Orderly: A Campus Dining Queue Solution

The Problem

On our university campus, the lunch rush creates a significant problem. Long queues form instantly in front of all restaurants, leading to campus-wide congestion, frustratingly long wait times for students, and a noisy, chaotic environment that makes it difficult for everyone to move around.

The Solution

Orderly is a full-stack web application designed to eliminate these queues and streamline the campus dining experience. It provides a digital platform where students can browse restaurant menus, place orders remotely, and receive updates on their order status. Restaurants get a dedicated dashboard to manage incoming orders efficiently, reducing the need for physical queues and improving overall service speed and campus flow.

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Core Features

This project was built with a two-sided marketplace structure, providing a tailored experience for both Customers and Restaurants.

Customer Features:

• Secure Authentication: Customers can sign up and sign in to their own accounts.
• Restaurant Discovery: Browse a list of all available campus restaurants.
• "Like" Favorite Restaurants: Customers can "like" restaurants to save them. This feature uses an optimistic UI update for a seamless, instant user experience.
• Order Management: Place orders directly from a restaurant's menu.
• Order History: View a detailed history of all past orders.
• Real-Time Order Tracking: See the live status of current orders (Pending, Preparing, Ready, etc.).

Restaurant Features:

• Secure Authentication: Restaurants have their own separate and secure accounts.
• Powerful Dashboard: A dedicated dashboard to view and manage all active orders in real-time. Staff can update an order's status with a single click.
• Settings Management: A separate, organized page where restaurant managers can:
  • Update the Menu: Add, edit, or delete menu items using an intuitive pop-up modal.
  • Set Wait Times: Update the estimated average wait time that is displayed to customers.
• Order History: View a complete history of all fulfilled and cancelled orders.

General Features:

• Modern, Responsive Frontend: A fast and user-friendly interface built with Next.js, featuring both light and dark mode support for readability.
• Robust Backend API: A secure and efficient API built with Python (FastAPI), featuring Pydantic data validation and a logical, well-documented structure.

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Tech Stack

• Backend: Python, FastAPI, SQLModel (as the ORM), Uvicorn
• Frontend: Next.js, React, TypeScript, SWR (for data fetching and state management), Tailwind CSS
• Database: SQLite (for simplicity and ease of setup)

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Getting Started

To get this project running locally, you'll need to run both the backend server and the frontend development server.

Prerequisites:

• Node.js and npm (or yarn)
• Python 3.8+ and pip

1. Backend Setup (FastAPI)

# 1. Navigate to the server directory
cd server

# 2. (Recommended) Create and activate a virtual environment
python -m venv venv
# On Windows:
venv\\Scripts\\activate
# On macOS/Linux:
source venv/bin/activate

# 3. Create a local environment file by copying the example
# On Windows:
copy .env.example .env
# On macOS/Linux:
cp .env.example .env

# 4. Install the required Python dependencies
pip install -r requirements.txt

# 5. Start the backend server
fastapi dev main.py

The backend API will now be running at http://localhost:8000.

2. Frontend Setup (Next.js)

# 1. In a new terminal, navigate to the client directory
cd client

# 2. Create a local environment file by copying the example
# On Windows:
copy .env.example .env.local
# On macOS/Linux:
cp .env.example .env.local

# 3. Install the required Node.js dependencies
npm install

# 4. Run the frontend development server
npm run dev

The frontend application will now be available at http://localhost:3000. Open this URL in your browser.

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Live Demo & Credentials

You can access the live version of the application here: food-ordering-app-mocha-nine.vercel.app

Use the following credentials to explore the app:

Customer Account

• Email: customer@example.com
• Password: Password-123

Restaurant Account

• Email: restaurant@example.com
• Password: Password-123

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Future Work

Given more time, the following features would be the next steps for this project:

• Implement a Test Suite: The highest priority for future work would be to develop a comprehensive test suite. This would involve using PyTest for the backend API endpoints and business logic, and Jest / React Testing Library for the frontend components to ensure code quality and long-term stability.
• Real-Time Notifications: Integrate WebSockets to provide instant notifications to users (e.g., a customer gets a browser notification when their order is ready for pickup).
• Search and Filtering: Add a search bar to allow customers to quickly find specific restaurants or menu items, and filter restaurants by criteria like wait time or cuisine type.
• Data Analytics Dashboard: Enhance the restaurant dashboard with analytics features, such as visualizing sales data with charts (e.g., daily revenue, popular items) and providing actionable insights for the restaurant owner.