EduTech - Personalized Study Plan Generator Backend

A dynamic study plan system that adjusts based on difficulty, available time, upcoming exams, and missed or completed tasks.

Features

• Task Management: Create, update, and track study tasks with difficulty levels and deadlines
• Dynamic Scheduling: Automatically generates personalized study plans based on:
  • Task difficulty (1-5 scale)
  • Priority status (Pending, Ongoing, Completed)
  • Time urgency (proximity to due date)
  • Available study hours per day
• Adaptive Planning: Adjusts study plans when tasks are missed or completed
• Progress Tracking: Monitor completion rates, overdue tasks, and study statistics
• Smart Prioritization: Calculates priority scores combining difficulty, status, and urgency

Installation

1. Clone the repository:

git clone https://github.com/sannman/studyplan-backend.git
cd studyplan-backend

2. Install uv (if not already installed):

curl -LsSf https://astral.sh/uv/install.sh | sh

3. Install dependencies:

uv sync

Running the Application

Start the Flask development server:

uv run python -m src.backend.app

The server will start on http://localhost:5000

For development with debug mode enabled:

FLASK_DEBUG=true uv run python -m src.backend.app

For production: Use a production WSGI server like gunicorn or waitress:

uv add gunicorn
uv run gunicorn -w 4 -b 0.0.0.0:5000 src.backend.app:app

API Endpoints

Health Check

GET /health

Returns server status.

Task Management

Create Task

POST /post_task
Content-Type: application/json

{
  "task_name": "Study Calculus Chapter 1",
  "scale_difficulty": 4,
  "priority": "Pending",
  "timedue": "2026-01-15T10:00:00Z"
}

Get All Tasks

GET /get_tasks

Update Task Status

PUT /update_task_status
Content-Type: application/json

{
  "task_name": "Study Calculus Chapter 1",
  "new_status": "Completed"
}

Delete Task

DELETE /delete_task/<task_name>

Get Tasks by Status

GET /tasks_by_status/<status>

Status can be: Pending, Ongoing, or Completed

Study Planning

Calculate Task Scores

GET /score_tasks

Returns priority scores for all tasks based on difficulty, priority, and time urgency.

Generate Study Plan

POST /generate_plan
Content-Type: application/json

{
  "available_hours_per_day": 4.0,
  "study_session_duration": 1.0
}

Generates a complete study schedule with session timings.

Mark Task as Missed

POST /mark_missed/<task_name>

Increases priority and regenerates the study plan.

Task Queries

Get Upcoming Tasks

GET /upcoming_tasks?days_ahead=7

Get Overdue Tasks

GET /overdue_tasks

Get Statistics

GET /stats

Returns overall statistics including completion rate, average difficulty, and task counts.

Priority Scoring Algorithm

The system calculates priority scores using:

Score = Difficulty Weight × Priority Weight × Time Weight

• Difficulty Weight: 1.0 (easy) to 3.0 (very hard)
• Priority Weight:
  • Pending: 1.0
  • Ongoing: 2.0
  • Completed: 0.0
• Time Weight: Increases as deadline approaches
  • Overdue: 5.0
  • Due within 24 hours: 4.5
  • Due within 3 days: 3.5
  • Due within 7 days: 2.5
  • Due within 14 days: 1.5
  • Due later: 1.0

Example Usage

Creating Tasks and Generating a Study Plan

# Create tasks
curl -X POST http://localhost:5000/post_task \
  -H "Content-Type: application/json" \
  -d '{
    "task_name": "Physics Exam Prep",
    "scale_difficulty": 5,
    "priority": "Ongoing",
    "timedue": "2026-01-08T14:00:00Z"
  }'

# Generate study plan
curl -X POST http://localhost:5000/generate_plan \
  -H "Content-Type: application/json" \
  -d '{"available_hours_per_day": 5.0, "study_session_duration": 1.5}'

# Check statistics
curl http://localhost:5000/stats

# Mark task as completed
curl -X PUT http://localhost:5000/update_task_status \
  -H "Content-Type: application/json" \
  -d '{"task_name": "Physics Exam Prep", "new_status": "Completed"}'

Data Storage

The application now uses a lightweight local SQLite database for persistence:

• db/studyplan.db: Stores task records and calculated priority scores

Architecture

• app.py: Flask REST API endpoints
• planner.py: Core scheduling and prioritization algorithms
• data.py: SQLite-based data persistence layer

Technologies

• Python 3.13+
• Flask 3.1.2
• Flask-CORS 6.0.2
• Pydantic 2.12.5
• Python-dotenv 1.2.1