What is LeetCode 703 Kth Largest Element in a Stream?

It's a design problem: build a class adding numbers to a stream, returning kth largest after each—using min-heap for efficiency.

How to solve LeetCode 703 in Python?

Use heapq min-heap size k: push val, pop if >k, return heap[0]. Init pre-adds nums.

Why min-heap for kth largest not max-heap?

Min-heap root = smallest of largest k, exactly kth. Max-heap root = overall max, not kth—needs full scan.

🛠️ Developer Tools

Heaps vs. the Data Deluge: Mastering LeetCode 703's Kth Largest Stream

Data streams never sleep. LeetCode 703 arms you with a min-heap to snag the kth largest element on the fly—like a digital sieve sifting gold from rivers of numbers.

theAIcatchup Apr 09, 2026 3 min read

Visual trace of min-heap growing for LeetCode 703 kth largest stream

⚡ Key Takeaways

Min-heap of size k tracks k largest effortlessly—root is always your answer. 𝕏
O(log k) per add crushes sorting for endless streams. 𝕏
Powers real-time AI: top-k in LLMs, anomaly detection, leaderboards. 𝕏

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#LeetCode 703 #Python algorithms #kth largest stream #min-heap #priority queue

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Originally reported by Dev.to

⚡ Key Takeaways

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