Trees

Quick Start Guide

# import required algorithm
>>> from package.pygostructures.data_structures.trees import BinarySearchTree

# creating BST
>>> bst = BinarySearchTree()

# insert value to be inserted
>>> bst.insert(5)
>>> bst.insert(7)
>>> bst.insert(3)
>>> bst.insert(6)
>>> bst.insert(20)
>>> bst.insert(19)
>>> bst.insert(0)
>>> bst.insert(1)
>>> bst.insert(100)
>>> bst.insert(111)

# check if give argument is present in the bst
>>> bst.search(19)
True
>>> bst.search(50)
False

# performs inorder traversal
>>> bst.inorder(bst.root)
0-->1-->3-->5-->6-->7-->19-->20-->100-->111

# performs preorder traversal
>>> bst.preorder(bst.root)
5-->3-->0-->1-->7-->6-->20-->19-->100-->111

# performs postorder
>>> bst.postorder(bst.root)
1-->0-->3-->6-->19-->111-->100-->20-->7-->5

Trees Programs

Author : Robin Singh

Binary Search Tree

class pythorn.data_structures.trees.BinarySearchTree

Binary Search Tree Funtion

Parameters

root – root node

insert(ele)

inserts a node into the tree

search(k)

Function for searching an given element

Returns

true if element is present else return false

inorder(temp)

here we first traverse to the leftmost node and then print the data and then move to the rightmost child

Parameters

temp – root node

preorder(temp)

here we first print the root node and then traverse towards leftmost node and then to the rightmost node

Parameters

temp – root node

postorder(temp)

here we first traverse to the leftmost node and then to the rightmost node and then print the data

Parameters

temp – root node

static get_code()

Returns

source code

static time_complexity()

Returns

time complexity