wrong in this case. all elements are identical except one. there aren't a lot of swaps going on. what are you talking about.

Sorting is efficient when the input data is small. For large data set would be efficient.

I agree with the previous commentator, I forgot about sets and sorting)).
I consider this solution to be the most understandable and concise than the solution at the top of the list. The only question regarding the speed of code execution is - what will be faster, sorting or converting to a set?

I completely forgot about the sorting methods and my code is hella complex but atleast it works.

@mediocreprogrammer99 & @RamidW

you should use always the spoiler flag when discussing code

(i added the flags to your comments)

Your's is probably a bit faster without the need to copy the list. I tend to not modify the data I'm given just in case the test cases are written in such a way as to depend on the same data after my function is called (it's bitten me in the past).

ditto

i feel so dumb

i think about mapping, but dont know there is all function in py, greate and readable

try this to measure time :

%timeit

I did it on the solution that I implemented (based on a sort) and found it OK in performance compared to other solutions.
For ex on a 1-million items list: time to execute with sort = 3 ms, time to execute with solution with sets = 8 ms
for whatever that's worth ...

tried the same way but had a memory limit with sorted a very big numbers array.
pass with count el of sorted set