... cost . We take up only extra space, which is a very good benefit of using binary heaps. Solution def mergeKLists(self, lists: 'List[ListNode]') -> 'ListNode': k = len(lists) dummy = head = ListNode(None) heap = [] if not lists: return None # Ensure that all linked list (indices) are inserted into the heap for i in range(0, k): if lists[i] is None: continue heapq.
0 CommentsIntroduction Welcome to the algorithm handbook wiki! In this wiki you will find a mini-cheat sheet overview of data structures, and examples of their usages in modern languages. Algorithm problems can be found here.
0 CommentsWelcome This page contains solutions to common interview problems that may be encountered. Arrays Longest Substring Without Repeating Characters Rotate a 2D Matrix Buy/Sell Two Stocks Merge Intervals Next Permutation Random Permutation Replace all occurrences of a space with a string Linked Lists Reversing sublists of singly linked lists Cycles in singly linked lists Overlapping singly linked lists Merging two sorted singly linked lists Merge k sorted lists Recursion Counting the path of sums Money Denominations Phone Number Mnemonics Unique Permutation Dynamic Programming Perfect Squares Find the Maximum Min Path Binary Trees Tree Symmetry Iterative In-Order Traversal of a Binary Tree Construct a Binary Tree from Pre-Order Traversal and In-Order Traversal BST Validate a BST Binary Heaps Merge k sorted lists Graphs Find a path in a maze from start to finish Flip colors in a matrix Search Search in a rotated sorted array Find the Duplicate Number Greedy Algorithms Queue Reconstruction By Height Trie Build a Trie in Python Invariant Compute the max.
0 Comments