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🚀 Welcome to Part 145 of Code & Debug’s DSA in Python Course! In this video, we implement Dijkstra’s Algorithm using a set and understand why it’s NOT optimal compared to using a priority queue (heapq). 🔍 What you’ll learn: ✅ Dijkstra’s Algorithm using set ✅ Why set can become inefficient — O(V) extraction ✅ Comparison with priority queue (heap) — O(log V) ✅ When to use what (interview-ready insights) ✅ Clean Python implementation ✅ Time and space complexity breakdown 📄 Concept Covered: • set has no efficient min-extraction → leads to higher time complexity • Heap-based Dijkstra is better for large graphs • Dry run included to visualize inefficiencies 📄 GFG Problem Link: https://www.geeksforgeeks.org/problems/implementing-dijkstra-set-1-adjacency-matrix/1 👉 Refer to the article for better understanding: 🔗 https://codeanddebug.in/blog/dijkstra-algorithm-in-python-using-a-set/ 📚 Python DSA Course 2025 Playlist & Sheet: https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing 🚀 Zero to Hero Python DSA Batch: https://codeanddebug.in/course/zero-to-hero-python-dsa 💡 Free Masterclass with LeetCode-Based Problems: https://codeanddebug.in/course/master-dsa-with-leetcode 💬 Doubts? Drop them in the comments! 👍 Like, 🔁 Share & 🔔 Subscribe to stay ahead in Graph Algorithms. #DijkstraAlgorithm #SetVsHeap #PythonDSA #GraphAlgorithms #CodeAndDebug #PriorityQueue #Part145 #PythonForDSA #TimeComplexity
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