Binarytree Module in Python

Last Updated : 10 Jan, 2023

A binary tree is a data structure in which every node or vertex has at most two children. In Python, a binary tree can be represented in different ways with different data structures(dictionary, list) and class representations for a node. However, binarytree library helps to directly implement a binary tree. It also supports heap and binary search tree(BST). This module does not come pre-installed with Python’s standard utility module. To install it type the below command in the terminal.

pip install binarytree

Creating Node

The node class represents the structure of a particular node in the binary tree. The attributes of this class are values, left, right.

Syntax: binarytree.Node(value, left=None, right=None)
Parameters:
value: Contains the data for a node. This value must be number.
left: Contains the details of left node child.
right: Contains details of the right node child.

Note: If left or right child node is not an instance of binarytree.Node class then binarytree.exceptions.NodeTypeError is raised and if the node value is not a number then binarytree.exceptions.NodeValueError is raised.
Example:

Python3

   from binarytree import Node 
root = Node(3) 
root.left = Node(6) 
root.right = Node(8) 
  
# Getting binary tree 
print('Binary tree :', root) 
  
# Getting list of nodes 
print('List of nodes :', list(root)) 
  
# Getting inorder of nodes 
print('Inorder of nodes :', root.inorder) 
  
# Checking tree properties 
print('Size of tree :', root.size) 
print('Height of tree :', root.height) 
  
# Get all properties at once 
print('Properties of tree : \n', root.properties) 
 
  

Output:

Binary tree :
3
/ \
6 8
List of nodes : [Node(3), Node(6), Node(8)]
Inorder of nodes : [Node(6), Node(3), Node(8)]
Size of tree : 3
Height of tree : 1
Properties of tree :
{‘height’: 1, ‘size’: 3, ‘is_max_heap’: False, ‘is_min_heap’: True, ‘is_perfect’: True, ‘is_strict’: True, ‘is_complete’: True, ‘leaf_count’: 2, ‘min_node_value’: 3, ‘max_node_value’: 8, ‘min_leaf_depth’: 1, ‘max_leaf_depth’: 1, ‘is_bst’: False, ‘is_balanced’: True, ‘is_symmetric’: False}

Build a binary tree from the List:

Instead of using the Node method repeatedly, we can use build() method to convert a list of values into a binary tree.
Here, a given list contains the nodes of tree such that the element at index i has its left child at index 2*i+1, the right child at index 2*i+2 and parent at (i – 1)//2. The elements at index j for j>len(list)//2 are leaf nodes. None indicates the absence of a node at that index. We can also get the list of nodes back after building a binary tree using values attribute.

Syntax: binarytree.build(values)
Parameters:
values: List representation of the binary tree.
Returns: root of the binary tree.

Example:

Python3

   # Creating binary tree  
# from given list 
from binarytree import build 
  
  
# List of nodes 
nodes =[3, 6, 8, 2, 11, None, 13] 
  
# Building the binary tree 
binary_tree = build(nodes) 
print('Binary tree from list :\n', 
      binary_tree) 
  
# Getting list of nodes from 
# binarytree 
print('\nList from binary tree :',  
      binary_tree.values) 
 
  

Output:

Binary tree from list :         ___3     /    \    6      8   / \      \  2   11     13      List from binary tree : [3, 6, 8, 2, 11, None, 13]

Build a random binary tree:

tree() generates a random binary tree and returns its root node.

Syntax: binarytree.tree(height=3, is_perfect=False)
Parameters:
height: It is the height of the tree and its value can be between the range 0-9 (inclusive)
is_perfect: If set True a perfect binary is created.
Returns: Root node of the binary tree.

Example:

Python3

   from binarytree import tree 
  
  
# Create a random binary  
# tree of any height 
root = tree() 
print("Binary tree of any height :") 
print(root) 
  
# Create a random binary  
# tree of given height 
root2 = tree(height = 2) 
print("Binary tree of given height :") 
print(root2) 
  
# Create a random perfect  
# binary tree of given height 
root3 = tree(height = 2, 
             is_perfect = True) 
print("Perfect binary tree of given height :") 
print(root3) 
 
  

Output:

Binary tree of any height :          14____       /      \      2        5__     /        /   \    6        1     13   /        /     /  \  7        9     4    8    Binary tree of given height :      1__   /   \  5     2       / \      4   3    Perfect binary tree of given height :        __3__     /     \    2       4   / \     / \  6   0   1   5

Building a BST:

The binary search tree is a special type of tree data structure whose inorder gives a sorted list of nodes or vertices. In Python, we can directly create a BST object using binarytree module. bst() generates a random binary search tree and return its root node.

Syntax: binarytree.bst(height=3, is_perfect=False)
Parameters:
height: It is the height of the tree and its value can be between the range 0-9 (inclusive)
is_perfect: If set True a perfect binary is created.
Returns: Root node of the BST.

Example:

Python3

   from binarytree import bst 
  
  
# Create a random BST  
# of any height 
root = bst() 
print('BST of any height : \n', 
      root) 
  
# Create a random BST of  
# given height 
root2 = bst(height = 2) 
print('BST of given height : \n', 
      root2) 
  
# Create a random perfect  
# BST of given height 
root3 = bst(height = 2,  
            is_perfect = True) 
print('Perfect BST of given height : \n', 
      root3) 
 
  

Output:

BST of any height :              ____9______         /           \      __5__       ____12___     /     \     /         \    2       8   10         _14   / \     /      \       /  1   4   7        11    13    BST of given height :          5     / \    4   6   /  3    Perfect BST of given height :          __3__     /     \    1       5   / \     / \  0   2   4   6

Importing heap:

Heap is a tree data structure that can be of two types –

max heap
min heap

Using the heap() method of binarytree library, we can generate a random maxheap and return its root node. To generate minheap, we need to set the is_max attribute as False.

Syntax: binarytree.heap(height=3, is_max=True, is_perfect=False)
Parameters:
height: It is the height of the tree and its value can be between the range 0-9 (inclusive)
is_max: If set True generates a max heap else min heap.
is_perfect: If set True a perfect binary is created.
Returns: Root node of the heap.

Python3

   from binarytree import heap 
  
  
# Create a random max-heap 
root = heap() 
print('Max-heap of any height : \n', 
      root) 
  
# Create a random max-heap 
# of given height 
root2 = heap(height = 2) 
  
print('Max-heap of given height : \n', 
      root2) 
  
# Create a random perfect  
# min-heap of given height 
root3 = heap(height = 2,  
             is_max = False,  
             is_perfect = True) 
  
print('Perfect min-heap of given height : \n', 
      root3) 
 
  

Output:

Max-heap of any height :               _______14______          /               \      ___12__            __13__     /       \          /      \    10        8        3        9   /  \      / \      / \      /  1    5    4   6    0   2    7    Max-heap of given height :          __6__     /     \    4       5   / \     / \  2   0   1   3    Perfect min-heap of given height :          __0__     /     \    1       3   / \     / \  2   6   4   5

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Binarytree Module in Python

Creating Node

Python3

Build a binary tree from the List:

Python3

Build a random binary tree:

Python3

Building a BST:

Python3

Importing heap:

Python3

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