I want to know if there's a more Pythonic way of doing the following, perhaps using dictionary comprehensions:
A = some list
D = {}
for i,v in enumerate(A):
if v in D:
D[v].append(i)
else:
D[v] = [i]
I want to know if there's a more Pythonic way of doing the following, perhaps using dictionary comprehensions:
A = some list
D = {}
for i,v in enumerate(A):
if v in D:
D[v].append(i)
else:
D[v] = [i]
Using defaultdict
:
from collections import defaultdict
D = defaultdict(list)
[D[v].append(i) for i, v in enumerate(A)]
Using setdefault
:
D = {}
[D.setdefault(v, []).append(i) for i, v in enumerate(A)]
I can't figure any mean to use a dictionnary comprehension without sorting the data:
from itertools import groupby
from operator import itemgetter
{v: ids for v, ids in groupby(enumerate(sorted(A)), itemgetter(1))}
Performances:
from collections import defaultdict
from itertools import groupby
from operator import itemgetter
from random import randint
A = tuple(randint(0, 100) for _ in range(1000))
def one():
D = defaultdict(list)
[D[v].append(i) for i, v in enumerate(A)]
def two():
D = {}
[D.setdefault(v, []).append(i) for i, v in enumerate(A)]
def three():
{v: ids for v, ids in groupby(enumerate(sorted(A)), itemgetter(1))}
from timeit import timeit
for func in (one, two, three):
print(func.__name__ + ':', timeit(func, number=1000))
Results (as always, the simplest win):
one: 0.25547646999984863
two: 0.3754340969971963
three: 0.5032370890003222
You can do the following
d = collections.defaultdict(list)
for i,v in enumerate(A):
d[v].append(i)
You can see that the values of the resulting dictionary are list
s, the elements of which are to be produced while traversing. If you insist on doing a dict comp, you have to first find all the (value, [indices])
, then do a dict comp on [(k,[v])]
, which just means extra acrobatics without any benefit.