Data Structure and Algorithm in Python

Welcome to the Data Structure and Algorithm in Python repository! This project contains implementations of fundamental data structures and algorithms using Python and Jupyter Notebooks. It serves as a learning resource and reference for understanding core computer science concepts.

Table of Contents

• Overview
• Prerequisites
• Installation
• Implemented Modules
  • Binary Search
  • Linked List
  • Queue
  • Recursion

Overview

This repository demonstrates how to implement and utilize common data structures and algorithms in Python. Each concept is explored in a dedicated Jupyter Notebook, providing code examples and explanations.

Note: If you are new to Python or need a quick refresher, checking out the Python Basics and Data Types guide is highly recommended.

Prerequisites

To run the code in this repository, you need:

• Python 3.x
• Jupyter Notebook or JupyterLab

Installation

1. Clone the repository:

   git clone https://github.com/Abhi-VIT/Data-Structure-and-Algorithm-in-Python.git
   cd Data-Structure-and-Algorithm-in-Python

2. Launch Jupyter Notebook:

   jupyter notebook

3. Open the desired .ipynb file to view and run the code.

Implemented Modules

Binary Search

File: Binary_Search.ipynb

This notebook demonstrates the Binary Search algorithm, an efficient way to find an element in a sorted array.

• Algorithm: Iteratively divides the search interval in half.
• Key Function: binary_search(arr, target)
• Complexity: O(log n)

Linked List

File: LinkedList.ipynb

This notebook provides a complete implementation of a Singly Linked List.

• Components:
  • node class: Represents a single node with data and a pointer to the next node.
  • LinkedList class: Manages the list.
• Operations:
  • append(data): Adds a node to the end.
  • insert_first(data): Adds a node to the beginning.
  • insert_last(data): Alias for append.
  • insert_position(data, position): Inserts a node at a specific index.
  • display(): Prints the list elements.

Queue

File: Queue.ipynb and Queues.py

This notebook explores Queue data structures using different approaches.

• List Implementation: managing a queue using a standard Python list (inefficient for large data sets due to O(n) pops from the beginning).
• Deque Implementation: Using collections.deque for efficient O(1) appends and pops from both ends.
• Custom Queue Class: A wrapper class around deque providing standard queue methods:
  • enqueue(val)
  • dequeue()
  • is_empty()
  • size()

Recursion

File: Recursion.ipynb

This notebook illustrates the concept of Recursion.

• Example: Calculating the factorial of a number.
• Concepts: Base case, recursive step, and recursion depth limits (demonstrating RecursionError).

---

Happy Coding!