Python Program to Construct a Tree & Perform Insertion, Deletion, Display

When building a tree data structure in Python, we need to construct a tree and perform operations such as inserting an element, deleting an element and displaying elements of the tree. This can be achieved by defining a class with methods for these operations.

Below is a demonstration of the same −

Tree Structure Implementation

class Tree_struct:
    def __init__(self, data=None, parent=None):
        self.key = data
        self.children = []
        self.parent = parent

    def set_root(self, data):
        self.key = data

    def add_node(self, node):
        self.children.append(node)

    def search_node(self, key):
        if self.key == key:
            return self
        for child in self.children:
            temp = child.search_node(key)
            if temp is not None:
                return temp
        return None

    def remove_node(self):
        parent = self.parent
        index = parent.children.index(self)
        parent.children.remove(self)
        for child in reversed(self.children):
            parent.children.insert(index, child)
            child.parent = parent

    def bfs(self):
        queue = [self]
        while queue != []:
            popped = queue.pop(0)
            for child in popped.children:
                queue.append(child)
            print(popped.key, end=' ')

my_instance = None

print('Menu (this assumes no duplicate keys)')
print('add <data> at root')
print('add <data> below <data>')
print('remove <data>')
print('display')
print('quit')

while True:
    do = input('What would you like to do? ').split()

    operation = do[0].strip().lower()
    if operation == 'add':
        data = int(do[1])
        new_node = Tree_struct(data)
        suboperation = do[2].strip().lower()
        if suboperation == 'at':
            my_instance = new_node
        elif suboperation == 'below':
            position = do[3].strip().lower()
            key = int(position)
            ref_node = None
            if my_instance is not None:
                ref_node = my_instance.search_node(key)
            if ref_node is None:
                print('No such key.')
                continue
            new_node.parent = ref_node
            ref_node.add_node(new_node)

    elif operation == 'remove':
        data = int(do[1])
        to_remove = my_instance.search_node(data)
        if my_instance == to_remove:
            if my_instance.children == []:
                my_instance = None
            else:
                leaf = my_instance.children[0]
                while leaf.children != []:
                    leaf = leaf.children[0]
                leaf.parent.children.remove(leaf)
                leaf.parent = None
                leaf.children = my_instance.children
                my_instance = leaf
        else:
            to_remove.remove_node()

    elif operation == 'display':
        if my_instance is not None:
            print('Breadth First Search traversal is : ', end='')
            my_instance.bfs()
            print()
        else:
            print('The tree is empty')

    elif operation == 'quit':
        break

Output

Menu (this assumes no duplicate keys)
add <data> at root
add <data> below <data>
remove <data>
display
quit
What would you like to do? add 5 at root
What would you like to do? add 6 below 5
What would you like to do? add 8 below 6
What would you like to do? remove 8
What would you like to do? display
Breadth First Search traversal is : 5 6
What would you like to do? quit

How It Works

The Tree_struct class contains the following key components ?

• __init__() − Initializes a node with data, an empty children list, and parent reference

• add_node() − Appends a child node to the current node's children list

• search_node() − Recursively searches for a node with the given key value

• remove_node() − Removes a node and promotes its children to the parent level

• bfs() − Performs breadth-first search traversal using a queue

Key Operations

The interactive menu supports these operations ?

• add <data> at root − Creates a new root node

• add <data> below <parent> − Adds a child node under an existing parent

• remove <data> − Removes a node and handles child redistribution

• display − Shows the tree using breadth-first traversal

• quit − Exits the program

Conclusion

This implementation demonstrates a general tree structure with interactive operations for insertion, deletion, and display. The breadth-first search traversal provides an efficient way to visit all nodes level by level.