我已经编写了一个deepextract包，它完全符合您的要求:https://github.com/ya332/deepextract 你可以这样做

from deepextract import deepextract
# Demo: deepextract.extract_key(obj, key)
deeply_nested_dict = {
    "items": {
        "item": {
            "id": {
                "type": {
                    "donut": {
                        "name": {
                            "batters": {
                                "my_target_key": "my_target_value"
                            }
                        }
                    }
                }
            }
        }
    }
}
print(deepextract.extract_key(deeply_nested_dict, "my_target_key") == "my_target_value")

返回

True

通过把所有这些答案和我做的小改变结合起来，我认为这个函数会很有用。安全、快捷、易于维护。

def deep_get(dictionary, keys, default=None):
    return reduce(lambda d, key: d.get(key, default) if isinstance(d, dict) else default, keys.split("."), dictionary)

例子:

from functools import reduce
def deep_get(dictionary, keys, default=None):
    return reduce(lambda d, key: d.get(key, default) if isinstance(d, dict) else default, keys.split("."), dictionary)

person = {'person':{'name':{'first':'John'}}}
print(deep_get(person, "person.name.first"))    # John

print(deep_get(person, "person.name.lastname")) # None

print(deep_get(person, "person.name.lastname", default="No lastname"))  # No lastname

还有一个相同功能的函数，也返回一个布尔值来表示是否找到键，并处理一些意想不到的错误。

'''
json : json to extract value from if exists
path : details.detail.first_name
            empty path represents root

returns a tuple (boolean, object)
        boolean : True if path exists, otherwise False
        object : the object if path exists otherwise None

'''
def get_json_value_at_path(json, path=None, default=None):

    if not bool(path):
        return True, json
    if type(json) is not dict :
        raise ValueError(f'json={json}, path={path} not supported, json must be a dict')
    if type(path) is not str and type(path) is not list:
        raise ValueError(f'path format {path} not supported, path can be a list of strings like [x,y,z] or a string like x.y.z')

    if type(path) is str:
        path = path.strip('.').split('.')
    key = path[0]
    if key in json.keys():
        return get_json_value_at_path(json[key], path[1:], default)
    else:
        return False, default

使用示例:

my_json = {'details' : {'first_name' : 'holla', 'last_name' : 'holla'}}
print(get_json_value_at_path(my_json, 'details.first_name', ''))
print(get_json_value_at_path(my_json, 'details.phone', ''))

(真的,大声叫) (假的,”)

def safeget(_dct, *_keys):
    if not isinstance(_dct, dict): raise TypeError("Is not instance of dict")
    def foo(dct, *keys):
        if len(keys) == 0: return dct
        elif not isinstance(_dct, dict): return None
        else: return foo(dct.get(keys[0], None), *keys[1:])
    return foo(_dct, *_keys)

assert safeget(dict()) == dict()
assert safeget(dict(), "test") == None
assert safeget(dict([["a", 1],["b", 2]]),"a", "d") == None
assert safeget(dict([["a", 1],["b", 2]]),"a") == 1
assert safeget({"a":{"b":{"c": 2}},"d":1}, "a", "b")["c"] == 2

Glom是一个很好的库，可以进入点查询:

In [1]: from glom import glom

In [2]: data = {'a': {'b': {'c': 'd'}}}

In [3]: glom(data, "a.b.c")
Out[3]: 'd'

查询失败有一个很好的堆栈跟踪，指出确切的故障点:

In [4]: glom(data, "a.b.foo")
---------------------------------------------------------------------------
PathAccessError                           Traceback (most recent call last)
<ipython-input-4-2a3467493ac4> in <module>
----> 1 glom(data, "a.b.foo")

~/.cache/pypoetry/virtualenvs/neural-knapsack-dE7ihQtM-py3.8/lib/python3.8/site-packages/glom/core.py in glom(target, spec, **kwargs)
   2179 
   2180     if err:
-> 2181         raise err
   2182     return ret
   2183 

PathAccessError: error raised while processing, details below.
 Target-spec trace (most recent last):
 - Target: {'a': {'b': {'c': 'd'}}}
 - Spec: 'a.b.foo'
glom.core.PathAccessError: could not access 'foo', part 2 of Path('a', 'b', 'foo'), got error: KeyError('foo')

默认保护:

In [5]: glom(data, "a.b.foo", default="spam")
Out[5]: 'spam'

格洛姆的魅力在于多功能的规格参数。例如，可以很容易地从以下数据中提取所有的名字:

In [8]: data = {
   ...:     "people": [
   ...:         {"first_name": "Alice", "last_name": "Adams"},
   ...:         {"first_name": "Bob", "last_name": "Barker"}
   ...:     ]
   ...: }

In [9]: glom(data, ("people", ["first_name"]))
Out[9]: ['Alice', 'Bob']

更多的例子请阅读glom文档。

递归解。它不是最有效的，但我发现它比其他示例更具可读性，而且它不依赖于functools。

def deep_get(d, keys):
    if not keys or d is None:
        return d
    return deep_get(d.get(keys[0]), keys[1:])

例子

d = {'meta': {'status': 'OK', 'status_code': 200}}
deep_get(d, ['meta', 'status_code'])     # => 200
deep_get(d, ['garbage', 'status_code'])  # => None

一个更精致的版本

def deep_get(d, keys, default=None):
    """
    Example:
        d = {'meta': {'status': 'OK', 'status_code': 200}}
        deep_get(d, ['meta', 'status_code'])          # => 200
        deep_get(d, ['garbage', 'status_code'])       # => None
        deep_get(d, ['meta', 'garbage'], default='-') # => '-'
    """
    assert type(keys) is list
    if d is None:
        return default
    if not keys:
        return d
    return deep_get(d.get(keys[0]), keys[1:], default)