# 53-maximum-subarray


Try it on <a href='https://leetcode.com/problems/53-maximum-subarray'>leetcode</a>

## Description
<div class="description">
<div><p>Given an integer array <code>nums</code>, find the contiguous subarray (containing at least one number) which has the largest sum and return <em>its sum</em>.</p>

<p>A <strong>subarray</strong> is a <strong>contiguous</strong> part of an array.</p>

<p>&nbsp;</p>
<p><strong>Example 1:</strong></p>

<pre><strong>Input:</strong> nums = [-2,1,-3,4,-1,2,1,-5,4]
<strong>Output:</strong> 6
<strong>Explanation:</strong> [4,-1,2,1] has the largest sum = 6.
</pre>

<p><strong>Example 2:</strong></p>

<pre><strong>Input:</strong> nums = [1]
<strong>Output:</strong> 1
</pre>

<p><strong>Example 3:</strong></p>

<pre><strong>Input:</strong> nums = [5,4,-1,7,8]
<strong>Output:</strong> 23
</pre>

<p>&nbsp;</p>
<p><strong>Constraints:</strong></p>

<ul>
	<li><code>1 &lt;= nums.length &lt;= 10<sup>5</sup></code></li>
	<li><code>-10<sup>4</sup> &lt;= nums[i] &lt;= 10<sup>4</sup></code></li>
</ul>

<p>&nbsp;</p>
<p><strong>Follow up:</strong> If you have figured out the <code>O(n)</code> solution, try coding another solution using the <strong>divide and conquer</strong> approach, which is more subtle.</p>
</div>
</div>

## Solution(Python)
```Python
class Solution:
    def maxSubArray(self, nums: List[int]) -> int:
        max_sum = float("-inf")
        cur_sum = 0

        for num in nums:
            if cur_sum + num > num:
                cur_sum = cur_sum + num
            else:
                cur_sum = num

            if cur_sum > max_sum:
                max_sum = cur_sum

        return max_sum

```