这是我做的递归合并字典到无限深度的解决方案。传递给函数的第一个字典是主字典——其中的值将覆盖第二个字典中相同键的值。

def merge(dict1: dict, dict2: dict) -> dict:
    merged = dict1

    for key in dict2:
        if type(dict2[key]) == dict:
            merged[key] = merge(dict1[key] if key in dict1 else {}, dict2[key])
        else:
            if key not in dict1.keys():
                merged[key] = dict2[key]

    return merged

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}}

这个版本的函数将处理N个字典，并且只处理字典——不能传递不恰当的参数，否则将引发TypeError。合并本身解释了键冲突，它不是覆盖来自合并链下的字典的数据，而是创建一组值并追加到该值;没有数据丢失。

它可能不是页面上最有效的，但它是最彻底的，当你合并2到N字典时，你不会丢失任何信息。

def merge_dicts(*dicts):
    if not reduce(lambda x, y: isinstance(y, dict) and x, dicts, True):
        raise TypeError, "Object in *dicts not of type dict"
    if len(dicts) < 2:
        raise ValueError, "Requires 2 or more dict objects"


    def merge(a, b):
        for d in set(a.keys()).union(b.keys()):
            if d in a and d in b:
                if type(a[d]) == type(b[d]):
                    if not isinstance(a[d], dict):
                        ret = list({a[d], b[d]})
                        if len(ret) == 1: ret = ret[0]
                        yield (d, sorted(ret))
                    else:
                        yield (d, dict(merge(a[d], b[d])))
                else:
                    raise TypeError, "Conflicting key:value type assignment"
            elif d in a:
                yield (d, a[d])
            elif d in b:
                yield (d, b[d])
            else:
                raise KeyError

    return reduce(lambda x, y: dict(merge(x, y)), dicts[1:], dicts[0])

print merge_dicts({1:1,2:{1:2}},{1:2,2:{3:1}},{4:4})

输出:{1:[1,2]，2:{1:2,3:1}，4:4}

在不影响输入字典的情况下返回一个合并。

def _merge_dicts(dictA: Dict = {}, dictB: Dict = {}) -> Dict:
    # it suffices to pass as an argument a clone of `dictA`
    return _merge_dicts_aux(dictA, dictB, copy(dictA))


def _merge_dicts_aux(dictA: Dict = {}, dictB: Dict = {}, result: Dict = {}, path: List[str] = None) -> Dict:

    # conflict path, None if none
    if path is None:
        path = []

    for key in dictB:

        # if the key doesn't exist in A, add the B element to A
        if key not in dictA:
            result[key] = dictB[key]

        else:
            # if the key value is a dict, both in A and in B, merge the dicts
            if isinstance(dictA[key], dict) and isinstance(dictB[key], dict):
                _merge_dicts_aux(dictA[key], dictB[key], result[key], path + [str(key)])

            # if the key value is the same in A and in B, ignore
            elif dictA[key] == dictB[key]:
                pass

            # if the key value differs in A and in B, raise error
            else:
                err: str = f"Conflict at {'.'.join(path + [str(key)])}"
                raise Exception(err)

    return result

灵感来自@andrew cooke的解决方案

我一直在测试你的解决方案，并决定在我的项目中使用这个:

def mergedicts(dict1, dict2, conflict, no_conflict):
    for k in set(dict1.keys()).union(dict2.keys()):
        if k in dict1 and k in dict2:
            yield (k, conflict(dict1[k], dict2[k]))
        elif k in dict1:
            yield (k, no_conflict(dict1[k]))
        else:
            yield (k, no_conflict(dict2[k]))

dict1 = {1:{"a":"A"}, 2:{"b":"B"}}
dict2 = {2:{"c":"C"}, 3:{"d":"D"}}

#this helper function allows for recursion and the use of reduce
def f2(x, y):
    return dict(mergedicts(x, y, f2, lambda x: x))

print dict(mergedicts(dict1, dict2, f2, lambda x: x))
print dict(reduce(f2, [dict1, dict2]))

将函数作为参数传递是将jterrace解决方案扩展为所有其他递归解决方案的关键。

换个答案怎么样?!?这也避免了突变/副作用:

def merge(dict1, dict2):
    output = {}

    # adds keys from `dict1` if they do not exist in `dict2` and vice-versa
    intersection = {**dict2, **dict1}

    for k_intersect, v_intersect in intersection.items():
        if k_intersect not in dict1:
            v_dict2 = dict2[k_intersect]
            output[k_intersect] = v_dict2

        elif k_intersect not in dict2:
            output[k_intersect] = v_intersect

        elif isinstance(v_intersect, dict):
            v_dict2 = dict2[k_intersect]
            output[k_intersect] = merge(v_intersect, v_dict2)

        else:
            output[k_intersect] = v_intersect

    return output

dict1 = {1:{"a":{"A"}}, 2:{"b":{"B"}}}
dict2 = {2:{"c":{"C"}}, 3:{"d":{"D"}}}
dict3 = {1:{"a":{"A"}}, 2:{"b":{"B"},"c":{"C"}}, 3:{"d":{"D"}}}

assert dict3 == merge(dict1, dict2)