From f8f9f98dffa675a23071887613d6fcd0fb16ee3e Mon Sep 17 00:00:00 2001
From: Vir Bhojani <141424554+Veer567@users.noreply.github.com>
Date: Mon, 21 Oct 2024 07:36:30 +0530
Subject: [PATCH 1/2] Create  Fibonacci_series_with_classes.py

This Python program calculates the Fibonacci series using a class with memoization. The Fibonacci class has a calculate method that recursively computes Fibonacci numbers, storing previously calculated results in a dictionary to improve efficiency. The print_series method outputs the series up to a specified count. This approach is optimized for performance by avoiding redundant calculations through memoization.
---
 Python/Fibonacci_series_with_classes.py | 26 +++++++++++++++++++++++++
 1 file changed, 26 insertions(+)
 create mode 100644 Python/Fibonacci_series_with_classes.py

diff --git a/Python/Fibonacci_series_with_classes.py b/Python/Fibonacci_series_with_classes.py
new file mode 100644
index 0000000..bc69246
--- /dev/null
+++ b/Python/Fibonacci_series_with_classes.py
@@ -0,0 +1,26 @@
+class Fibonacci:
+    def __init__(self):
+        self.memo = {}  # Dictionary to store calculated Fibonacci numbers for optimization
+
+    def calculate(self, n):
+        # Base cases
+        if n <= 0:
+            return 0
+        elif n == 1:
+            return 1
+        
+        # Check if Fibonacci number is already calculated
+        if n in self.memo:
+            return self.memo[n]
+        
+        # Calculate the Fibonacci number and store it in the dictionary (memoization)
+        self.memo[n] = self.calculate(n-1) + self.calculate(n-2)
+        return self.memo[n]
+
+    def print_series(self, count):
+        for i in range(count):
+            print(self.calculate(i), end=" ")
+
+# Example usage
+fib = Fibonacci()
+fib.print_series(10)  # Output: 0 1 1 2 3 5 8 13 21 34

From 3c5f411189735b7f645cf28cc3fa84e9b75a08cf Mon Sep 17 00:00:00 2001
From: Vir Bhojani <141424554+Veer567@users.noreply.github.com>
Date: Mon, 21 Oct 2024 10:02:50 +0530
Subject: [PATCH 2/2] Create Binary_Tree.py

A Binary Tree is a hierarchical data structure where each node has at most two children, referred to as the left and right child.

In-Order Traversal is a tree traversal method where nodes are visited in the following order:

Visit the left subtree.
Visit the root node.
Visit the right subtree.
In in-order traversal, the elements of a binary tree are processed in a sorted sequence (for a binary search tree). This is useful for retrieving data in a specific order.
---
 Python/Binary_Tree.py | 26 ++++++++++++++++++++++++++
 1 file changed, 26 insertions(+)
 create mode 100644 Python/Binary_Tree.py

diff --git a/Python/Binary_Tree.py b/Python/Binary_Tree.py
new file mode 100644
index 0000000..34b23c3
--- /dev/null
+++ b/Python/Binary_Tree.py
@@ -0,0 +1,26 @@
+class TreeNode:
+    def __init__(self, data):
+        self.data = data
+        self.left = None
+        self.right = None
+
+class BinaryTree:
+    def __init__(self):
+        self.root = None
+
+    def inorder_traversal(self, node):
+        if node:
+            self.inorder_traversal(node.left)
+            print(node.data, end=" ")
+            self.inorder_traversal(node.right)
+
+# Example usage
+tree = BinaryTree()
+tree.root = TreeNode(1)
+tree.root.left = TreeNode(2)
+tree.root.right = TreeNode(3)
+tree.root.left.left = TreeNode(4)
+tree.root.left.right = TreeNode(5)
+
+print("In-order Traversal:")
+tree.inorder_traversal(tree.root)  # Output: 4 2 5 1 3