andrew cookes的回答有一个小问题:在某些情况下，当你修改返回的dict时，它会修改第二个参数b。具体来说是因为这句话:

if key in a:
    ...
else:
    a[key] = b[key]

如果b[key]是一个字典，它将被简单地赋给a，这意味着对该字典的任何后续修改将同时影响a和b。

a={}
b={'1':{'2':'b'}}
c={'1':{'3':'c'}}
merge(merge(a,b), c) # {'1': {'3': 'c', '2': 'b'}}
a # {'1': {'3': 'c', '2': 'b'}} (as expected)
b # {'1': {'3': 'c', '2': 'b'}} <----
c # {'1': {'3': 'c'}} (unmodified)

为了解决这个问题，这一行必须用这个替换:

if isinstance(b[key], dict):
    a[key] = clone_dict(b[key])
else:
    a[key] = b[key]

其中clone_dict为:

def clone_dict(obj):
    clone = {}
    for key, value in obj.iteritems():
        if isinstance(value, dict):
            clone[key] = clone_dict(value)
        else:
            clone[key] = value
    return

不动。这显然没有考虑到list, set和其他东西，但我希望它说明了合并字典时的陷阱。

为了完整起见，这里是我的版本，在那里你可以传递它多个字典:

def merge_dicts(*args):
    def clone_dict(obj):
        clone = {}
        for key, value in obj.iteritems():
            if isinstance(value, dict):
                clone[key] = clone_dict(value)
            else:
                clone[key] = value
        return

    def merge(a, b, 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
                else:
                    raise Exception('Conflict at `{path}\''.format(path='.'.join(path + [str(key)])))
            else:
                if isinstance(b[key], dict):
                    a[key] = clone_dict(b[key])
                else:
                    a[key] = b[key]
        return a
    return reduce(merge, args, {})

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。

概述

下面的方法将字典的深度合并问题细分为:

使用A的参数化浅归并函数merge(f)(A,b) 函数f归并两个字典a和b 与归并一起使用的递归归并函数f

实现

合并两个(非嵌套的)字典的函数可以用很多种方式编写。我个人喜欢

def merge(f):
    def merge(a,b): 
        keys = a.keys() | b.keys()
        return {key:f(a.get(key), b.get(key)) for key in keys}
    return merge

定义一个合适的递归归并函数f的一个好方法是使用multidispatch，它允许定义函数根据参数的类型沿着不同的路径求值。

from multipledispatch import dispatch

#for anything that is not a dict return
@dispatch(object, object)
def f(a, b):
    return b if b is not None else a

#for dicts recurse 
@dispatch(dict, dict)
def f(a,b):
    return merge(f)(a,b)

例子

要合并两个嵌套字典，只需使用merge(f)，例如:

dict1 = {1:{"a":"A"},2:{"b":"B"}}
dict2 = {2:{"c":"C"},3:{"d":"D"}}
merge(f)(dict1, dict2)
#returns {1: {'a': 'A'}, 2: {'b': 'B', 'c': 'C'}, 3: {'d': 'D'}} 

注:

这种方法的优点是:

该函数由较小的函数构建而成，每个函数只做一件事 这使得代码更容易推理和测试 这种行为不是硬编码的，但可以根据需要进行更改和扩展，从而提高代码重用(参见下面的示例)。

定制

一些答案还考虑了包含列表的字典，例如其他(可能嵌套的)字典。在这种情况下，可能需要映射列表并根据位置合并它们。这可以通过在归并函数f中添加另一个定义来实现:

import itertools
@dispatch(list, list)
def f(a,b):
    return [merge(f)(*arg) for arg in itertools.zip_longest(a, b)]

andrew cookes的回答有一个小问题:在某些情况下，当你修改返回的dict时，它会修改第二个参数b。具体来说是因为这句话:

if key in a:
    ...
else:
    a[key] = b[key]

如果b[key]是一个字典，它将被简单地赋给a，这意味着对该字典的任何后续修改将同时影响a和b。

a={}
b={'1':{'2':'b'}}
c={'1':{'3':'c'}}
merge(merge(a,b), c) # {'1': {'3': 'c', '2': 'b'}}
a # {'1': {'3': 'c', '2': 'b'}} (as expected)
b # {'1': {'3': 'c', '2': 'b'}} <----
c # {'1': {'3': 'c'}} (unmodified)

为了解决这个问题，这一行必须用这个替换:

if isinstance(b[key], dict):
    a[key] = clone_dict(b[key])
else:
    a[key] = b[key]

其中clone_dict为:

def clone_dict(obj):
    clone = {}
    for key, value in obj.iteritems():
        if isinstance(value, dict):
            clone[key] = clone_dict(value)
        else:
            clone[key] = value
    return

不动。这显然没有考虑到list, set和其他东西，但我希望它说明了合并字典时的陷阱。

为了完整起见，这里是我的版本，在那里你可以传递它多个字典:

def merge_dicts(*args):
    def clone_dict(obj):
        clone = {}
        for key, value in obj.iteritems():
            if isinstance(value, dict):
                clone[key] = clone_dict(value)
            else:
                clone[key] = value
        return

    def merge(a, b, 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
                else:
                    raise Exception('Conflict at `{path}\''.format(path='.'.join(path + [str(key)])))
            else:
                if isinstance(b[key], dict):
                    a[key] = clone_dict(b[key])
                else:
                    a[key] = b[key]
        return a
    return reduce(merge, args, {})

以下是来自@andrew cooke的回答。 它以更好的方式处理嵌套列表。

def deep_merge_lists(original, incoming):
    """
    Deep merge two lists. Modifies original.
    Recursively call deep merge on each correlated element of list. 
    If item type in both elements are
     a. dict: Call deep_merge_dicts on both values.
     b. list: Recursively call deep_merge_lists on both values.
     c. any other type: Value is overridden.
     d. conflicting types: Value is overridden.

    If length of incoming list is more that of original then extra values are appended.
    """
    common_length = min(len(original), len(incoming))
    for idx in range(common_length):
        if isinstance(original[idx], dict) and isinstance(incoming[idx], dict):
            deep_merge_dicts(original[idx], incoming[idx])

        elif isinstance(original[idx], list) and isinstance(incoming[idx], list):
            deep_merge_lists(original[idx], incoming[idx])

        else:
            original[idx] = incoming[idx]

    for idx in range(common_length, len(incoming)):
        original.append(incoming[idx])


def deep_merge_dicts(original, incoming):
    """
    Deep merge two dictionaries. Modifies original.
    For key conflicts if both values are:
     a. dict: Recursively call deep_merge_dicts on both values.
     b. list: Call deep_merge_lists on both values.
     c. any other type: Value is overridden.
     d. conflicting types: Value is overridden.

    """
    for key in incoming:
        if key in original:
            if isinstance(original[key], dict) and isinstance(incoming[key], dict):
                deep_merge_dicts(original[key], incoming[key])

            elif isinstance(original[key], list) and isinstance(incoming[key], list):
                deep_merge_lists(original[key], incoming[key])

            else:
                original[key] = incoming[key]
        else:
            original[key] = incoming[key]

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。