Study Revision Planner

A compact Flask app that creates spaced-repetition revision schedules from topics and an exam date. Built as a lightweight tool for students to plan study sessions using simple forgetting-curve intervals.

Features

• Generate per-topic revision sessions using difficulty-based intervals (easy/medium/hard).
• Dashboard: today's tasks, overdue alerts, upcoming timeline, and per-subject progress.
• Mark sessions done (persisted to JSON) with immediate UI feedback.
• Export the full schedule as CSV for external use.

Tech stack

• Python 3.10+ and Flask (see requirements.txt)
• Server-rendered HTML (Jinja2), CSS and a small JavaScript helper
• Storage: JSON file at data/study_data.json

Quick start (development)

1. Create a virtual env and install deps:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

2. Run the dev server (default port: 5001):

python app.py
# open http://127.0.0.1:5001

Usage

• Open the app in your browser.
• Fill the form: Subject name, Exam date, and one topic per line in the format Topic name | difficulty (difficulty: easy, medium, or hard).
• Click Generate schedule to persist the subject and build review sessions.
• Use Mark done to record completion; export with Export CSV.

Tests

Unit tests check the scheduler logic and exam-boundary edge cases.

Run all tests:

python -m unittest discover -v

Files with tests:

• tests/test_scheduler.py
• tests/test_scheduler_edges.py

Project layout

• app.py - Flask app, scheduling functions, and routes (index, add subject, toggle/reset session, export CSV)
• templates/index.html - dashboard and form
• static/styles.css, static/app.js - UI and small client helpers
• data/study_data.json - persisted data (empty by default)
• tests/ - unit tests

Deployment notes

This repo uses the Flask development server for simplicity. For production:

1. Use a WSGI server such as gunicorn or uWSGI.
2. Persist data using a real datastore (SQLite/Postgres) or ensure data/ is stored on a volume.
3. Ensure the app uses production data storage before publishing.

Example production run (quick):

pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:8000 app:app

License

MIT License - see LICENSE for details.

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Repository: https://github.com/Cletrix-Labs/study-revision-planner
Live Demo: https://reviseo.onrender.com

Built for quick ⭐ , organized revision planning.