# 53.maximum-subarray

## Statement

• Difficulty: Easy
• Tag: `数组` `分治` `动态规划`

``````输入：nums = [-2,1,-3,4,-1,2,1,-5,4]

``````

``````输入：nums = [1]

``````

``````输入：nums = [5,4,-1,7,8]

``````

• `1 <= nums.length <= 105`
• `-104 <= nums[i] <= 104`

• Difficulty: Easy
• Tag: `Array` `Divide and Conquer` `Dynamic Programming`

Given an integer array `nums`, find the contiguous subarray (containing at least one number) which has the largest sum and return its sum.

A subarray is a contiguous part of an array.

Example 1:

``````Input: nums = [-2,1,-3,4,-1,2,1,-5,4]
Output: 6
Explanation: [4,-1,2,1] has the largest sum = 6.
``````

Example 2:

``````Input: nums = [1]
Output: 1
``````

Example 3:

``````Input: nums = [5,4,-1,7,8]
Output: 23
``````

Constraints:

• `1 <= nums.length <= 105`
• `-104 <= nums[i] <= 104`

Follow up: If you have figured out the `O(n)` solution, try coding another solution using the divide and conquer approach, which is more subtle.

## Solution

``````from typing import List

class Solution:
def maxSubArray(self, nums: List[int]) -> int:
res = -10000
cur = 0
for a in nums:
cur += a
res = max(res, cur)
if cur < 0:
cur = 0
return res
``````