DSA in Python- Dijkstra’s Algorithm Using Set | Why Priority Queue is Better | Graphs Part 145

🚀 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