Counting the number of True Booleans in a Python List

Solution 1:

True is equal to 1.

>>> sum([True, True, False, False, False, True])
3

Solution 2:

list has a count method:

>>> [True,True,False].count(True)
2

This is actually more efficient than sum, as well as being more explicit about the intent, so there's no reason to use sum:

In [1]: import random

In [2]: x = [random.choice([True, False]) for i in range(100)]

In [3]: %timeit x.count(True)
970 ns ± 41.1 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)

In [4]: %timeit sum(x)
1.72 µs ± 161 ns per loop (mean ± std. dev. of 7 runs, 100000 loops each)

Solution 3:

If you are only concerned with the constant True, a simple sum is fine. However, keep in mind that in Python other values evaluate as True as well. A more robust solution would be to use the bool builtin:

>>> l = [1, 2, True, False]
>>> sum(bool(x) for x in l)
3

UPDATE: Here's another similarly robust solution that has the advantage of being more transparent:

>>> sum(1 for x in l if x)
3

P.S. Python trivia: True could be true without being 1. Warning: do not try this at work!

>>> True = 2
>>> if True: print('true')
... 
true
>>> l = [True, True, False, True]
>>> sum(l)
6
>>> sum(bool(x) for x in l)
3
>>> sum(1 for x in l if x)
3

Much more evil:

True = False

Solution 4:

You can use sum():

>>> sum([True, True, False, False, False, True])
3

Solution 5:

After reading all the answers and comments on this question, I thought to do a small experiment.

I generated 50,000 random booleans and called sum and count on them.

Here are my results:

>>> a = [bool(random.getrandbits(1)) for x in range(50000)]
>>> len(a)
50000
>>> a.count(False)
24884
>>> a.count(True)
25116
>>> def count_it(a):
...   curr = time.time()
...   counting = a.count(True)
...   print("Count it = " + str(time.time() - curr))
...   return counting
... 
>>> def sum_it(a):
...   curr = time.time()
...   counting = sum(a)
...   print("Sum it = " + str(time.time() - curr))
...   return counting
... 
>>> count_it(a)
Count it = 0.00121307373046875
25015
>>> sum_it(a)
Sum it = 0.004102230072021484
25015

Just to be sure, I repeated it several more times:

>>> count_it(a)
Count it = 0.0013530254364013672
25015
>>> count_it(a)
Count it = 0.0014507770538330078
25015
>>> count_it(a)
Count it = 0.0013344287872314453
25015
>>> sum_it(a)
Sum it = 0.003480195999145508
25015
>>> sum_it(a)
Sum it = 0.0035257339477539062
25015
>>> sum_it(a)
Sum it = 0.003350496292114258
25015
>>> sum_it(a)
Sum it = 0.003744363784790039
25015

And as you can see, count is 3 times faster than sum. So I would suggest to use count as I did in count_it.

Python version: 3.6.7
CPU cores: 4
RAM size: 16 GB
OS: Ubuntu 18.04.1 LTS