If you're asking which method would faster if put in a function(hence the return's), then I used the timeit module to do a little testing. I put each method in a function, and then ran the program to see which function ran faster. Here is the program:
import timeit
def is_empty2():
a = []
if a:
return True
else:
return False
def is_empty1():
a = []
return a == []
print("Time for method 2:")
print(timeit.timeit(is_empty2))
print("")
print("Time for method 1:")
print(timeit.timeit(is_empty1))
I ran the program five times, each time recording the speed for each function. After getting an average for each time, here is what I came up with:
method one speed(milliseconds): 0.2571859563796641
----------------------------- ------------------
method two speed(milliseconds): 0.2679253742685615
At least from my testing above, the first method you described in your question was slightly faster than the second method. Of course those numbers above could drastically change depending on what exactly is inside those two functions.
I agree however, with what Cdarke said in the comments. Go with the one that is the most clear and concise. Don't go with one option solely based upon its speed. in the words of Guido van Rosom: Readability counts.
x == []seems to short circuit (CPython 3), so the performance of both approaches should be O(1), and multiple thousands of entries vs. one or two entries should not matter.TrueandFalseare switched around. Your intent could just be writtennot bool(a)by the way.not a[]tests as false, and non-empty lists test as true. No need to get fancy because the whole point of this truthiness approach is to be able to use list lengths equivalent to boolean values.