Inorder Binary Tree Traversal (using Python)

Question:

I am trying to perform an inorder traversal of a tree. The code itself feels right, except it is not working properly. I have a feeling it has to either do with the if condition, how append works in python, or something perhaps with return. This works correctly if I use print instead of return, I think, but I want to be able to use return and still get the correct answer. For example, for the tree [1,None,2,3], my code returns [1] which is clearly incorrect.

Additionally is it possible to solve this problem using list comprehension? If so, any sample code would be greatly appreciated.

Here is my code:

    class Solution(object):
        def inorderTraversal(self, root):
            res = []
            if root:
                self.inorderTraversal(root.left)
                res.append(root.val)
                self.inorderTraversal(root.right)
            return res

Also before marking this as a duplicate, I know in order traversals have been asked on Stackoverflow (plenty of times), but none of them helped me understand why my understanding is wrong. I would be so grateful if someone helped me learn how to correct my approach versus simply posting another link without explanation. Thank you so much!

Asked By: Jane Sully

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Answers:

The reason this doesn’t work is that res only has the value of the first node you give it appended to it; each time you recursively recall the function, it just makes a new res. It is a simple fix though, as follows:

class Solution(object):
    def inorderTraversal(self, root):
        res = []
        if root:
            res = self.inorderTraversal(root.left) 
            res.append(root.val)
            res = res + self.inorderTraversal(root.right)
        return res

In this, it returns the left branch, the value, and then the right. This can be done much more briefly as follows:

class Solution(object):
    def inorderTraversal(self, root):
        return (self.inorderTraversal(root.left) + [root.val] + self.inorderTraversal(root.right)) if root else []

Use this instead , a simple recursion ::

class Node:
    def __init__(self,key):
        self.left = None
        self.right = None
        self.val = key

def printInorder(root):
    if root:
        printInorder(root.left)
        print(root.val)
        printInorder(root.right)

def printPostorder(root):
    if root:
        printPostorder(root.left)
        printPostorder(root.right)
        print(root.val)

def printPreorder(root):
    if root:
        print(root.val)
        printPreorder(root.left)
        printPreorder(root.right)

# Driver code
root = Node(1)
root.left      = Node(2)
root.right     = Node(3)
root.left.left  = Node(4)
root.left.right  = Node(5)
print "Preorder traversal of binary tree is"
printPreorder(root)

print "nInorder traversal of binary tree is"
printInorder(root)

print "nPostorder traversal of binary tree is"
printPostorder(root)

Source :: here

Answered By: Akash Kandpal

@Benedict Randall Shaw’s answer is already perfect. I just want to add some fun to it in a pythonic way. Although the doc does not suggest using a mutable object as default parameter, this will somewhat simplify the code by treating the default mutable list as a class member of the python function.

The difference is only the += is replaced by =, since the res is always the same list object inside the function before the function object is garbage collected.

def inorderTraversal(root, res=[]):
    if root:
        res = inorderTraversal(root.left)
        res.append(root.val)
        res = inorderTraversal(root.right)
return res
Answered By: Yossarian42

Yet another approach to output a list, the advantage being that you need to add values only to a single list:

def inorder(root):
    return_list = []
    def innerInOrder(root):
        if root == None:
          return
        innnerInOrder(root.left)
        return_list.append(root.data)
        innerInOrder(root.right)
    innerInOrder(root)
    return return_list
Answered By: okay

You could just declare the list outside the function so that it does not create a new list everytime you call the function ( since it’s a recursive function), but you could use other approaches posted. 🙂

Answered By: Abhinav Reddy
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