I don't expect the former to be slow in python as it would be a primitive implemented in C (although even a simple lisp interpreter can have an advantage here by just concatenating the conses).
For the latter, any language runtime capable of inference should be able to optimize it.
Python version:
from random import randrange
from time import time
def main():
L = [float(randrange(2**52, 2**53)) for _ in range(20000000)]
M = [float(randrange(2**52, 2**53)) for _ in range(20000000)]
t0 = time()
N = [ x+y for x,y in zip(L, M) ]
print('Concluded in', round(1000*(time() - t0)), 'millisec.')
main()
Python 3.10.5 (main, Jun 9 2022, 00:00:00) [GCC 12.1.1 20220507 (Red Hat 12.1.1-1)] on linux
Type "help", "copyright", "credits" or "license()" for more information.
============ RESTART: /run/media/user/KINGSTON/benchmark_doubles.py ============
Concluded in 1904 millisec.
| L M N t0 |
Transcript clear.
L := (1 to: 2e7) collect:
[ :each | (( 2 raisedTo: 52 ) to: ( 2 raisedTo: 53 )) atRandom asFloat ].
M := (1 to: 2e7) collect:
[ :each | (( 2 raisedTo: 52 ) to: ( 2 raisedTo: 53 )) atRandom asFloat ].
t0 := DateAndTime now.
M := L with: M collect: [ :x :y | x + y ].
Transcript
show: 'Concluded in '
,
((DateAndTime now - t0) asMilliSeconds asInteger ) asFloat asString
, ' millisec.';
cr.
Concluded in 914.0 millisec. def fooer(i: str, strings: list[str]):
push = str.append
for s in strings:
push(i, s)