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。

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)

如果有人想要另一种方法来解决这个问题，这是我的解决方案。

优点:简洁、声明性和函数式风格(递归，没有突变)。

潜在缺点:这可能不是你想要的合并。查阅文档字符串以了解语义。

def deep_merge(a, b):
    """
    Merge two values, with `b` taking precedence over `a`.

    Semantics:
    - If either `a` or `b` is not a dictionary, `a` will be returned only if
      `b` is `None`. Otherwise `b` will be returned.
    - If both values are dictionaries, they are merged as follows:
        * Each key that is found only in `a` or only in `b` will be included in
          the output collection with its value intact.
        * For any key in common between `a` and `b`, the corresponding values
          will be merged with the same semantics.
    """
    if not isinstance(a, dict) or not isinstance(b, dict):
        return a if b is None else b
    else:
        # If we're here, both a and b must be dictionaries or subtypes thereof.

        # Compute set of all keys in both dictionaries.
        keys = set(a.keys()) | set(b.keys())

        # Build output dictionary, merging recursively values with common keys,
        # where `None` is used to mean the absence of a value.
        return {
            key: deep_merge(a.get(key), b.get(key))
            for key in keys
        }

这个问题的一个问题是字典的值可以是任意复杂的数据块。基于这些和其他答案，我得出了以下代码:

class YamlReaderError(Exception):
    pass

def data_merge(a, b):
    """merges b into a and return merged result

    NOTE: tuples and arbitrary objects are not handled as it is totally ambiguous what should happen"""
    key = None
    # ## debug output
    # sys.stderr.write("DEBUG: %s to %s\n" %(b,a))
    try:
        if a is None or isinstance(a, str) or isinstance(a, unicode) or isinstance(a, int) or isinstance(a, long) or isinstance(a, float):
            # border case for first run or if a is a primitive
            a = b
        elif isinstance(a, list):
            # lists can be only appended
            if isinstance(b, list):
                # merge lists
                a.extend(b)
            else:
                # append to list
                a.append(b)
        elif isinstance(a, dict):
            # dicts must be merged
            if isinstance(b, dict):
                for key in b:
                    if key in a:
                        a[key] = data_merge(a[key], b[key])
                    else:
                        a[key] = b[key]
            else:
                raise YamlReaderError('Cannot merge non-dict "%s" into dict "%s"' % (b, a))
        else:
            raise YamlReaderError('NOT IMPLEMENTED "%s" into "%s"' % (b, a))
    except TypeError, e:
        raise YamlReaderError('TypeError "%s" in key "%s" when merging "%s" into "%s"' % (e, key, b, a))
    return a

我的用例是合并YAML文件，其中我只需要处理可能的数据类型的子集。因此我可以忽略元组和其他对象。对我来说，合理的合并逻辑意味着

取代标量 添加列表 通过添加缺失键和更新现有键来合并字典

其他任何事情和不可预见的事情都会导致错误。

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。

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