feat(work): add solutions for problems 42, 209, and 34

work/1/Medium/Array/209.minimum-size-subarray-sum.py

@@ -0,0 +1,63 @@
+"""
+209. Minimum Size Subarray Sum
+Difficulty: Medium
+https://leetcode.com/problems/minimum-size-subarray-sum/
+
+──────────────────────────────────────────────────
+
+Given an array of positive integers nums and a positive integer
+target, return the minimal length of a subarray whose sum is greater
+than or equal to target. If there is no such subarray, return 0
+instead.
+
+
+
+Example 1:
+
+Input: target = 7, nums = [2,3,1,2,4,3]
+Output: 2
+Explanation: The subarray [4,3] has the minimal length under the
+problem constraint.
+
+Example 2:
+
+Input: target = 4, nums = [1,4,4]
+Output: 1
+
+Example 3:
+
+Input: target = 11, nums = [1,1,1,1,1,1,1,1]
+Output: 0
+
+
+
+Constraints:
+
+        • 1 <= target <= 10^9
+
+        • 1 <= nums.length <= 10^5
+
+        • 1 <= nums[i] <= 10^4
+
+
+
+Follow up: If you have figured out the O(n) solution, try coding
+another solution of which the time complexity is O(n log(n)).
+"""
+
+
+class Solution:
+    def minSubArrayLen(self, target: int, nums: list[int]) -> int:
+        window_sum = 0
+        length = len(nums) + 1
+        left = 0
+
+        for right in range(len(nums)):
+            window_sum += nums[right]
+            while window_sum >= target:
+                length = min(length, right - left + 1)
+                window_sum -= nums[left]
+                left += 1
+        if length > len(nums):
+            return 0
+        return length