From 678add8d415031280bca4b07e937ed9ef403cd9c Mon Sep 17 00:00:00 2001
From: Manasvi Reddy <manasvireddyk25@gmail.com>
Date: Sun, 5 Jul 2026 19:46:01 -0400
Subject: [PATCH] Done Trees-2

---
 Problem1.py | 51 +++++++++++++++++++++++++++++++++++++++++++++++++++
 Problem2.py | 35 +++++++++++++++++++++++++++++++++++
 2 files changed, 86 insertions(+)
 create mode 100644 Problem1.py
 create mode 100644 Problem2.py

diff --git a/Problem1.py b/Problem1.py
new file mode 100644
index 00000000..894d8ffd
--- /dev/null
+++ b/Problem1.py
@@ -0,0 +1,51 @@
+# Problem1 (https://leetcode.com/problems/construct-binary-tree-from-inorder-and-postorder-traversal/)
+# Time Complexity: O(n), We visit every node exactly once and each visit does constant work using dictionary lookup and a moving pointer
+# Space Complexity: O(n), We use a dictionary of size n to store index positions and the recursion stack can go up to depth n in the worst case
+# Approach: The last value in postorder is always the root of the current subtree so we read it using a pointer that moves backward
+# We use a dictionary to instantly find where that root sits in inorder so we know how many nodes go to the left and right
+# We always build the right subtree before the left subtree because reading postorder backward gives root then right side then left side
+
+# Definition for a binary tree node.
+# class TreeNode:
+#     def __init__(self, val=0, left=None, right=None):
+#         self.val = val
+#         self.left = left
+#         self.right = right
+class Solution:
+    def buildTree(self, inorder: List[int], postorder: List[int]) -> Optional[TreeNode]:
+        # this dictionary will store the index of every value in inorder so we never have to search for it later
+        self.map = {}       
+
+        # this pointer starts at the last index of postorder and will move backward as we build each root
+        self.postorder_index = len(postorder)-1
+
+        # fill the dictionary once so lookups later take constant time
+        for i in range(len(inorder)):
+            self.map[inorder[i]]=i
+        
+        # start building the tree using the full range of inorder, from index 0 to the last index
+        return self.helper(postorder,0,len(inorder)-1)
+    
+    def helper(self,postorder,start,end):
+        # if start has gone past end it means there are no elements left in this range so there is nothing to build
+        if start > end:
+            return None
+        
+        # the value at our current pointer position in postorder is always the root of this subtree
+        root_value = postorder[self.postorder_index]
+
+        # look up where this root value sits in inorder so we know how to split left and right parts
+        root_index = self.map[root_value]
+
+        # move the pointer one step back so the next call reads the correct next value
+        self.postorder_index -=1
+
+        # create the node for this root value
+        node = TreeNode(root_value)
+
+        # build the right subtree first since reading postorder backward gives right side nodes before left side nodes
+        node.right = self.helper(postorder,root_index+1, end)
+        # only after the right subtree is fully built do we build the left subtree
+        node.left = self.helper(postorder,start, root_index -1)
+
+        return node
\ No newline at end of file
diff --git a/Problem2.py b/Problem2.py
new file mode 100644
index 00000000..87824722
--- /dev/null
+++ b/Problem2.py
@@ -0,0 +1,35 @@
+# Problem2 (https://leetcode.com/problems/sum-root-to-leaf-numbers/)
+# Time Complexity: O(n), we visit every node exactly once
+# Space Complexity: O(h), h is the height of the tree, this space comes from the recursion call stack
+
+# Approach: We walk down the tree from root to leaf using recursion.
+# As we move to each node, we build a number by taking the number built so far, multiplying it by 10, then adding the current node's value.
+# When we reach a leaf node, the number is complete, so we add it to a running total.
+# We keep doing this for every path in the tree until all leaves are visited, then return the total.
+
+# Definition for a binary tree node.
+# class TreeNode:
+#     def __init__(self, val=0, left=None, right=None):
+#         self.val = val
+#         self.left = left
+#         self.right = right
+class Solution:
+    def sumNumbers(self, root: Optional[TreeNode]) -> int:
+        self.result = 0         # this will hold the total sum of all root to leaf numbers, starts at 0 since nothing is added yet
+        self.helper(root, 0)    # start the recursion at the root, with current_number as 0 since nothing has been built yet
+        return self.result  
+
+    def helper(self, root, current_number):
+        if root is None:  # if we have gone past a leaf, there is nothing to do here
+            return
+
+        current_number = current_number * 10 + root.val  
+        # shift the digits built so far one place to the left, then add the current node's value this is how numbers are built digit by digit.
+        if root.left is None and root.right is None:  # this means the current node is a leaf, no children on either side
+            self.result += current_number  
+            # since this is a leaf, current_number is now a complete root to leaf number, so we add it to the total
+
+        self.helper(root.left, current_number)  
+        # move to the left child, carrying forward the number built so far so it can keep building on it
+        self.helper(root.right, current_number)  
+        # move to the right child, carrying forward the same number built so far, independent of what the left side does
\ No newline at end of file