # since __setattr__ is overridden, self.__dict = d doesn't work
        object.__setattr__(self, '_Dictate__dict', d)

    # Dictionary-like access / updates
    def __getitem__(self, name):
        value = self.__dict[name]
        if isinstance(value, dict):  # recursively view sub-dicts as objects
            value = Dictate(value)
        return value

    def __setitem__(self, name, value):
        self.__dict[name] = value
    def __delitem__(self, name):
        del self.__dict[name]

    # Object-like access / updates
    def __getattr__(self, name):
        return self[name]

    def __setattr__(self, name, value):
        self[name] = value
    def __delattr__(self, name):
        del self[name]

    def __repr__(self):
        return "%s(%r)" % (type(self).__name__, self.__dict)
    def __str__(self):
        return str(self.__dict)

使用示例:

d = {'a': 'b', 1: 2}
dd = Dictate(d)
assert dd.a == 'b'  # Access like an object
assert dd[1] == 2  # Access like a dict
# Updates affect d
dd.c = 'd'
assert d['c'] == 'd'
del dd.a
del dd[1]
# Inner dicts are mapped
dd.e = {}
dd.e.f = 'g'
assert dd['e'].f == 'g'
assert d == {'c': 'd', 'e': {'f': 'g'}}

其他回答

如果你的dict来自json.loads(),你可以在一行中将它转换为对象(而不是dict):

import json
from collections import namedtuple

json.loads(data, object_hook=lambda d: namedtuple('X', d.keys())(*d.values()))

请参见如何将JSON数据转换为Python对象。

如果只是将dict赋值给一个空对象的__dict__呢?

class Object:
    """If your dict is "flat", this is a simple way to create an object from a dict

    >>> obj = Object()
    >>> obj.__dict__ = d
    >>> d.a
    1
    """
    pass

当然,这在你嵌套的dict例子上失败了,除非你递归地遍历dict:

# For a nested dict, you need to recursively update __dict__
def dict2obj(d):
    """Convert a dict to an object

    >>> d = {'a': 1, 'b': {'c': 2}, 'd': ["hi", {'foo': "bar"}]}
    >>> obj = dict2obj(d)
    >>> obj.b.c
    2
    >>> obj.d
    ["hi", {'foo': "bar"}]
    """
    try:
        d = dict(d)
    except (TypeError, ValueError):
        return d
    obj = Object()
    for k, v in d.iteritems():
        obj.__dict__[k] = dict2obj(v)
    return obj

你的例子列表元素可能是一个映射,一个(键,值)对的列表,像这样:

>>> d = {'a': 1, 'b': {'c': 2}, 'd': [("hi", {'foo': "bar"})]}
>>> obj = dict2obj(d)
>>> obj.d.hi.foo
"bar"

I ended up trying BOTH the AttrDict and the Bunch libraries and found them to be way too 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。

下面的代码来自这里,适用于嵌套字典和ide,如VS code能够提示现有的属性:

class Struct:
    def __init__(self, **kwargs):
        for key, value in kwargs.items():
            if isinstance(value, dict):
                self.__dict__[key] = Struct(**value)
            else:
                self.__dict__[key] = value


my_dict = {
    'name': 'bobbyhadz',
    'address': {
        'country': 'Country A',
        'city': 'City A',
        'codes': [1, 2, 3]
    },
}

obj = Struct(**my_dict)

如果您想了解如何加载YAML文件并将其转换为Python对象,请参阅以下要点。

这是另一种将字典列表转换为对象的替代方法:

def dict2object(in_dict):
    class Struct(object):
        def __init__(self, in_dict):
            for key, value in in_dict.items():
                if isinstance(value, (list, tuple)):
                    setattr(
                        self, key,
                        [Struct(sub_dict) if isinstance(sub_dict, dict)
                         else sub_dict for sub_dict in value])
                else:
                    setattr(
                        self, key,
                        Struct(value) if isinstance(value, dict)
                        else value)
    return [Struct(sub_dict) for sub_dict in in_dict] \
        if isinstance(in_dict, list) else Struct(in_dict)