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Processing time of dictionary

I have a dictionary like this:
first_dict={‘cat’:[‘dog’, ‘cat’], ‘dog’:[‘cat’],’mouse’:[‘rabbit’], ‘rabbit’:[‘whale’]}

I want to output the dictionary in the following way:
output_dict = {‘dog’:[‘cat’, ‘dog’], ‘cat’:[‘dog’],’mouse’:[‘rabbit’], ‘rabbit’:[‘whale’]}

(notice the ‘cat’ and ‘dog’ are in the same groups)
I understand that I could iterate all the keys and group by the key value. Or iterate keys and compare the key strings.
I was wondering, which of these two solutions is better in terms of performance?

You can use collections.Counter to group:
from collections import Counter
output_dict = Counter(first_dict)

to get
Counter({‘cat’: 2, ‘dog’: 2,’mouse’: 1, ‘rabbit’: 1})

To sort with respect to value in this case, use OrderedDict:
from collections import OrderedDict
ordered_dict = OrderedDict(sorted(first_dict.items(), key=lambda x: x[1]))

to get
OrderedDict([(‘cat’, [(‘dog’, ‘cat’), (‘cat’, ‘dog’)]), (‘dog’, [‘cat’, ‘dog’]), (‘mouse’, [‘rabbit’]), (‘rabbit’, [‘whale’])])

Counter only supports strings, ordered_dict supports tuples

Bones Pro 421 Crack !!EXCLUSIVE!!

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