LeetCode 380: Insert Delete GetRandom O(1) | Python Solution | Hash Map + Array
📝 In this problem, we implement a data structure that supports constant time insertion, deletion, and random element retrieval. #leetcode #datastructure #hashmap #randomized
*Time Complexity:* O(1) for all operations (insert, remove, getRandom)
*Space Complexity:* O(n) where n is the number of elements
⏱️ Timestamps
00:00 - Understanding problem statement
01:01 - Analyzing data structures
03:45 - Python code walk-through
04:39 - Solution analysis - runtime + memory
🔑 Key Concepts
Hash Map (Dictionary)
Array Operations
Constant Time Operations
Randomized Algorithms
💡 Learning Points
How to achieve O(1) operations using complementary data structures
Efficient implementation of randomized element selection
Trade-offs between time and space complexity
Practical application of hash maps in system design
🔗 Related Problems
LeetCode 381: Insert Delete GetRandom O(1) - Duplicates allowed
LeetCode 710: Random Pick with Blacklist
LeetCode 519: Random Flip Matrix
LeetCode 528: Random Pick with Weight
👥 Target Audience
This video is for intermediate programmers preparing for coding interviews, particularly those focusing on system design and data structure implementation.
📚 Prerequisites
Basic understanding of Python
Knowledge of hash maps/dictionaries
Familiarity with array operations
🔗 Links
LeetCode problem: https://leetcode.com/problems/insert-...
Solution code: https://leetcode.com/problems/insert-...
💡 Additional Tips
Focus on the trick of swapping the element to be deleted with the last element
Explain why a simple hash map alone can't handle getRandom in O(1)
Emphasize the importance of keeping the array and hash map in sync
🎯 Call to Action
If you found this solution helpful, please hit the like button and subscribe for weekly algorithm challenges! Drop your questions or alternative approaches in the comments below, and I'll respond to every one of them. #codinginterview #pythonsolution #algorithmpractice