这是一个很一般的解。你可以处理任意数量的dict +键，只在一些dict +容易使用任何聚合函数你想要:

def aggregate_dicts(dicts, operation=sum):
    """Aggregate a sequence of dictionaries using `operation`."""
    all_keys = set().union(*[el.keys() for el in dicts])
    return {k: operation([dic.get(k, None) for dic in dicts]) for k in all_keys}

例子:

dicts_same_keys = [{'x': 0, 'y': 1}, {'x': 1, 'y': 2}, {'x': 2, 'y': 3}]
aggregate_dicts(dicts_same_keys, operation=sum)
#{'x': 3, 'y': 6}

不相同的键和泛型聚合示例:

dicts_diff_keys = [{'x': 0, 'y': 1}, {'x': 1, 'y': 2}, {'x': 2, 'y': 3, 'c': 4}]

def mean_no_none(l):
    l_no_none = [el for el in l if el is not None]
    return sum(l_no_none) / len(l_no_none)

aggregate_dicts(dicts_diff_keys, operation=mean_no_none)
# {'x': 1.0, 'c': 4.0, 'y': 2.0}

这是一个很一般的解。你可以处理任意数量的dict +键，只在一些dict +容易使用任何聚合函数你想要:

def aggregate_dicts(dicts, operation=sum):
    """Aggregate a sequence of dictionaries using `operation`."""
    all_keys = set().union(*[el.keys() for el in dicts])
    return {k: operation([dic.get(k, None) for dic in dicts]) for k in all_keys}

例子:

dicts_same_keys = [{'x': 0, 'y': 1}, {'x': 1, 'y': 2}, {'x': 2, 'y': 3}]
aggregate_dicts(dicts_same_keys, operation=sum)
#{'x': 3, 'y': 6}

不相同的键和泛型聚合示例:

dicts_diff_keys = [{'x': 0, 'y': 1}, {'x': 1, 'y': 2}, {'x': 2, 'y': 3, 'c': 4}]

def mean_no_none(l):
    l_no_none = [el for el in l if el is not None]
    return sum(l_no_none) / len(l_no_none)

aggregate_dicts(dicts_diff_keys, operation=mean_no_none)
# {'x': 1.0, 'c': 4.0, 'y': 2.0}

来自python 3.5:合并和求和

Thanks to @tokeinizer_fsj that told me in a comment that I didn't get completely the meaning of the question (I thought that add meant just adding keys that eventually where different in the two dictinaries and, instead, i meant that the common key values should be summed). So I added that loop before the merging, so that the second dictionary contains the sum of the common keys. The last dictionary will be the one whose values will last in the new dictionary that is the result of the merging of the two, so I thing the problem is solved. The solution is valid from python 3.5 and following versions.

a = {
    "a": 1,
    "b": 2,
    "c": 3
}

b = {
    "a": 2,
    "b": 3,
    "d": 5
}

# Python 3.5

for key in b:
    if key in a:
        b[key] = b[key] + a[key]

c = {**a, **b}
print(c)

>>> c
{'a': 3, 'b': 5, 'c': 3, 'd': 5}

可重用代码

a = {'a': 1, 'b': 2, 'c': 3}
b = {'b': 3, 'c': 4, 'd': 5}


def mergsum(a, b):
    for k in b:
        if k in a:
            b[k] = b[k] + a[k]
    c = {**a, **b}
    return c


print(mergsum(a, b))

明确地对Counter()求和是在这种情况下最python化的方法，但前提是它的结果为正值。下面是一个例子，正如你所看到的，在B字典中对c的值求负后，结果中没有c。

In [1]: from collections import Counter

In [2]: A = Counter({'a':1, 'b':2, 'c':3})

In [3]: B = Counter({'b':3, 'c':-4, 'd':5})

In [4]: A + B
Out[4]: Counter({'d': 5, 'b': 5, 'a': 1})

这是因为计数器主要用于使用正整数来表示运行计数(负计数是没有意义的)。但是为了帮助这些用例，python记录了最小范围和类型限制如下:

The Counter class itself is a dictionary subclass with no restrictions on its keys and values. The values are intended to be numbers representing counts, but you could store anything in the value field. The most_common() method requires only that the values be orderable. For in-place operations such as c[key] += 1, the value type need only support addition and subtraction. So fractions, floats, and decimals would work and negative values are supported. The same is also true for update() and subtract() which allow negative and zero values for both inputs and outputs. The multiset methods are designed only for use cases with positive values. The inputs may be negative or zero, but only outputs with positive values are created. There are no type restrictions, but the value type needs to support addition, subtraction, and comparison. The elements() method requires integer counts. It ignores zero and negative counts.

为了在Counter求和之后解决这个问题你可以使用Counter。更新以获得所需的输出。它的工作方式类似于dict.update()，但添加计数而不是替换它们。

In [24]: A.update(B)

In [25]: A
Out[25]: Counter({'d': 5, 'b': 5, 'a': 1, 'c': -1})

一个更通用的解决方案，它也适用于非数字值:

a = {'a': 'foo', 'b':'bar', 'c': 'baz'}
b = {'a': 'spam', 'c':'ham', 'x': 'blah'}

r = dict(a.items() + b.items() +
    [(k, a[k] + b[k]) for k in set(b) & set(a)])

或者更普通一点:

def combine_dicts(a, b, op=operator.add):
    return dict(a.items() + b.items() +
        [(k, op(a[k], b[k])) for k in set(b) & set(a)])

例如:

>>> a = {'a': 2, 'b':3, 'c':4}
>>> b = {'a': 5, 'c':6, 'x':7}

>>> import operator
>>> print combine_dicts(a, b, operator.mul)
{'a': 10, 'x': 7, 'c': 24, 'b': 3}

一种解决方法是使用字典理解。

C = { k: A.get(k,0) + B.get(k,0) for k in list(B.keys()) + list(A.keys()) }