Growing window maximum
Compute a sliding-window maximum over a stream. Given a list of integers and a window size w, return a list where the i-th entry is the maximum of the window ending at index i, using min(i+1, w) elements (the window grows until it reaches size w). Return the list of per-position maxima. Assume w >= 1 and the input may be empty.
Implement
sliding_max(nums: list[int], w: int) → list[int]Examples
in
[[1,3,2,5,4],3]out[1,3,3,5,5]What a strong answer looks like
State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.
0:00 of about 25 min
solution.py
InputExpectedGot
[[1,3,2,5,4],3][1,3,3,5,5]not run yetsample