LoopOS (Work in Progress)

LoopOS is a personal behavior tracking and analytics system that I am currently building to better understand daily patterns and improve decision-making over time.

The idea is simple: log daily actions, analyze patterns, and gradually evolve the system into something that can provide meaningful insights and predictions.

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Current Status

This project is actively under development.

Completed (v0):

• Basic backend setup using FastAPI
• Data logging (task, mood, time spent)
• SQLite database integration

In Progress:

• Data retrieval and display
• Basic frontend interface
• Initial analytics (trends, summaries)

Planned:

• Data visualization dashboard
• Machine learning models for prediction
• Improved UI/UX
• Deployment

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Concept

LoopOS is built around feedback loops:

Action → Data → Analysis → Insight → Improvement

Instead of just tracking activities, the goal is to create a system that learns from behavior and helps optimize it over time.

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Tech Stack

• Backend: Python, FastAPI
• Database: SQLite
• Analytics: pandas (planned)
• Machine Learning: scikit-learn (planned)
• Frontend: HTML, CSS, JavaScript

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Project Structure

loopos/
│
├── backend/
│   ├── app/
│   │   ├── main.py
│   │   ├── models.py
│   │   ├── schemas.py
│   │   ├── database.py
│   │   ├── routes/
│   │   ├── services/
│   │   └── utils/
│   │
│   └── requirements.txt
│
├── frontend/
│   ├── index.html
│   ├── script.js
│   └── style.css
│
└── README.md

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Running Locally

cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload

Open:

• API Docs → http://127.0.0.1:8000/docs
• Frontend → open frontend/index.html

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Why I’m Building This

I've started building LoopOS as a personal improvement project. I wanted a way to understand how I actually spend my time, instead of relying on assumptions.

I'm most interested in understanding patterns: when I’m productive, when I lose focus, and how my behavior changes over time.

This project is an attempt to combine that curiosity with engineering, gradually evolving a simple logging system into something that can provide meaningful insights and support better decisions.

LoopOS is an attempt to go beyond logging and build a system that can eventually:

• identify patterns
• highlight inefficiencies
• suggest better actions

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Notes

This project is being built incrementally, focusing first on core functionality before adding advanced features like analytics and machine learning.

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Upcoming Focus

• Connecting frontend with backend data
• Adding basic analytics using pandas
• Improving data structure for future ML models

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