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.

org/study_deck_02/dsa/arrays-hashing/0347-top-k-frequent-elements.org

@@ -1,18 +1,56 @@
 #+PROPERTY: STUDY_DECK_02
 * TODO 0347. Top K Frequent Elements :medium:
 :PROPERTIES:
-:NEETCODE: [[file:../../roadmap.org::*0347. Top K Frequent Elements][Roadmap]]
+:NEETCODE: [[file:../../roadmap.org::*0347. Top K Frequent Elements][0347. Top K Frequent Elements]]
 :END:
 
+Given an integer array ~nums~ and an integer ~k~, return /the/ ~k~ /most frequent elements/. You may return the answer in *any order*.
+
+*Example 1:*
+
+*Input:* nums = [1,1,1,2,2,3], k = 2
+
+*Output:* [1,2]
+
+*Example 2:*
+
+*Input:* nums = [1], k = 1
+
+*Output:* [1]
+
+*Example 3:*
+
+*Input:* nums = [1,2,1,2,1,2,3,1,3,2], k = 2
+
+*Output:* [1,2]
+
+*Constraints:*
+
+ - ~1 <= nums.length <= 10^{5}~
+
+ - ~-10^{4} <= nums[i] <= 10^{4}~
+
+ - ~k~ is in the range ~[1, the number of unique elements in the array]~.
+
+ - It is *guaranteed* that the answer is *unique*.
+
+*Follow up:* Your algorithm's time complexity must be better than ~O(n log n)~, where n is the array's size.
+
 ** TODO Approach
 Write your approach here.
 
 ** TODO Python
 #+begin_src python
-
+class Solution:
+    def topKFrequent(self, nums: List[int], k: int) -> List[int]:
 #+end_src
 
 ** TODO C++
 #+begin_src cpp
-
+class Solution {
+public:
+    vector<int> topKFrequent(vector<int>& nums, int k) {
+        
+    }
+};
 #+end_src