Med Consultation API

The Med Consultation API is a Django Rest Framework (DRF) based platform designed for online medical consultations, appointment scheduling, and patient management.

Table of Contents

1. Features
2. Technologies Used
3. Project Structure
4. Installation
5. Environment Variables
6. Running the Application
7. API Documentation
8. Best Practices Followed
9. Contributing
10. License

---

Features

• User authentication and authorization using Django Rest Framework's Token Authentication
• Role-based access control (Doctors, Patients, Admin)
• Appointment scheduling and management
• Patient record management
• Secure APIs with Token-based authentication
• Comprehensive error handling and input validation

Technologies Used

• Programming Language: Python

• Framework: Django, Django Rest Framework (DRF)

• Database: PostgreSQL

• Authentication: Token Authentication

• Containerization: Docker

• Testing: Pytest

• Documentation: DRF's built-in API documentation and Swagger/OpenAPI

  

Project Structure

med-consultation-api/
├── api/
│   ├── migrations/              # Database migrations
│   ├── __init__.py              # Package initialization
│   ├── admin.py                 # Django admin configuration
│   ├── apps.py                  # App configuration
│   ├── managers.py              # Custom database managers
│   ├── models.py                # Database models
│   ├── serializers.py           # DRF serializers for request and response validation
│   ├── tests.py                 # Unit tests
│   ├── urls.py                  # URL routing for the API
│   └── views.py                 # API view logic
├── media/
│   ├── avatars/                 # User avatar storage
│   └── news/                    # News-related media files
├── root/
│   ├── __init__.py              # Project package initialization
│   ├── asgi.py                  # ASGI configuration
│   ├── settings.py              # Project settings
│   ├── urls.py                  # Root URL routing
│   └── wsgi.py                  # WSGI configuration
├── static/                      # Static files for the project
├── .env.local                   # Local environment variables
├── .env.prod                    # Production environment variables
├── docker-compose.yml           # Docker Compose configuration
├── Dockerfile                   # Docker configuration
├── entrypoint.prod.sh           # Entry point script for production
├── manage.py                    # Django management script
├── mig.sh                       # Migration script helper
├── nginx.conf                   # Nginx configuration
├── pytest.ini                   # Pytest configuration
├── README.md                    # Project documentation
├── requirements.txt             # Python dependencies
└── TODO                         # Pending development tasks

Installation

Prerequisites

• Python 3.9+
• PostgreSQL
• Docker (Optional for containerized deployment)

Steps

1. Clone the repository:

   git clone https://github.com/themusharraf/med-consultation-api.git
   cd med-consultation-api

2. Create a virtual environment and activate it:

   python3 -m venv venv
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

Environment Variables

Create a .env file in the project root by copying .env.example:

cp .env.example .env

Fill in the required environment variables:

DATABASE_URL=postgresql://user:password@localhost:5432/medconsultation
SECRET_KEY=your_django_secret_key
DEBUG=True
ALLOWED_HOSTS=*

Running the Application

Locally

python manage.py migrate
python manage.py runserver

API Documentation

Once the application is running, visit:

• DRF's Browsable API: http://localhost:8000/api/
• Swagger/OpenAPI: http://127.0.0.1:8000/api/docs#/ (if configured)

Best Practices Followed

1. Modular Architecture: Organized code into views, serializers, and models.
2. Database Migrations: Use of Django's migration system.
3. Environment Variables: Secure and configurable environment settings.
4. Secure Authentication: Token-based authentication for API security.
5. Data Validation: Use of DRF serializers for request and response validation.
6. Exception Handling: Comprehensive error handling for better API responses.
7. Testing: Unit and integration tests using Pytest.
8. Logging: Standard logging practices for monitoring and debugging.
9. Documentation: Auto-generated API documentation with Swagger and DRF.
10. Containerization: Dockerized application for consistency across environments.

Contributing

Contributions are welcome! Follow these steps:

1. Fork the repository.
2. Create a new branch.
3. Commit your changes.
4. Submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.