嘿，我也有同样的问题，但我想出了一个解决方案，我会把它贴在这里，以防它对其他人也有用，基本上合并嵌套字典和添加值，对我来说，我需要计算一些概率，所以这一个工作得很好:

#used to copy a nested dict to a nested dict
def deepupdate(target, src):
    for k, v in src.items():
        if k in target:
            for k2, v2 in src[k].items():
                if k2 in target[k]:
                    target[k][k2]+=v2
                else:
                    target[k][k2] = v2
        else:
            target[k] = copy.deepcopy(v)

通过使用上述方法，我们可以合并:

目标={6 6:{“63”:1},“63,4:{4 4:1},4,4:{“4 3”:1},“63”:{63,4:1}}

src ={5 4:{4 4: 1}, 5、5:{“5、4”:1},4,4:{“4 3”:1}}

这将变成: {', 5 ':{“5、4”:1},“5、4”:{4 4:1},“6 6”:{“63”:1},“63,4:{4 4:1},4,4:{“4 3”:2},“63”:{63,4:1}}

还要注意这里的变化:

目标={6 6:{“63”:1},“63”:{63,4:1},4,4:{“4 3”:1},“63,4:{4 4:1}}

src ={5 4:{4 4: 1},“4 3”:{“3、4”:1},4,4:{“4、9”:1},3、4:{4 4:1},5、5:{“5、4”:1}}

merge =可不,‘五,四’:可不,‘4、4’:一个出于美观,‘4、三’:可不,‘3、4”:一个有关联,“6、63”:可不,‘63倍或四’:一个出于美观,‘5、5:可不,' 5、4”:一个有关联,“6、6”:可不,‘6、63’:一个出于美观,‘3,4‘:可不,‘四,四’:一个出于美观,‘63倍或四’一‘::可不,‘四,四出于美观,‘4,4:可不,’‘四,三’:一,‘4 9,‘:一个出于美观出于美观。

别忘了还添加导入copy:

import copy

这实际上是相当棘手的-特别是如果你想要一个有用的错误消息时，事情是不一致的，同时正确地接受重复但一致的条目(这是这里没有其他答案做的..)。

假设你没有大量的条目，递归函数是最简单的:

from functools import reduce

def merge(a, b, path=None):
    "merges b into a"
    if path is None: path = []
    for key in b:
        if key in a:
            if isinstance(a[key], dict) and isinstance(b[key], dict):
                merge(a[key], b[key], path + [str(key)])
            elif a[key] == b[key]:
                pass # same leaf value
            else:
                raise Exception('Conflict at %s' % '.'.join(path + [str(key)]))
        else:
            a[key] = b[key]
    return a

# works
print(merge({1:{"a":"A"},2:{"b":"B"}}, {2:{"c":"C"},3:{"d":"D"}}))
# has conflict
merge({1:{"a":"A"},2:{"b":"B"}}, {1:{"a":"A"},2:{"b":"C"}})

注意，这会使a发生变化——b的内容被添加到a(也会返回a)。如果你想保留a，你可以叫它merge(dict(a) b)

Agf指出(下面)，你可能有两个以上的字典，在这种情况下，你可以使用:

reduce(merge, [dict1, dict2, dict3...])

所有内容都将被添加到dict1中。

注意:我编辑了我的初始答案以改变第一个参数;这使得“reduce”更容易解释

Short-n-sweet:

from collections.abc import MutableMapping as Map

def nested_update(d, v):
"""
Nested update of dict-like 'd' with dict-like 'v'.
"""

for key in v:
    if key in d and isinstance(d[key], Map) and isinstance(v[key], Map):
        nested_update(d[key], v[key])
    else:
        d[key] = v[key]

这类似于(并且构建在)Python的字典上。更新方法。它返回None(如果你喜欢，你总是可以添加返回d)，因为它在原地更新dict d。v中的键将覆盖d中任何现有的键(它不会尝试解释字典的内容)。

它也适用于其他(“类字典”)映射。

我有一个迭代的解决方案-工作得更好的大字典&很多(例如jsons等):

import collections


def merge_dict_with_subdicts(dict1: dict, dict2: dict) -> dict:
    """
    similar behaviour to builtin dict.update - but knows how to handle nested dicts
    """
    q = collections.deque([(dict1, dict2)])
    while len(q) > 0:
        d1, d2 = q.pop()
        for k, v in d2.items():
            if k in d1 and isinstance(d1[k], dict) and isinstance(v, dict):
                q.append((d1[k], v))
            else:
                d1[k] = v

    return dict1

注意，这将使用d2中的值来覆盖d1，以防它们都不是字典。(与python的dict.update()相同)

