Shivram Sambhus
Software Developer (⌐■_■) Showcasing my creations: a collection of projects I've worked on, from coding experiments to design explorations
Projects
Typer-Diff, a npm package for comparing two typed strings
Developed Typer Diff, a lightweight library that compares two strings and provides detailed reporting on differences between them. Utilized TypeScript for type safety and implemented auto-versioning using Changeset for efficient release tracking.
Yearbook Photo System with Integrated E-Commerce
Designed and developed an automated yearbook photo system for Gymnasium Oberwil using Vercel, Supabase Email OTP, Wallee, and Twint. Implemented secure authentication, e-commerce functionality, and streamlined photo capture process with custom QR codes, PDF generation, and image downloads.
Browser-Based Multiplayer Game with AI-Powered Opponents
Developed a browser-based multiplayer game with AI-powered opponents using Svelte, Golang, and Python. Implemented a game server in Golang to handle game logic and communication, while training AI bots using reinforcement learning in Python. Trained the AI bots using deep reinforcement learning library Stable Baselines 3.
Computational Biology Simulations of Evolution and Virus propagation
Utilized JavaScript to create visualizations for genome probability, mutational evolution, species distribution over time, and virus spread during the 'biology in code' summer school program at EPFL and School of Computer and Communications Science.
MMDL · A music archiving tool
Developed Mega Music Downloader (MMDL), a Python package for efficiently archiving songs from YouTube. Utilized async code, multithreading, and PyPI publication to ensure fast and seamless downloading, while providing an intuitive interface and flexible usage methods. Featured technologies include Python, PyPI, YouTube-DL, AsyncIO, and Multithreading.
Textharvester · Domain specific web crawler and downloader
Developed TextHarvester, a Python package for collecting and crawling URLs from the Internet and downloading website content into text files. Utilized a depth-first algorithm to efficiently collect a large amount of text data for general-purpose NLP tasks. Featured technologies include PyPI, YouTube-DL, AsyncIO, and Multithreading.