https://github.com/learning-zone/python-project

https://github.com/learning-zone/python-project

Last synced: 5 days ago
JSON representation

• Host: GitHub
• URL: https://github.com/learning-zone/python-project
• Owner: learning-zone
• License: gpl-3.0
• Created: 2026-06-06T06:46:30.000Z (23 days ago)
• Default Branch: main
• Last Pushed: 2026-06-06T17:34:35.000Z (22 days ago)
• Last Synced: 2026-06-06T19:14:56.360Z (22 days ago)
• Language: PHP
• Size: 41 MB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md
  • Agents: Agents.md

Awesome Lists containing this project

README

          
# Learning Management System (LMS)

The Learning Management System is a comprehensive, multi-tenant **Student Information System (SIS)** and **Learning Management System (LMS)** designed for K-12 schools, universities, and large educational districts. It combines a secure, highly scalable **Django** backend with a high-performance **React.js (Vite)** frontend to manage entire institutional workflows.

## Features

### Enterprise & School Administration 

- **Multi-Tenant Architecture**: Isolate data completely for different school branches, campuses, or independent districts under a single deployment.

- **Advanced Role-Based Access Control (RBAC)**: Fine-grained permissions matching academic hierarchies: Super Admins, Principal, Registrars, Finance Officers, Teachers, Students, and Parents.

- **Parent-Teacher Portal**: Dedicated secure view for guardians to track attendance, report cards, fee balances, and communicate directly with teachers.

- **Student Information System (SIS)**: Handle admissions, digital student profiles, records management, and automatic generation of transcripts.

- **Attendance & Timetable Automation**: Automated scheduling engines to handle complex recurring timetables, class allocations, and daily biometric/digital attendance.

### Academic & LMS Features

- **Course Creation and Enrollment**: Dynamic curriculum mapping, syllabus management, and enrollment thresholds.

- **Content Delivery**: Secure streaming for course materials, integration with AWS S3 for media storage, and timed quizzes.

- **Progress Tracking & AI Analytics**: Executive dashboard monitoring class performance, attrition indicators, and performance trends.

- **Discussion Forums**: Real-time collaborative channels featuring moderation controls for compliance.

### Finance & Operations

- **Automated Fee Management**: Invoice creation, automated payment reminders, custom fee structures, and scholarship allocations.

- **Payment Gateway Integration**: Production-ready support for Stripe, Razorpay, or PayPal with secure multi-currency processing.

- **Audit Trails & Security Compliance**: Comprehensive tracking logs logging every administrative action (who changed a grade, who authorized a refund) for compliance audits.

## Technologies Used



     

     

     

     

     

     

     

     

     



- **Python**: Core backend language targeting Python 3.10+.

- **Django & DRF**: Python web framework paired with Django REST Framework for building enterprise-grade APIs.

- **drf-yasg**: Auto-generated OpenAPI/Swagger interactive API documentation.

- **React.js & Redux Toolkit**: Client-side state hydration and dynamic dashboard UI architecture.

- **Vite**: Lightning-fast frontend build tool and dev server.

- **PostgreSQL**: Relational database engine utilizing schema-based multi-tenancy.

- **Redis & Celery**: Background task queueing engine managing heavy administrative workloads like mass-email reports, fee invoices, and PDF generation.

- **Gunicorn**: Production-grade WSGI server for serving the Django application.

- **AWS S3 & django-storages**: Cloud object storage for media files and static assets via `boto3`.

- **Docker**: Standardized containerization across staging, development, and production clusters.

---

## Configuration & Environment Variables

Before executing the steps below, you **must** configure your environment variables. Create a `.env` file in both the `backend` and `frontend` directories using the reference templates below:

### Backend Configuration (`backend/.env`)

```env

DEBUG=False

SECRET_KEY=your-production-super-secret-key

ALLOWED_HOSTS=yourschool.com,localhost

# Database Configuration

DATABASE_URL=postgres://user:password@localhost:5432/school_db

# Redis & Celery

CELERY_BROKER_URL=redis://localhost:6379/0

# Storage & Payment Keys

AWS_ACCESS_KEY_ID=your_aws_key

AWS_SECRET_ACCESS_KEY=your_aws_secret

STRIPE_SECRET_KEY=sk_live_your_key

```

### Frontend Configuration (`frontend/.env`)

```env

VITE_API_BASE_URL=http://localhost:8000/api/v1

VITE_STRIPE_PUBLIC_KEY=pk_test_your_key

```

---

## Getting Started

1. **Clone the Repository**:

   ```bash

   git clone https://github.com/learning-zone/python-project.git

   ```

2. **Backend Setup**:

   - Navigate to the `lms/lms-backend` directory.

   - Install dependencies:

     ```bash

     pip install poetry

     poetry install

     ```

   - Set up the database:

     ```bash

     poetry run python manage.py migrate

     ```

   - Start your background workers (Celery/Redis):

     ```bash

     poetry run celery -A core worker --loglevel=info

     ```

   - Run the development server:

     ```bash

     poetry run python manage.py runserver

     ```

   - Run the test suite:

     ```bash

     poetry run coverage run manage.py test

     poetry run coverage report

     ```

3. **Frontend Setup**:

   - Navigate to the `lms/lms-web` directory.

   - Install dependencies:

     ```bash

     yarn install

     ```

   - Start the frontend application locally:

     ```bash

     yarn dev

     ```

4. **Access the Application**:

   - Backend API Docs: http://localhost:8000/api/docs/

   - Frontend Client: http://localhost:5173

---

## Docker Deployment Setup

For automated cloud deployment (AWS, GCP, Render), we recommend containerization using the built-in configuration.

To spin up the entire ecosystem (Django, React, Postgres, Redis, Celery) run:

```bash

docker-compose up --build

```

---

## Development Flow

1. Create a new feature branch: `git checkout -b feature/-`

2. Develop the feature, committing atomic changes.

3. Ensure backend and frontend tests pass:

   ```bash

   yarn run test

   poetry run python manage.py test

   ```

4. Create a Pull Request and get feedback.

5. After approval, merge into the `develop` branch.

## Contributing

Contributions are more than welcome! Please follow the guidelines in CONTRIBUTING.md.

## License

This project is licensed under the GPL-3.0 License. See [LICENSE](LICENSE) for details.