Sync LeetCode submission Runtime - 105 ms (15.79%), Memory - 28.9 MB (13.40%)

Author: jimit105

0215-kth-largest-element-in-an-array/README.md

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+<p>Given an integer array <code>nums</code> and an integer <code>k</code>, return <em>the</em> <code>k<sup>th</sup></code> <em>largest element in the array</em>.</p>
+
+<p>Note that it is the <code>k<sup>th</sup></code> largest element in the sorted order, not the <code>k<sup>th</sup></code> distinct element.</p>
+
+<p>Can you solve it without sorting?</p>
+
+<p>&nbsp;</p>
+<p><strong class="example">Example 1:</strong></p>
+<pre><strong>Input:</strong> nums = [3,2,1,5,6,4], k = 2
+<strong>Output:</strong> 5
+</pre><p><strong class="example">Example 2:</strong></p>
+<pre><strong>Input:</strong> nums = [3,2,3,1,2,4,5,5,6], k = 4
+<strong>Output:</strong> 4
+</pre>
+<p>&nbsp;</p>
+<p><strong>Constraints:</strong></p>
+
+<ul>
+	<li><code>1 &lt;= k &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>

0215-kth-largest-element-in-an-array/solution.py

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+# Approach 2: Min-Heap
+
+# Time: O(n * log k)
+# Space: O(k)
+
+import heapq
+
+class Solution:
+    def findKthLargest(self, nums: List[int], k: int) -> int:
+        heap = []
+        heapq.heapify(heap)
+
+        for num in nums:
+            heapq.heappush(heap, num)
+            if len(heap) > k:
+                heapq.heappop(heap)
+
+        return heap[0]
+