Chemical Equipment Parameter Visualizer

A hybrid Web + Desktop application for uploading, analyzing, and visualizing chemical equipment data from CSV files.

🚀 Features

• CSV Upload: Upload equipment data via Web or Desktop interface
• Data Analysis: Automatic calculation of averages and distributions using Pandas
• Visualizations: Interactive charts with Chart.js (Web) and Matplotlib (Desktop)
• PDF Reports: Generate downloadable PDF reports with ReportLab
• History Management: Stores last 5 uploaded datasets
• Authentication: Token-based user authentication
• Responsive UI: Modern dark-themed interfaces on both platforms

📁 Project Structure

chemical-equipment-visualizer/
├── backend/                    # Django REST API
│   ├── equipment_visualizer/   # Django project settings
│   ├── equipment_api/          # Main API app
│   ├── manage.py
│   └── requirements.txt
├── frontend-web/               # React.js application
│   ├── src/
│   │   ├── components/         # React components
│   │   ├── App.jsx
│   │   ├── api.js
│   │   └── index.css
│   ├── package.json
│   └── vite.config.js
├── frontend-desktop/           # PyQt5 application
│   ├── main.py                 # Desktop app entry point
│   ├── api_client.py           # API client
│   └── requirements.txt
├── sample_equipment_data.csv   # Sample test data
└── README.md

🛠️ Tech Stack

Layer	Technology	Purpose
Backend	Django + DRF	REST API
Web Frontend	React + Chart.js	Web visualization
Desktop Frontend	PyQt5 + Matplotlib	Desktop visualization
Data Processing	Pandas	CSV parsing & analytics
PDF Generation	ReportLab	PDF reports
Database	SQLite	Data storage

📋 Prerequisites

• Python 3.9+
• Node.js 18+
• pip (Python package manager)
• npm (Node package manager)

⚙️ Setup Instructions

1. Clone the Repository

git clone https://github.com/yourusername/chemical-equipment-visualizer.git
cd chemical-equipment-visualizer

2. Backend Setup (Django)

# Navigate to backend directory
cd backend

# Create virtual environment
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# Linux/Mac:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run migrations
python manage.py migrate

# Create superuser (optional)
python manage.py createsuperuser

# Start server
python manage.py runserver

The API will be available at http://localhost:8000/api/

3. Web Frontend Setup (React)

# Open new terminal, navigate to frontend-web
cd frontend-web

# Install dependencies
npm install

# Start development server
npm run dev

The web app will be available at http://localhost:5173/

4. Desktop Frontend Setup (PyQt5)

# Open new terminal, navigate to frontend-desktop
cd frontend-desktop

# Create virtual environment (optional but recommended)
python -m venv venv
venv\Scripts\activate  # Windows

# Install dependencies
pip install -r requirements.txt

# Run the desktop application
python main.py

📊 Sample Data

A sample CSV file (sample_equipment_data.csv) is provided with the following format:

Equipment Name	Type	Flowrate	Pressure	Temperature
Reactor R-101	Reactor	150.5	25.0	180.0
Heat Exchanger HX-201	Heat Exchanger	320.0	15.5	95.0
...	...	...	...	...

🔌 API Endpoints

Endpoint	Method	Description
/api/upload/	POST	Upload CSV file
/api/datasets/	GET	List last 5 datasets
/api/datasets/<id>/	GET	Dataset details
/api/datasets/<id>/summary/	GET	Statistics summary
/api/datasets/<id>/report/	GET	Download PDF report
/api/auth/register/	POST	User registration
/api/auth/login/	POST	User login
/api/auth/logout/	POST	User logout

🖼️ Screenshots

Web Application

• Dashboard with CSV upload
• Interactive data tables
• Chart.js visualizations (Bar, Pie, Line charts)
• Upload history view

Desktop Application

• PyQt5 dark-themed interface
• Matplotlib charts
• PDF report generation
• Dataset history management

🧪 Testing

Backend Tests

cd backend
python manage.py test

Manual Testing

1. Start the Django backend
2. Launch either web or desktop frontend
3. Upload the sample_equipment_data.csv file
4. Verify data table and charts display correctly
5. Test PDF report download

📝 Usage Guide

1. Start the Backend: Run Django server on port 8000
2. Launch Frontend: Open web app or desktop app
3. Upload CSV: Drag-drop or browse for CSV file
4. View Analysis: See statistics and visualizations
5. Download Report: Generate PDF summary
6. View History: Access last 5 uploaded datasets

🔐 Authentication

• Register a new account via web or desktop
• Login to track your uploads
• Guest mode available (uploads not linked to user)

📄 License

MIT License - feel free to use and modify.

👤 Author

Created as an intern screening task for demonstrating full-stack development skills.

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Happy Visualizing! 🔬📊