Python-拼合字典列表 [英] Python - Flatten the list of dictionaries

问题描述

词典列表:

data = [{
         'a':{'l':'Apple',
                'b':'Milk',
                'd':'Meatball'},
         'b':{'favourite':'coke',
              'dislike':'juice'}
         },
         {
         'a':{'l':'Apple1',
                'b':'Milk1',
                'd':'Meatball2'},
         'b':{'favourite':'coke2',
              'dislike':'juice3'}
         }, ...
]

我需要加入所有嵌套的字典才能达到预期的输出:

I need to join all nested dictionaries to reach at the expected output:

 [{'d': 'Meatball', 'b': 'Milk', 'l': 'Apple', 'dislike': 'juice', 'favourite': 'coke'},
  {'d': 'Meatball2', 'b': 'Milk1', 'l': 'Apple1', 'dislike': 'juice3', 'favourite': 'coke2'}]

我尝试嵌套列表理解，但无法将dict结合在一起:

I try nested list comprehension, but cannot join dict together:

L = [y for x in data for y in x.values()]
print (L)

[{'d': 'Meatball', 'b': 'Milk', 'l': 'Apple'}, 
 {'dislike': 'juice', 'favourite': 'coke'}, 
{'d': 'Meatball2', 'b': 'Milk1', 'l': 'Apple1'}, 
 {'dislike': 'juice3', 'favourite': 'coke2'}]

我正在寻找最快的解决方案.

I am looking for the fastest solution.

推荐答案

您可以使用

You can do the following, using itertools.chain:

>>> from itertools import chain
# timeit: ~3.40
>>> [dict(chain(*map(dict.items, d.values()))) for d in data]
[{'l': 'Apple', 
  'b': 'Milk', 
  'd': 'Meatball', 
  'favourite': 'coke', 
  'dislike': 'juice'}, 
 {'l': 'Apple1', 
  'b': 'Milk1', 
  'dislike': 'juice3', 
  'favourite': 'coke2', 
  'd': 'Meatball2'}]

chain，map，*的用法使该表达式成为以下双重嵌套理解的简写，它实际上在我的系统上表现更好(Python 3.5.2)，并且不再那么长:

The usage of chain, map, * make this expression a shorthand for the following doubly nested comprehension which actually performs better on my system (Python 3.5.2) and isn't that much longer:

# timeit: ~2.04
[{k: v for x in d.values() for k, v in x.items()} for d in data]
# Or, not using items, but lookup by key
# timeit: ~1.67
[{k: x[k] for x in d.values() for k in x} for d in data]

注意:

RoadRunner的循环和更新方法在timeit: ~1.37

Note:

RoadRunner's loop-and-update approach outperforms both these one-liners at timeit: ~1.37

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