LeetCode #11: Container With Most Water - Python Implementation

LeetCode #11 – Container With Most Water | Python Implementation I implemented a greedy two-pointer approach to find the maximum water a container can hold. Pointers start at opposite ends maximizing the width, and at each step the area is computed as the product of width and the shorter boundary. The critical greedy decision: always move the pointer with the smaller height inward, since keeping the shorter boundary can never yield a larger area with reduced width. This pattern directly applies to resource allocation optimization, load balancing systems, and capacity planning in distributed infrastructure. Key Takeaway: The greedy pointer movement is the core insight — moving the taller boundary inward is never beneficial since the area is always limited by the shorter side. This transforms an O(n²) brute-force enumeration into a clean O(n) single-pass solution by eliminating provably suboptimal states at every step. Time: O(n) | Space: O(1) #LeetCode #DataStructures #Python #TwoPointers #Greedy #CodingInterview #ProblemSolving #SoftwareEngineering

  • graphical user interface, text, application, email

To view or add a comment, sign in

Explore content categories