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AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP • AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP • AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP •
AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP • AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP • AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP •
Nikhil Shah.

Architecting resilient digital infrastructure and minimalist product experiences.

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Dice Game Python CLI
Case Study // Active Record

Dice Game Python CLI.

Strategy & Vision

"Building core programming logic through simulation Developed a CLI-based system to simulate gameplay and handle user interaction."

Technical Stack

Python

External Assets

Launch Deployment
Technical Source

Overview

This project is a command-line dice game built in Python, designed to simulate a simple competitive game between a user and the computer.

The focus of this project was to strengthen core programming concepts such as control flow, randomness, and user interaction in a CLI environment.

Problem

As an early-stage project, the goal was to move beyond basic syntax and build a complete, interactive program that handles user input, game logic, and result tracking.

Approach

The system was built using Python and the random module to simulate dice rolls.

The game logic includes:

  • generating random values for both player and computer
  • comparing outcomes
  • tracking wins, losses, and draws across multiple rounds

A menu-driven CLI interface was implemented to manage gameplay and replay functionality.

Key Features

  • Interactive command-line gameplay
  • Configurable number of rounds
  • Score tracking for player and computer
  • Replay functionality
  • Clean and modular Python code structure

Outcome

This project helped build a strong foundation in Python programming, particularly in handling logic, loops, and user interaction.

It represents an early step toward building more structured and system-oriented applications.

Process Gallery

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