Suppose we have a binary search tree. We have to find the Kth smallest element in that BST. So if the tree is like −
So if we want to find 3rd smallest element, then k = 3, and result will be 7.
To solve this, we will follow these steps −
- create one empty list called nodes
- call solve(root, nodes)
- return k – 1th element of nodes
- the solve method is created, this takes root and nodes array, this will work as follows −
- if root is null, then return
- solve(left of root, nodes)
- add value of root into the nodes array
- solve(right of root, nodes)
Let us see the following implementation to get better understanding −
Example
class TreeNode: def __init__(self, data, left = None, right = None): self.data = data self.left = left self.right = right def insert(temp,data): que = [] que.append(temp) while (len(que)): temp = que[0] que.pop(0) if (not temp.left): temp.left = TreeNode(data) break else: que.append(temp.left) if (not temp.right): temp.right = TreeNode(data) break else: que.append(temp.right) def make_tree(elements): Tree = TreeNode(elements[0]) for element in elements[1:]: insert(Tree, element) return Tree class Solution(object): def kthSmallest(self, root, k): nodes = [] self.solve(root,nodes) return nodes[k-1] def solve(self, root,nodes): if root == None: return self.solve(root.left,nodes) nodes.append(root.data) self.solve(root.right,nodes) ob1 = Solution() tree = make_tree([10,5,15,2,7,13]) print(ob1.kthSmallest(tree, 3))
Input
[10,5,15,2,7,13] 3
Output
7