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
LeetCode #11: Container With Most Water - Python Implementation
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Mark Baggett is an excellent instructor, and I highly recommend checking out his SEC573 course if you're looking to improve your security automation skills!
📺 Now Available OnDemand: Inside the New SEC573 with Mark Baggett See how the updated course uses Python, LLMs, and MCP to help defenders build smarter tools faster. Watch the replay and get inspired to start automating. 🔗 https://go.sans.org/OkqVCi #OnDemand #SEC573 #CyberDefense #SecurityAutomation #Python #LLM
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