如果它们共享任何键值对,如何合并来自单独列表的多个词典?

How to merge multiple dictionaries from separate lists if they share any key-value pairs?

如果多个列表共享一个共同的键值对,如何合并它们?

例如,这里有三个字典列表:

l1 = [{'fruit':'banana','category':'B'},{'fruit':'apple','category':'A'}]
l2 = [{'type':'new','category':'A'},{'type':'old','category':'B'}]
l3 = [{'order':'2','type':'old'},{'order':'1','type':'new'}]

期望的结果:

l = [{'fruit':'apple','category':'A','order':'1','type':'new'},{'fruit':'banana','category':'B','order':'2','type':'old'}]

棘手的部分是我希望这个函数只接受列表作为参数而不是键,因为我只想插入任意数量的字典列表而不关心哪个键-名称是重叠的(在这种情况下,将所有三个名称组合在一起的键名是 'category' 和 'type')。

我要注意索引应该无关紧要,因为它只应基于公共元素。

这是我的尝试:

def combine_lists(*args):
    base_list = args[0]
    L = []
    for sublist in args[1:]:
        L.extend(sublist)
    for D in base_list:
        for Dict in L:
            if any([tup in Dict.items() for tup in D.items()]): 
                D.update(Dict)
    return base_list

对于这个问题,将字典视为元组列表很方便:

In [4]: {'fruit':'apple','category':'A'}.items()
Out[4]: [('category', 'A'), ('fruit', 'apple')]

由于我们希望连接共享一个键值对的字典,我们可以将每个 元组作为图中的节点,成对的元组作为边。一旦你有了图表 问题简化为找到图形的连通分量。

使用networkx,

import itertools as IT
import networkx as nx

l1 = [{'fruit':'apple','category':'A'},{'fruit':'banana','category':'B'}]
l2 = [{'type':'new','category':'A'},{'type':'old','category':'B'}]
l3 = [{'order':'1','type':'new'},{'order':'2','type':'old'}]

data = [l1, l2, l3]
G = nx.Graph()
for dct in IT.chain.from_iterable(data):
    items = list(dct.items())
    node1 = node1[0]
    for node2 in items:
        G.add_edge(node1, node22)

for cc in nx.connected_component_subgraphs(G):
    print(dict(IT.chain.from_iterable(cc.edges())))

产量

{'category': 'A', 'fruit': 'apple', 'type': 'new', 'order': '1'}
{'category': 'B', 'fruit': 'banana', 'type': 'old', 'order': '2'}

如果你想删除 networkx 依赖,你可以使用,例如,pillmuncher's implementation:

import itertools as IT

def connected_components(neighbors):
    """
     (pillmuncher)
    """
    seen = set()
    def component(node):
        nodes = set([node])
        while nodes:
            node = nodes.pop()
            seen.add(node)
            nodes |= neighbors[node] - seen
            yield node
    for node in neighbors:
        if node not in seen:
            yield component(node)

l1 = [{'fruit':'apple','category':'A'},{'fruit':'banana','category':'B'}]
l2 = [{'type':'new','category':'A'},{'type':'old','category':'B'}]
l3 = [{'order':'1','type':'new'},{'order':'2','type':'old'}]

data = [l1, l2, l3]
G = {}
for dct in IT.chain.from_iterable(data):
    items = dct.items()
    node1 = items[0]
    for node2 in items[1:]:
        G.setdefault(node1, set()).add(node2)
        G.setdefault(node2, set()).add(node1)

for cc in connected_components(G):
    print(dict(cc))

打印出与上面相同的结果。