Performance of f-string vs string.join

one = 'one'
two = 'two'
three = 'three'

Are the 2 equivalent in time complexity?

result_1 = f'{one}{two}{three}'
result_2 = ''.join([one, two, three])

I know that join works in linear time. But is the same true also for f-strings?
With f-strings, the number of strings being concatenated is always a constant, so I guess one could say it's constant time complexity, but I was more curious to know how the concatenation is implemented and how it would fare with a large number of strings.

The performance of these two approaches may vary between releases of Python and could also depend on your hardware.

In Python 3.11.3 on macOS 13.4 (3 GHz 10-Core Intel Xeon W) the f-string implementation is faster than str.join()

from timeit import timeit

ONE = 'one'
TWO = 'two'
THREE = 'three'

def func1(one, two, three):
    return f'{one}{two}{three}'

def func2(one, two, three):
    return ''.join([one,two,three])

for func in func1, func2:
    print(func.__name__, timeit(lambda: func(ONE, TWO, THREE), number=2_000_000))

Output:

func1 0.2694316829999934
func2 0.33222394099993835

Note:

This result will be due in part to the fact that func2 has to construct a list. This can be eliminated by re-writing it as:

def func2(*args):
    return ''.join(args)

...which timeit reports as:

func2 0.30138257099997645