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level_order_traversal_binary_tree.py
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level_order_traversal_binary_tree.py
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'''Level order traversal of a binary tree is breadth first traversal for the tree.
I have implemented the solution using queue.
Algorithm:
For each node, first the node is visited and then it’s child nodes are put in a FIFO queue.
printLevelorder(tree)
1) Create an empty queue q
2) temp_node = root /*start from root*/
3) Loop while temp_node is not NULL
a) print temp_node->data.
b) Enqueue temp_node’s children
(first left then right children) to q
c) Dequeue a node from q.
Implementation:
Here is a simple implementation of the above algorithm. Queue is implemented using an array with maximum size of 500. We can implement queue as linked list also.
'''
# Python program to print level
# order traversal using Queue
# A node structure
class Node:
# A utility function to create a new node
def __init__(self ,key):
self.data = key
self.left = None
self.right = None
# Iterative Method to print the
# height of a binary tree
def printLevelOrder(root):
# Base Case
if root is None:
return
# Create an empty queue
# for level order traversal
queue = []
# Enqueue Root and initialize height
queue.append(root)
while(len(queue) > 0):
# Print front of queue and
# remove it from queue
print (queue[0].data)
node = queue.pop(0)
#Enqueue left child
if node.left is not None:
queue.append(node.left)
# Enqueue right child
if node.right is not None:
queue.append(node.right)
#Driver Code
root = Node(int(input()))
root.left = Node(int(input()))
root.right = Node(int(input()))
root.left.left = Node(int(input()))
root.left.right = Node(int(input()))
root.right.left=Node(int(input()))
root.right.right=Node(int(input()))
print ("Level Order Traversal of binary tree is -")
printLevelOrder(root)
'''
TestCase:
1.
Input :
1 2 3 4 5
Explanation :
The tree will look like this
1
2 3
4 5
Output :
Level Order traversal of binary tree is
1 2 3 4 5
2.
Input :
15 10 20 8 12 16 25
Explanation:
The tree will look like this
15
10 20
8 12 16 25
Output :
Level Order traversal of binary tree is
15 10 20 8 12 16 25
Time Complexity: O(n) where n is number of nodes in the binary tree
Space Complexity: O(n) where n is number of nodes in the binary tree
'''