KitchenIntel Backend (kitchenintel-be)

KitchenIntel Backend is a Django REST Framework application designed for restaurant analytics and menu intelligence. It provides APIs to manage menu categories, menu items, orders, dashboards, and data-driven insights for restaurant operations.

Features

• Menu and category management
• Order and order item management
• Dashboard and graph analytics (weekly/monthly)
• Data seeding for rapid development/testing
• Optimized API with custom pagination

Technology Stack

• Python 3
• Django 5
• Django REST Framework
• PostgreSQL (or SQLite for development)
• Huey (task queue)
• Pandas, Matplotlib, Seaborn (for analytics/graphs)

Getting Started

1. Clone the Repository

git clone <your-repo-url>
cd kitchenintel-be

2. Install Dependencies

It is recommended to use a virtual environment:

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

3. Environment Variables

Copy the sample environment file and configure your settings:

cp .env-sample .env
# Edit .env as needed (set DB, secret key, etc)

4. Apply Migrations

python manage.py migrate

Data Generation & Seeding

This project provides management commands to generate initial data for menu categories, menus, and orders. Run these commands in order for a complete data setup.

1. Seed Menu Categories

python manage.py seed_menu_categories

This will create parent and child menu categories as defined in menu_category/seed/menu_category_data.py.

2. Seed Menus

python manage.py seed_menu

This will create menu items and assign them to categories based on menu/seed/menu_data.py. Ensure categories are seeded first.

3. Seed Orders

python manage.py seed_order_data

This will generate realistic order and order item data for analytics and dashboard features. You can clear existing orders before seeding with:

python manage.py seed_order_data --clear

API Endpoints

• Dashboards: /api/dashboards-insights/
• Graphs: /api/graphs/
• Orders: /api/orders/
• Order Items: /api/order-items/

(See source code for more endpoints and details.)

Notes

• For development, SQLite is supported, but PostgreSQL is recommended for production.
• Data generation scripts are idempotent and safe to run multiple times.
• For analytics and dashboard features, ensure all seed steps are completed.

---

For any questions or issues, please open an issue or contact the maintainer.