🧪 ChemData Visualizer 📊

Professional Chemical Equipment Data Monitoring & Analysis Platform

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🎥 FOSSEE Internship Demo Video

🎬 Demo video created for FOSSEE Internship Screening Task

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Real-time monitoring and analysis of chemical equipment data across web and desktop platforms

Features • Architecture • Quick Start • Documentation • API Reference

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🚀 Live Demo

Component	URL	Status
Frontend (Web App)	https://chem-data-visualizer.vercel.app/
Backend (API)	https://chemdata-visualizer.onrender.com/

Note: The backend is hosted on Render's free tier and may take ~50 seconds to spin up if it has been inactive. Please be patient on the first request!

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📋 Overview

ChemData Visualizer is a comprehensive, enterprise-grade full-stack application designed for real-time monitoring, analysis, and visualization of chemical equipment data. The platform provides:

• 🌐 Modern Web Dashboard - React-based responsive web application with real-time analytics
• 🖥️ Native Desktop Application - PyQt5-powered desktop app for local analysis and monitoring
• 🔌 RESTful API Backend - Django REST Framework with robust data processing
• 📊 Advanced Analytics - Statistical analysis, trend visualization, and correlation studies
• 📑 Professional Reporting - Automated PDF report generation with charts and branding
• 🔐 Secure Authentication - JWT tokens and Google OAuth2 integration (Future Feature)
• 🐳 Docker Support - Containerized deployment for production environments

The platform enables chemical engineers and operators to monitor equipment performance, analyze trends, detect anomalies, and generate comprehensive reports with just a few clicks.

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📸 Application Preview

🖥️ Desktop Application

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🌐 Web Application Screenshots

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📄 PDF Report Generation

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🚀 Deployed Dashboard Previews

Vercel Deployment	Render Deployment

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🏗️ System Architecture

🎯 High-Level Overview

graph TB
    subgraph "Client Layer"
        WEB[🌐 Web Application<br/>React + Vite + TailwindCSS]
        DESKTOP[🖥️ Desktop Application<br/>PyQt5 + Matplotlib]
    end

    subgraph "API Gateway"
        NGINX[⚡ Nginx / Load Balancer]
    end

    subgraph "Application Layer"
        DJANGO[🔧 Django 5.0<br/>REST Framework]
        AUTH[🔐 Authentication Service<br/>JWT + OAuth2]
        ANALYTICS[📊 Analytics Engine<br/>Pandas + NumPy]
        PDF[📄 PDF Generator<br/>ReportLab]
    end

    subgraph "Data Layer"
        DB[(💾 Database<br/>SQLite/PostgreSQL)]
        MEDIA[📁 Media Storage<br/>CSV Files + PDFs]
        CACHE[⚡ Cache Layer<br/>Optional Redis]
    end

    WEB -->|HTTPS/JSON| NGINX
    DESKTOP -->|HTTPS/JSON| NGINX
    NGINX -->|Proxy| DJANGO

    DJANGO --> AUTH
    DJANGO --> ANALYTICS
    DJANGO --> PDF

    DJANGO -->|ORM Queries| DB
    DJANGO -->|File I/O| MEDIA
    ANALYTICS -->|Read/Write| DB
    PDF -->|Generate| MEDIA

    style WEB fill:#2196F3,stroke:#1565C0,stroke-width:3px,color:#fff
    style DESKTOP fill:#4CAF50,stroke:#2E7D32,stroke-width:3px,color:#fff
    style DJANGO fill:#FF9800,stroke:#E65100,stroke-width:3px,color:#fff
    style AUTH fill:#9C27B0,stroke:#6A1B9A,stroke-width:3px,color:#fff
    style DB fill:#607D8B,stroke:#37474F,stroke-width:3px,color:#fff
    style ANALYTICS fill:#F44336,stroke:#C62828,stroke-width:3px,color:#fff

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🔄 Data Processing Pipeline

sequenceDiagram
    participant User
    participant Client as Web/Desktop Client
    participant API as Django REST API
    participant Parser as Pandas Parser
    participant DB as Database
    participant PDF as ReportLab Engine

    User->>Client: Upload CSV File
    Client->>API: POST /api/upload/
    API->>MEDIA: Save CSV to Media Storage
    API->>Parser: Parse CSV with Pandas
    Parser->>Parser: Validate & Transform Data
    Parser->>DB: Bulk Create EquipmentRecords
    DB-->>API: Insert Success
    API-->>Client: 201 Created (Dataset ID)
    Client-->>User: Upload Confirmation

