This repository is a curated collection of Python projects, algorithm implementations, and utility scripts developed for learning, practice, and demonstration purposes. It brings together various small-scale applications, classic algorithms, and practical tools, all written in Python. The collection showcases a mix of programming concepts, problem-solving techniques, and algorithmic thinking.
The projects included range from application-based solutions like a Budget App, Time Calculator, Polygon Area Calculator, and Probability Calculator, each designed to solve a specific task or automate a particular operation. These projects often involve user interaction, input validation, and practical use cases, making them valuable for beginners looking to understand how Python can be applied to real-world problems.
Alongside these applications, the repository contains implementations of well-known algorithms such as Merge Sort, Binary Search Tree, Shortest Path Algorithm, and the Luhn Algorithm. These algorithmic solutions demonstrate fundamental concepts in computer science, including sorting, searching, graph traversal, and validation techniques. They are useful references for anyone looking to strengthen their understanding of data structures and algorithms using Python.
The utility scripts—like a Password Generator, Case Converter, Equation Solver, and Cipher Program—serve as practical examples of Python’s versatility in handling everyday tasks and programming challenges. Other classic problems like the Tower of Hanoi and Sudoku Solver are included to showcase algorithmic problem-solving in action.
This repository is structured to be a resource for learners, educators, and developers who want quick access to Python-based solutions and code examples. Each script or project is organized in a way that makes it easy to navigate, understand, and reuse. Where applicable, comments and documentation are provided to explain the logic and approach behind the code.
Whether you're looking to study algorithms, explore Python project ideas, or find coding practice challenges, this collection aims to offer a solid starting point and a handy reference for Python enthusiasts of all levels.