class Solution:
    def minimumDifference(self, nums: List[int], k: int) -> int:
        sortedNums = sorted(nums)
        start = 0
        l = len(sortedNums)
        res = sortedNums[l - 1] - sortedNums[0]
        for start in range(0, l - k + 1):
            res = min(res, sortedNums[start + k - 1] - sortedNums[start])
        return res

我的代码如上，对Python还不是特别熟悉，不够简练，另外range，以及start end index的设置也费了点脑子，用一个例子比用脑子想容易很多

比如

0, 1, 2, 3 # index

1, 2, 3, 4 # size

k = 2

start from 0 to 2, range (0, 3)
2 = 4 - 2 
when start = 2, end  = 3, end  = start + k - 1

让GPT评价了一下，优化如下

Your code is correct and idiomatic for the standard solution (sort + fixed-size window).

What’s good

• Correct logic: after sorting, the minimum difference among any size-k subset is the minimum of a[i+k-1] - a[i].

• Complexity: O(n log n) time for sorting + O(n) scan; O(n) extra space because sorted() returns a new list.

• Clean window indexing; no off-by-one issues.

Small improvements

1. start = 0 before the loop is unused (can remove).

2. Use clearer names + handle edge cases explicitly (optional).

A slightly cleaner version:

class Solution:
    def minimumDifference(self, nums: List[int], k: int) -> int:
        if k <= 1:
            return 0

        nums.sort()  # in-place, saves memory vs sorted(nums)
        res = float("inf")

        for i in range(len(nums) - k + 1):
            res = min(res, nums[i + k - 1] - nums[i])

        return res

Opinion: Prefer nums.sort() over sorted(nums) in LeetCode unless you need to preserve the original list.

确实更简洁