一些测试:

def test_deep_update():
    d = dict()
    merge_dict_with_subdicts(d, {"a": 4})
    assert d == {"a": 4}

    new_dict = {
        "b": {
            "c": {
                "d": 6
            }
        }
    }
    merge_dict_with_subdicts(d, new_dict)
    assert d == {
        "a": 4,
        "b": {
            "c": {
                "d": 6
            }
        }
    }

    new_dict = {
        "a": 3,
        "b": {
            "f": 7
        }
    }
    merge_dict_with_subdicts(d, new_dict)
    assert d == {
        "a": 3,
        "b": {
            "c": {
                "d": 6
            },
            "f": 7
        }
    }

    # test a case where one of the dicts has dict as value and the other has something else
    new_dict = {
        'a': {
            'b': 4
        }
    }
    merge_dict_with_subdicts(d, new_dict)
    assert d['a']['b'] == 4

我已经测试了大约1200个字典——这种方法花了0.4秒，而递归的解决方案花了2.5秒。

from collections import defaultdict
from itertools import chain

class DictHelper:

@staticmethod
def merge_dictionaries(*dictionaries, override=True):
    merged_dict = defaultdict(set)
    all_unique_keys = set(chain(*[list(dictionary.keys()) for dictionary in dictionaries]))  # Build a set using all dict keys
    for key in all_unique_keys:
        keys_value_type = list(set(filter(lambda obj_type: obj_type != type(None), [type(dictionary.get(key, None)) for dictionary in dictionaries])))
        # Establish the object type for each key, return None if key is not present in dict and remove None from final result
        if len(keys_value_type) != 1:
            raise Exception("Different objects type for same key: {keys_value_type}".format(keys_value_type=keys_value_type))

        if keys_value_type[0] == list:
            values = list(chain(*[dictionary.get(key, []) for dictionary in dictionaries]))  # Extract the value for each key
            merged_dict[key].update(values)

        elif keys_value_type[0] == dict:
            # Extract all dictionaries by key and enter in recursion
            dicts_to_merge = list(filter(lambda obj: obj != None, [dictionary.get(key, None) for dictionary in dictionaries]))
            merged_dict[key] = DictHelper.merge_dictionaries(*dicts_to_merge)

        else:
            # if override => get value from last dictionary else make a list of all values
            values = list(filter(lambda obj: obj != None, [dictionary.get(key, None) for dictionary in dictionaries]))
            merged_dict[key] = values[-1] if override else values

    return dict(merged_dict)



if __name__ == '__main__':
  d1 = {'aaaaaaaaa': ['to short', 'to long'], 'bbbbb': ['to short', 'to long'], "cccccc": ["the is a test"]}
  d2 = {'aaaaaaaaa': ['field is not a bool'], 'bbbbb': ['field is not a bool']}
  d3 = {'aaaaaaaaa': ['filed is not a string', "to short"], 'bbbbb': ['field is not an integer']}
  print(DictHelper.merge_dictionaries(d1, d2, d3))

  d4 = {"a": {"x": 1, "y": 2, "z": 3, "d": {"x1": 10}}}
  d5 = {"a": {"x": 10, "y": 20, "d": {"x2": 20}}}
  print(DictHelper.merge_dictionaries(d4, d5))

输出:

{'bbbbb': {'to long', 'field is not an integer', 'to short', 'field is not a bool'}, 
'aaaaaaaaa': {'to long', 'to short', 'filed is not a string', 'field is not a bool'}, 
'cccccc': {'the is a test'}}

{'a': {'y': 20, 'd': {'x1': 10, 'x2': 20}, 'z': 3, 'x': 10}}

还有一个轻微的变化:

下面是一个纯粹的基于python3集的深度更新函数。它通过一次循环遍历一层来更新嵌套字典，并调用自己来更新下一层的字典值:

def deep_update(dict_original, dict_update):
    if isinstance(dict_original, dict) and isinstance(dict_update, dict):
        output=dict(dict_original)
        keys_original=set(dict_original.keys())
        keys_update=set(dict_update.keys())
        similar_keys=keys_original.intersection(keys_update)
        similar_dict={key:deep_update(dict_original[key], dict_update[key]) for key in similar_keys}
        new_keys=keys_update.difference(keys_original)
        new_dict={key:dict_update[key] for key in new_keys}
        output.update(similar_dict)
        output.update(new_dict)
        return output
    else:
        return dict_update

举个简单的例子:

x={'a':{'b':{'c':1, 'd':1}}}
y={'a':{'b':{'d':2, 'e':2}}, 'f':2}

print(deep_update(x, y))
>>> {'a': {'b': {'c': 1, 'd': 2, 'e': 2}}, 'f': 2}