1+ # Given an array of positive integers nums and a positive integer target, return the
2+ # minimal length of a
3+ # subarray
4+ # whose sum is greater than or equal to target. If there is no such subarray, return
5+ # 0 instead.
6+ 7+ 8+ 9+ # Example 1:
10+ 11+ # Input: target = 7, nums = [2,3,1,2,4,3]
12+ # Output: 2
13+ # Explanation: The subarray [4,3] has the minimal length under the problem constraint.
14+ # Example 2:
15+ 16+ # Input: target = 4, nums = [1,4,4]
17+ # Output: 1
18+ # Example 3:
19+ 20+ # Input: target = 11, nums = [1,1,1,1,1,1,1,1]
21+ # Output: 0
22+ 23+ 24+ # Constraints:
25+ 26+ # 1 <= target <= 109
27+ # 1 <= nums.length <= 105
28+ # 1 <= nums[i] <= 104
29+ 30+ 31+ # Follow up: If you have figured out the O(n) solution, try coding another solution of
32+ # which the time complexity is O(n log(n)).
33+ 34+ 35+ from typing import List
36+ class Solution :
37+ def minSubArrayLen (self , target : int , nums : List [int ]) -> int :
38+ prefix_sum = left = 0
39+ ln = len (nums )
40+ ans = ln + 1
41+ 42+ for i in range (ln ):
43+ prefix_sum += nums [i ]
44+ while prefix_sum >= target :
45+ ans = min (ans , i - left + 1 )
46+ prefix_sum -= nums [left ]
47+ left += 1
48+ if ans > ln :
49+ return 0
50+ else :
51+ return ans
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