feat: populate note files with problem descriptions and code stubs
Add populate-notes.mjs that fetches problem descriptions and Python/C++ code stubs from LeetCode's GraphQL API. Populated all 197 NeetCode 150 note files with: - Problem description (examples, constraints) - Python code stub (function signature) - C++ code stub (function signature + includes) API responses cached in leetcode/.cache/leetcode/ for instant re-runs.
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#+PROPERTY: STUDY_DECK_02
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* TODO 0053. Maximum Subarray :medium:
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:PROPERTIES:
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:NEETCODE: [[file:../../roadmap.org::*0053. Maximum Subarray][Roadmap]]
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:NEETCODE: [[file:../../roadmap.org::*0053. Maximum Subarray][0053. Maximum Subarray]]
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:END:
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Given an integer array ~nums~, find the subarray with the largest sum, and return /its sum/.
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*Example 1:*
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#+begin_src
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Input: nums = [-2,1,-3,4,-1,2,1,-5,4]
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Output: 6
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Explanation: The subarray [4,-1,2,1] has the largest sum 6.
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#+end_src
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*Example 2:*
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#+begin_src
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Input: nums = [1]
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Output: 1
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Explanation: The subarray [1] has the largest sum 1.
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#+end_src
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*Example 3:*
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#+begin_src
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Input: nums = [5,4,-1,7,8]
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Output: 23
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Explanation: The subarray [5,4,-1,7,8] has the largest sum 23.
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#+end_src
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*Constraints:*
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- ~1 <= nums.length <= 10^{5}~
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- ~-10^{4} <= nums[i] <= 10^{4}~
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*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.
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** TODO Approach
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Write your approach here.
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** TODO Python
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#+begin_src python
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class Solution:
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def maxSubArray(self, nums: List[int]) -> int:
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#+end_src
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** TODO C++
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#+begin_src cpp
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class Solution {
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public:
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int maxSubArray(vector<int>& nums) {
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}
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};
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#+end_src
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