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
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__
其他回答
我最近遇到了“Box”库,它也做同样的事情。
安装命令:pip install python-box
例子:
from box import Box
mydict = {"key1":{"v1":0.375,
"v2":0.625},
"key2":0.125,
}
mydict = Box(mydict)
print(mydict.key1.v1)
我发现它比其他现有的库(如dotmap)更有效,当你有大量嵌套字典时,dotmap会产生python递归错误。
链接到图书馆和详细信息:https://pypi.org/project/python-box/
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.
使用SimpleNamespace:
>>> from types import SimpleNamespace
>>> d = dict(x=[1, 2], y=['a', 'b'])
>>> ns = SimpleNamespace(**d)
>>> ns.x
[1, 2]
>>> ns
namespace(x=[1, 2], y=['a', 'b'])
kaggle_environments使用的实现是一个名为structify的函数。
class Struct(dict):
def __init__(self, **entries):
entries = {k: v for k, v in entries.items() if k != "items"}
dict.__init__(self, entries)
self.__dict__.update(entries)
def __setattr__(self, attr, value):
self.__dict__[attr] = value
self[attr] = value
# Added benefit of cloning lists and dicts.
def structify(o):
if isinstance(o, list):
return [structify(o[i]) for i in range(len(o))]
elif isinstance(o, dict):
return Struct(**{k: structify(v) for k, v in o.items()})
return o
https://github.com/Kaggle/kaggle-environments/blob/master/kaggle_environments/utils.py
这可能有助于在《ConnectX》等游戏中测试AI模拟代理
from kaggle_environments import structify
obs = structify({ 'remainingOverageTime': 60, 'step': 0, 'mark': 1, 'board': [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]})
conf = structify({ 'timeout': 2, 'actTimeout': 2, 'agentTimeout': 60, 'episodeSteps': 1000, 'runTimeout': 1200, 'columns': 7, 'rows': 6, 'inarow': 4, '__raw_path__': '/kaggle_simulations/agent/main.py' })
def agent(obs, conf):
action = obs.step % conf.columns
return action
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)