EchoState: A Cloud-Powered Music Mood Tracker

SUSSY BAKA — Sun, 01 Mar 2026 12:44:01 +0000

This is a submission for the DEV Weekend Challenge: Community

The Community

I built EchoState for people who experience their emotions through music.

There are certain type of people who don't just play songs but feel them. I’m part of that community.

My friends and I listen to a lot of music, and even though we think we understand our moods throughout the day, I started wondering whether our music choices might tell a different story.

EchoState is for people like me who want to observe their emotional patterns through the music they choose. Not based on genre, not based on algorithm recommendations, but based on how they personally classify and feel their songs.

What I Built

I built EchoState, a music-based mood tracking web app where users can log the songs they’re listening to and associate each one with a mood and energy level.

Instead of automatically pulling data from streaming platforms, the app encourages intentional reflection. When logging a song, the user selects how the song feels to them — calm, nostalgic, hype, focus, etc. — along with an energy level from 1 to 5.

From that data, the app generates:

A mood distribution pie chart to show dominant emotional patterns
An energy trend graph to visualize shifts over time
A monthly mood calendar with color-coded days
A streak tracker for consistent daily logging
A weekly goal progress bar
Emoji-based milestone rewards
A dynamic background that adapts to the dominant mood

Users authenticate using Google login, and all data is stored securely in the cloud using Firebase Firestore with real-time syncing.
It can also be used on mobile from the link itself.

Demo

You can try EchoState live here:

🌐 Live App:
https://tourmaline-longma-cf965d.netlify.app/

To test it:

Log in using Google
Add a few songs with moods and energy levels
Refresh the page to see cloud persistence
Explore the mood pie chart, energy graph, calendar view, and streak tracker

All data is stored securely in the cloud and updates in real time.

Video Demo:

Code

The full source code is available on GitHub:

🔗 GitHub Repository:

SussyBakaJr / EchoState

EchoState - A cloud-powered emotional listening reflection web app built with Firebase Authentication and real-time Firestore.

🎧 EchoState A Music-Based Emotional Reflection Web App EchoState is a music-driven emotional tracking web application that helps users reflect on their mood patterns through the songs they listen to The idea began as a concept to integrate directly with Spotify, but due to API and integration constraints, the project evolved into a manually logged, cloud-powered emotional listening tracker — allowing deeper personal reflection and full customization.

Live App https://tourmaline-longma-cf965d.netlify.app/

🌟 Core Features

🔐Authentication & Cloud Sync

-Google Login & Logout (Firebase Authentication)

-Secure per-user cloud storage (Firestore)

-Real-time data syncing

-User-specific data isolation

🎵Song Logging System

-Add songs manually

-Select mood category

-Assign energy level (1–5)

-Timestamped logging

-Real-time delete support

📊Emotional Analytics Dashboard

-Mood Pie Chart Visual representation of dominant emotional patterns.

-Energy Trend Graph Track how your listening energy fluctuates over time.

-Monthly Mood Calendar View emotional patterns day-by-day with color-coded mood tracking.

-Weekly Goal Tracker Set…

View on GitHub

How I Built It

EchoState was built using a frontend-first architecture with cloud-based data persistence.
The interface was created using HTML5 and CSS3, with a glassmorphism-inspired design and dynamic theming that adapts to the user's dominant mood. Background particle animations are rendered using the Canvas API to create a soft, reactive atmosphere.
The application logic is written in Vanilla JavaScript (ES6). Mood tracking, streak calculation, weekly goal progress, and chart updates are all handled client-side.

For analytics and visualization, I used:

Chart.js for the mood distribution pie chart
A real-time energy trend line graph
A dynamically generated monthly calendar grid

Authentication is handled using Firebase Authentication (Google OAuth), and all user data is stored in Firebase Firestore.
This ensures:

Instant cloud sync
Proper per-user data isolation
Accurate streak and analytics recalculation

The project is deployed on Netlify.

Building a Revision Tracker with GitHub Copilot CLI

SUSSY BAKA — Sun, 15 Feb 2026 01:40:05 +0000

This is a submission for the GitHub Copilot CLI Challenge

What I Built

I built a CLI-based Exam Revision Tracker using Java that helps students organize and track their exam preparation directly from the terminal.

The application allows users to:

Add subjects
Add revision topics under each subject
Mark topics as completed
Track subject-wise progress
View overall progress percentage
Maintain a daily study streak
Persist data between sessions using file serialization

This tool was inspired by the fact that I recently went through a very chaotic exam experience. I did not want to lose track of what has already been revised. So I wanted a lightweight, distraction-free productivity system that runs entirely in the terminal.

Demo

Using gh copilot -i

Interactive CLI Main Menu

Adding Subjects and Topics

Progress Calculation & Study Streak Tracking

Data Persistence Across Sessions

My Experience with GitHub Copilot CLI

This is my first time participating in a developer challenge, and I’m still very new to building full applications independently. Because of that, GitHub Copilot CLI became an incredibly valuable learning companion throughout this project.

I used GitHub Copilot CLI directly inside my terminal throughout development.

Instead of switching between browser tabs and documentation, I was able to:

Generate OOP class structures
Design encapsulated Java classes
Implement progress calculation logic
Add Java serialization for data persistence
Refine the study streak algorithm using LocalDate
Improve overall code organization

Prompts I used:

gh copilot -i "design the class structure for a CLI based exam revision tracker in Java using OOP principles"

gh copilot -p "write a Java class Subject that contains a subjectName and a list of Topic objects with progress calculation

gh copilot -p "how to implement Java object serialization to save application state"

Copilot CLI significantly reduced development friction and gave me the confidence to experiment with features like persistence and streak tracking — things I might have avoided as a beginner.

The most impactful aspect was how quickly I could prototype structured, clean OOP components without breaking my development flow.

As a newcomer, this experience showed me how powerful AI-assisted development can be — not as a replacement for understanding, but as a tool that accelerates learning and iteration.

Github Repository: https://github.com/SussyBakaJr/exam-revision-tracker-cli/tree/main

DEV Community: SUSSY BAKA

EchoState: A Cloud-Powered Music Mood Tracker

The Community

What I Built

Demo

Code

SussyBakaJr / EchoState

EchoState - A cloud-powered emotional listening reflection web app built with Firebase Authentication and real-time Firestore.

How I Built It

Building a Revision Tracker with GitHub Copilot CLI

What I Built

Demo

My Experience with GitHub Copilot CLI