使用集合。计数器:

>>> from collections import Counter
>>> A = Counter({'a':1, 'b':2, 'c':3})
>>> B = Counter({'b':3, 'c':4, 'd':5})
>>> A + B
Counter({'c': 7, 'b': 5, 'd': 5, 'a': 1})

计数器基本上是dict的一个子类，因此您仍然可以使用它们执行通常使用该类型执行的所有其他操作，例如遍历它们的键和值。

>>> A = {'a':1, 'b':2, 'c':3}
>>> B = {'b':3, 'c':4, 'd':5}
>>> c = {x: A.get(x, 0) + B.get(x, 0) for x in set(A).union(B)}
>>> print(c)

{'a': 1, 'c': 7, 'b': 5, 'd': 5}

上述解决方案非常适合具有少量计数器的场景。如果你有一个很大的列表，像这样的就更好了:

from collections import Counter

A = Counter({'a':1, 'b':2, 'c':3})
B = Counter({'b':3, 'c':4, 'd':5}) 
C = Counter({'a': 5, 'e':3})
list_of_counts = [A, B, C]

total = sum(list_of_counts, Counter())

print(total)
# Counter({'c': 7, 'a': 6, 'b': 5, 'd': 5, 'e': 3})

上述解决方案本质上是通过以下方法对计数器求和:

total = Counter()
for count in list_of_counts:
    total += count
print(total)
# Counter({'c': 7, 'a': 6, 'b': 5, 'd': 5, 'e': 3})

这个做的是同样的事情，但我认为它总是有助于看到它在下面有效地做了什么。

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}

dict1 = {'a':1, 'b':2, 'c':3}
dict2 = {'a':3, 'g':1, 'c':4}
dict3 = {} # will store new values

for x in dict1:
    
    if x in dict2: #sum values with same key
        dict3[x] = dict1[x] +dict2[x]
    else: #add the values from x to dict1
        dict3[x] = dict1[x]
        
#search for new values not in a
for x in dict2:
    if x not in dict1:
        dict3[x] = dict2[x]
print(dict3) # {'a': 4, 'b': 2, 'c': 7, 'g': 1}

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})