我需要合并多个字典,这是我有例如:
dict1 = {1:{"a":{A}}, 2:{"b":{B}}}
dict2 = {2:{"c":{C}}, 3:{"d":{D}}}
A、B、C和D是树的叶子,比如{"info1":"value", "info2":"value2"}
字典的级别(深度)未知,可能是{2:{"c":{"z":{"y":{c}}}}}
在我的例子中,它表示一个目录/文件结构,节点是文档,叶子是文件。
我想将它们合并得到:
dict3 = {1:{"a":{A}}, 2:{"b":{B},"c":{C}}, 3:{"d":{D}}}
我不确定如何用Python轻松做到这一点。
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。
def m(a,b):
aa = {
k : dict(a.get(k,{}), **v) for k,v in b.items()
}
aap = print(aa)
return aap
d1 = {1:{"a":"A"}, 2:{"b":"B"}}
d2 = {2:{"c":"C"}, 3:{"d":"D"}}
dict1 = {1:{"a":{1}}, 2:{"b":{2}}}
dict2 = {2:{"c":{222}}, 3:{"d":{3}}}
m(d1,d2)
m(dict1,dict2)
"""
Output :
{2: {'b': 'B', 'c': 'C'}, 3: {'d': 'D'}}
{2: {'b': {2}, 'c': {222}}, 3: {'d': {3}}}
"""
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)
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}