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🚀 Welcome to Part 144 of Code & Debug’s DSA in Python Course! In this video, we implement the Dijkstra’s Algorithm using a min-heap (priority queue) to efficiently compute the shortest distance from a source node to all others. 🔍 What you’ll learn: ✅ Dijkstra’s Algorithm Intuition ✅ Using heapq for optimal performance ✅ Why we skip already shorter paths (distance check) ✅ How to construct adjacency list from edge list ✅ Time and space complexity analysis 📄 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-with-a-priority-queue/ 📚 Python DSA Course Playlist & Sheet: https://docs.google.com/spreadsheets/d/1AWE15Fy3wD2iqu2vjK_R7cCiuvSsjYQclcdZmHpF66o/edit?usp=sharing 🚀 Zero to Hero Python DSA: 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 for more graph algorithms. #DijkstraAlgorithm #PriorityQueue #Graphs #PythonDSA #GFG #ShortestPath #CodeAndDebug #Part144 #Heapq #GraphTheory
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