Sliding window median
Given an integer array nums and a window size k, return a list of the medians of every contiguous window of size k as it slides from left to right. The median is the middle value of a sorted window if k is odd, or the average of the two middle values if k is even. To keep results exact and JSON-serializable, return each median multiplied by 2 as an integer (so an even-k average of 2 and 4 is reported as 6, and an odd-k median of 5 as 10). The array has 1 to 10^5 elements and 1 <= k <= len(nums).
Implement
sliding_window_median_x2(nums: list[int], k: int) → list[int]Examples
in
[[1,3,-1,-3,5,3,6,7],3]out[2,-2,-2,6,10,12]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 35 min
solution.py
InputExpectedGot
[[1,3,-1,-3,5,3,6,7],3][2,-2,-2,6,10,12]not run yetsample