Skip to content

PatrickFanella/clustr

Repository files navigation

Reddit Cluster Map

Reddit Cluster Map is a full-stack data visualization project that crawls Reddit, models relationships between communities and users, and renders those connections as an interactive graph. As a portfolio piece, it highlights the kind of work I do professionally: backend systems, data pipelines, APIs, performance-minded frontend development, and production-ready tooling.

Why this project stands out

  • End-to-end ownership — designed and built across backend, database, graph processing, frontend, and developer tooling
  • Strong backend fundamentals — Go services for crawling, API delivery, graph precalculation, rate limiting, retries, and scheduled jobs
  • Data and graph engineering — PostgreSQL-backed normalized storage with precomputed graph data and community detection
  • Interactive frontend — React + TypeScript UI with 2D/3D network visualization, dashboards, and inspection workflows
  • Production mindset — Dockerized local stack, CI workflows, Prometheus/Grafana monitoring, performance testing, and security-focused docs

Tech stack

  • Backend: Go, PostgreSQL, sqlc, REST APIs
  • Frontend: React, TypeScript, Vite, D3, Three.js
  • Infrastructure & quality: Docker, GitHub Actions, Prometheus, Grafana, Vitest, Playwright

What it demonstrates

This project highlights my ability to:

  • build and structure multi-service applications
  • work comfortably across APIs, databases, and frontend visualization
  • design for reliability with retries, rate limiting, monitoring, and testing
  • turn complex data into an experience that is useful, performant, and easy to explore

Quick links

If you're reviewing this as part of my portfolio, the main takeaway is simple: Reddit Cluster Map reflects full-stack product engineering with an emphasis on data-heavy systems, clear architecture, and polished execution.

About

A full-stack application for collecting, analyzing, and visualizing Reddit communities and their user interactions as network graphs.

Topics

Resources

Contributing

Stars

Watchers

Forks

Contributors