I have a dictionary, full of items. I want to peek at a single, arbitrary item:
print("Amongst our dictionary\'s items are such diverse elements as: %s&q
I believe the question has been significantly answered but hopefully this comparison will shed some light on the clean code vs time trade off:
from timeit import timeit
from random import choice
A = {x:[y for y in range(100)] for x in range(1000)}
def test_pop():
k, v= A.popitem()
A[k] = v
def test_iter(): k = next(A.iterkeys())
def test_list(): k = choice(A.keys())
def test_insert(): A[0] = 0
if __name__ == '__main__':
print('pop', timeit("test_pop()", setup="from __main__ import test_pop", number=10000))
print('iter', timeit("test_iter()", setup="from __main__ import test_iter", number=10000))
print('list', timeit("test_list()", setup="from __main__ import test_list", number=10000))
print('insert', timeit("test_insert()", setup="from __main__ import test_insert", number=10000))
Here are the results:
('pop', 0.0021750926971435547)
('iter', 0.002003908157348633)
('list', 0.047267913818359375)
('insert', 0.0010859966278076172)
It seems that using iterkeys is only marginal faster then poping an item and re-inserting but 10x's faster then creating the list and choosing a random object from it.