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🚀 Welcome to Part 146 of Code & Debug’s DSA Python Course 2025! In this session, we answer a very important and commonly asked question: ❓ "Why do we use a Priority Queue in Dijkstra’s Algorithm instead of a normal Queue?" 🔍 What you’ll learn: ✅ What goes wrong if you use a normal queue in Dijkstra ✅ How the priority queue helps always pick the minimum distance node ✅ Real-world example & dry run comparisons ✅ Why Dijkstra with a normal queue breaks the greedy property ✅ Time Complexity: O(E log V) of PQ-based approach – full breakdown ✅ Interview-level clarity on why heap is crucial 📄 Topics Covered: • Dijkstra with Queue: Wrong outputs • Priority Queue (Min Heap): Correctness + Efficiency • heapq in Python • Detailed comparison: Queue vs PQ • Why O(E log V) is optimal 📚 Complete Python DSA Playlist & Sheet: https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing 🚀 Master DSA from Scratch: https://codeanddebug.in/course/zero-to-hero-python-dsa 💡 Free Problem-Solving Masterclass (Leetcode-Based): https://codeanddebug.in/course/master-dsa-with-leetcode 👀 Still using a queue in Dijkstra? Let’s fix that today. 🔔 Subscribe for more real-world DSA insights. #DijkstraAlgorithm #PriorityQueue #WhyNotQueue #GraphsInPython #DSATimeComplexity #OElgV #GreedyAlgorithms #CodeAndDebug #Part146 #PythonDSA2025
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