I am comparing the performance of the any() built-in function with the actual implementation the docs suggest:
I am looking for an element greater than 0 in the following list:
lst = [0 for _ in range(1000000)] + [1]
This is the supposedly equivalent function:
def gt_0(lst):
for elm in lst:
if elm > 0:
return True
return False
And these are the results of the performance tests:
>> %timeit any(elm > 0 for elm in lst)
>> 10 loops, best of 3: 35.9 ms per loop
>> %timeit gt_0(lst)
>> 100 loops, best of 3: 16 ms per loop
I would expect both of the to have the exact same performance, however any() if two times slower. Why?
The reason is that you've passed a generator expression to the any() function. Python needs to convert your generator expression to a generator function and that's why it performs slower. Because a generator function needs to call the __next__() method each time for generating the item and passing it to the any. This is while in a manual defined function you are passing the whole list to your function which has all the items prepared already.
You can see the difference better by using a list comprehension rather than a generator expression:
In [4]: %timeit any(elm > 0 for elm in lst)
10 loops, best of 3: 66.8 ms per loop
In [6]: test_list = [elm > 0 for elm in lst]
In [7]: %timeit any(test_list)
100 loops, best of 3: 4.93 ms per loop
Also another bottleneck in your code which has more cost than extra calls on next is the way you do the comparison. As mentioned in comment the better equivalent of your manual function is:
any(True for elm in lst if elm > 0)
In this case you're doing the comparison with the generator expression and it'll perform almost in an equal time as your manual defined function (the slightest difference is because of the generator, I guess.) For a deeper understanding of the underlying reasons read the Ashwini's answer.