List of dictionaries:
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'}
}, ...
]
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'}]
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'}]
I am looking for the fastest solution.
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'}]
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]
Note:
RoadRunner's loop-and-update approach outperforms both these one-liners at timeit: ~1.37
You can do this with 2 nested loops, and dict.update()
to add inner dictionaries to a temporary dictionary and add it at the end:
L = []
for d in data:
temp = {}
for key in d:
temp.update(d[key])
L.append(temp)
# timeit ~1.4
print(L)
Which Outputs:
[{'l': 'Apple', 'b': 'Milk', 'd': 'Meatball', 'favourite': 'coke', 'dislike': 'juice'}, {'l': 'Apple1', 'b': 'Milk1', 'd': 'Meatball2', 'favourite': 'coke2', 'dislike': 'juice3'}]
You can use functools.reduce
along with a simple list comprehension to flatten out the list the of dicts
>>> from functools import reduce
>>> data = [{'b': {'dislike': 'juice', 'favourite': 'coke'}, 'a': {'l': 'Apple', 'b': 'Milk', 'd': 'Meatball'}}, {'b': {'dislike': 'juice3', 'favourite': 'coke2'}, 'a': {'l': 'Apple1', 'b': 'Milk1', 'd': 'Meatball2'}}]
>>> [reduce(lambda x,y: {**x,**y},d.values()) for d in data]
>>> [{'dislike': 'juice', 'l': 'Apple', 'd': 'Meatball', 'b': 'Milk', 'favourite': 'coke'}, {'dislike': 'juice3', 'l': 'Apple1', 'd': 'Meatball2', 'b': 'Milk1', 'favourite': 'coke2'}]
Time benchmark is as follows:
>>> import timeit
>>> setup = """
from functools import reduce
data = [{'b': {'dislike': 'juice', 'favourite': 'coke'}, 'a': {'l': 'Apple', 'b': 'Milk', 'd': 'Meatball'}}, {'b': {'dislike': 'juice3', 'favourite': 'coke2'}, 'a': {'l': 'Apple1', 'b': 'Milk1', 'd': 'Meatball2'}}]
"""
>>> min(timeit.Timer("[reduce(lambda x,y: {**x,**y},d.values()) for d in data]",setup=setup).repeat(3,1000000))
>>> 1.525032774952706
Time benchmark of other answers on my machine
>>> setup = """
data = [{'b': {'dislike': 'juice', 'favourite': 'coke'}, 'a': {'l': 'Apple', 'b': 'Milk', 'd': 'Meatball'}}, {'b': {'dislike': 'juice3', 'favourite': 'coke2'}, 'a': {'l': 'Apple1', 'b': 'Milk1', 'd': 'Meatball2'}}]
"""
>>> min(timeit.Timer("[{k: v for x in d.values() for k, v in x.items()} for d in data]",setup=setup).repeat(3,1000000))
>>> 2.2488374650129117
>>> min(timeit.Timer("[{k: x[k] for x in d.values() for k in x} for d in data]",setup=setup).repeat(3,1000000))
>>> 1.8990078769857064
>>> code = """
L = []
for d in data:
temp = {}
for key in d:
temp.update(d[key])
L.append(temp)
"""
>>> min(timeit.Timer(code,setup=setup).repeat(3,1000000))
>>> 1.4258553800173104
>>> setup = """
from itertools import chain
data = [{'b': {'dislike': 'juice', 'favourite': 'coke'}, 'a': {'l': 'Apple', 'b': 'Milk', 'd': 'Meatball'}}, {'b': {'dislike': 'juice3', 'favourite': 'coke2'}, 'a': {'l': 'Apple1', 'b': 'Milk1', 'd': 'Meatball2'}}]
"""
>>> min(timeit.Timer("[dict(chain(*map(dict.items, d.values()))) for d in data]",setup=setup).repeat(3,1000000))
>>> 3.774383604992181
If you have nested dictionaries with only 'a' and 'b' keys, then I suggest the following solution I find fast and very easy to understand (for readability purpose):
L = [x['a'] for x in data]
b = [x['b'] for x in data]
for i in range(len(L)):
L[i].update(b[i])
# timeit ~1.4
print(L)