Sliding window: minimum size subarray sum

A sliding window is a sub-range [left, right] that you grow on the right and shrink on the left, so you never re-scan the same elements. It turns many "find the best contiguous run" problems from O(n²) into a single O(n) pass.

The trick for minimum-length problems: keep expanding the window until it's "good enough", then shrink from the left as far as you can while it stays good — recording the smallest width you ever saw.

In plain steps (you write the Python):

advance `right` across the list, adding each value to a running total   # grow
while the total is >= target:        # window is "good" — try to shrink it
    record the current width (right - left + 1) if it's the smallest so far
    subtract the left value from the total and move `left` forward        # shrink

Your task

Write min_subarray_len(target, nums) that returns the length of the shortest contiguous subarray whose sum is ≥ target. If no such subarray exists, return 0. All numbers are positive.

min_subarray_len(7, [2, 3, 1, 2, 4, 3])   # 2   -> [4, 3]
min_subarray_len(4, [1, 4, 4])            # 1   -> [4]
min_subarray_len(11, [1, 1, 1, 1, 1])     # 0   -> never reaches 11

Hint: one pass, two indices. Add to a running total as right advances; while total >= target, record right - left + 1 and slide left forward.