通过pip安装dotmap

pip install dotmap

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 dotmap import DotMap

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

最重要的是，你可以将它转换为dict对象:

d = m.toDict()
m = DotMap(d) # automatic conversion in constructor

这意味着如果你想访问的东西已经是字典形式的，你可以把它转换成DotMap来方便访问:

import json
jsonDict = json.loads(text)
data = DotMap(jsonDict)
print data.location.city

最后，它会自动创建新的子DotMap实例，你可以这样做:

m = DotMap()
m.people.steve.age = 31

与Bunch的比较

完全公开:我是DotMap的创造者。我创建它是因为Bunch缺少这些功能

记住添加的顺序项并按此顺序迭代 自动创建子DotMap，当你有很多层次结构时，这节省了时间，并使代码更干净 从字典构造并递归地将所有子字典实例转换为DotMap

我的观点:出于我自己的目的，我开发了minydra，一个简单的命令行解析器，包括一个自定义类MinyDict(灵感来自addict):

In [1]: from minydra import MinyDict

In [2]: args = MinyDict({"foo": "bar", "yes.no.maybe": "idontknow"}).pretty_print(); args
╭──────────────────────────────╮
│ foo          : bar           │
│ yes.no.maybe : idontknow     │
╰──────────────────────────────╯
Out[2]: {'foo': 'bar', 'yes.no.maybe': 'idontknow'}

In [3]: args.resolve().pretty_print(); args
╭──────────────────────────╮
│ foo : bar                │
│ yes                      │
│ │no                      │
│ │ │maybe : idontknow     │
╰──────────────────────────╯
Out[3]: {'foo': 'bar', 'yes': {'no': {'maybe': 'idontknow'}}}

In [4]: args.yes.no.maybe
Out[4]: "idontknow"

In [5]: "foo" in args
Out[5]: True

In [6]: "rick" in args
Out[6]: False

In [7]: args.morty is None
Out[7]: True

In [8]: args.items()
Out[8]: dict_items([('foo', 'bar'), ('yes', {'no': {'maybe': 'idontknow'}})])

它通过向json yaml和pickle添加转储/加载方法来上瘾，并且在MinyDict.update()中也有一个严格的模式来防止创建新键(这对于防止命令行中的错字很有用)

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__。

您可以使用SimpleNamespace来实现这一点

from types import SimpleNamespace
# Assign values
args = SimpleNamespace()
args.username = 'admin'

# Retrive values
print(args.username)  # output: admin

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