Mutable vs Immutable in Python — Why It Matters in DSA скачать в хорошем качестве

Mutable vs Immutable in Python — Why It Matters in DSA

If your Python DSA solutions sometimes give the wrong answer even though your logic looks correct, the problem is often NOT the algorithm — it’s mutability. In this video, we break down why mutable vs immutable objects in Python matter so much in Data Structures and Algorithms (DSA), especially in interviews. You’ll learn: • What mutable and immutable variables really mean in Python • List vs Tuple — when to use each in DSA • How shared references silently break recursion and backtracking • Why tuples are required for dynamic programming (DP) states • How string immutability affects time complexity • A real interview-level subsets problem with buggy and corrected code This video focuses on the “why”, not just the “what”, so you can avoid silent bugs and write safer, faster Python DSA solutions. If you are preparing for coding interviews, competitive programming, or want to master Python for DSA, this is a must-watch. Subscribe for more deep Python + DSA explanations. 00:00 Why Python DSA Code Fails Silently 00:40 What Mutability Really Means in Python 01:30 List vs Tuple — The Core DSA Difference 02:40 Shared Reference Bug Explained 03:40 Copying Lists the Right Way 04:30 Strings, Immutability & Time Complexity 05:30 Backtracking Bug Caused by Mutability 06:30 Why Tuples Are Used in Dynamic Programming 07:20 Subsets Problem — Buggy vs Correct Code 08:40 DSA Cheat Sheet (Final Summary) 09:10 Key Takeaways & Next Video #PythonDSA #PythonInterview #ListVsTuple #MutableVsImmutable #CodingInterviews