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-------------------------------------------------------------------------------------- Welcome to srkcodes! In Day 110 of #365DaysOfCode, we tackle Leetcode Q215: Kth Largest Element in an Array, which asks: Given an integer array nums and an integer k, return the kth largest element in the array.

We solve this without sorting, using a heap (priority queue) approach: maintain a min‑heap of size k, push each element, and pop when the heap exceeds size k, so the root is always the kth largest.

🔍 What You’ll Learn
Heap Approach in Python: How to use heapq.heappush() and heapq.heappop() to maintain a min‑heap of size k.
Python documentation

Time & Space Complexity: Understand why this method runs in O(n log k) time and O(k) space.

Edge Cases & Examples: Walk through sample inputs like [3,2,1,5,6,4] with k=2 to see the heap evolve.

When & Why to Use Heaps: Learn real-world use‑cases like streaming data, priority scheduling, and greedy algorithms.

💬 Practice Challenge: Can you adapt this to find the kth smallest element? Drop your code in the comments!

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🔗 External Study Resources for Deep Dive:
📝 Problem discussed in the video ➡️ https://leetcode.com/problems/kth-lar...

📚 Topic's ⬇️
Heap :- https://www.geeksforgeeks.org/heap-da...

💡 LeetCode problems ➡️ https://leetcode.com/problem-list/hea...