    User->>Client: Request Analytics
    Client->>API: GET /api/datasets/{id}/stats/
    API->>DB: Aggregate Queries<br/>(AVG, COUNT, GROUP BY)
    DB-->>API: Statistical Results
    API-->>Client: JSON Response
    Client->>Client: Render Charts & KPIs
    Client-->>User: Display Dashboard

    User->>Client: Request PDF Report
    Client->>API: GET /api/datasets/{id}/pdf/
    API->>DB: Fetch Dataset Records
    DB-->>API: Raw Data
    API->>PDF: Generate Report<br/>(Charts, Tables, Branding)
    PDF->>MEDIA: Save PDF File
    PDF-->>API: File Path
    API-->>Client: Download PDF
    Client-->>User: Save Report

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🐳 Docker Deployment Architecture

graph TB
    subgraph "Docker Network: chemdata-network"
        subgraph "Frontend Container"
            REACT[React App<br/>Port 5173]
        end

        subgraph "Backend Container"
            GUNICORN[Gunicorn WSGI<br/>Port 8000]
            DJANGO_APP[Django Application]
        end

        subgraph "Data Volumes"
            DB_VOL[Database Volume<br/>db.sqlite3]
            MEDIA_VOL[Media Volume<br/>uploads/]
        end
    end

    EXTERNAL[External Access] -->|Port 5173| REACT
    EXTERNAL -->|Port 8000| GUNICORN

    REACT -->|API Calls| GUNICORN
    GUNICORN --> DJANGO_APP
    DJANGO_APP --> DB_VOL
    DJANGO_APP --> MEDIA_VOL

    style REACT fill:#61DAFB,stroke:#1565C0,stroke-width:2px,color:#000
    style GUNICORN fill:#FF9800,stroke:#E65100,stroke-width:2px,color:#fff
    style DB_VOL fill:#607D8B,stroke:#37474F,stroke-width:2px,color:#fff

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✨ Key Features

🔐 Authentication & Security

Feature	Web App	Desktop App
JWT Token Authentication	✅	✅
Google OAuth2	✅ (Future)	❌
Session Management	✅	✅
Secure Password Hashing	✅	✅

📊 Data Visualization

Web Application Features

• Interactive Charts - Chart.js powered visualizations
  • 📊 Bar Charts - Average metrics by equipment type
  • 📈 Line Charts - Trend analysis over time
  • 🍩 Donut Charts - Equipment distribution
  • 📉 Scatter Plots - Correlation analysis
• Real-time KPI Cards - Total records, averages, equipment counts
• Responsive Grid Layout - Mobile-friendly design
• Skeleton Loading States - Smooth UX during data fetch
• Dark/Light Theme - User preference support

Desktop Application Features

• Native Matplotlib Charts - High-quality static and interactive plots
• Metric Switchers - Dynamic dropdown selectors for different parameters
• Correlation Explorer - Customizable X/Y axis scatter plots
• Export Capabilities - Save charts as PNG/SVG
• Tabbed Interface - Analytics Dashboard + Data Logs
• Branded Theme - Consistent teal (#0d9488) and slate colors

📂 Dataset Management

Feature	Description
CSV Upload	Drag-and-drop file upload with validation
Auto-Parsing	Pandas-powered CSV parsing and validation
User Isolation	Personal vs. Global dataset history
Bulk Operations	Efficient batch data insertion
File Storage	Secure media file management
History Tracking	Upload timestamps and metadata

📑 Professional Reporting

• PDF Generation - Professional reports with ReportLab
• Custom Branding - Company logo and styling
• Data Tables - Formatted equipment records
• Statistical Charts - Embedded visualizations
• Header Analysis - CSV structure documentation
• One-Click Export - Instant report download

🎨 User Experience

• Unified Design System - Consistent teal and slate theme across platforms
• Responsive Layouts - Works on desktop, tablet, and mobile
• Loading Indicators - Smooth transitions and feedback
• Error Handling - User-friendly error messages
• Empty States - Helpful guidance when no data present
• Interactive Filters - Dynamic data exploration

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🛠️ Technology Stack

Backend Technologies

Technology	Version	Purpose
Python	3.10+	Programming language
Django	5.0	Web framework
Django REST Framework	3.14+	RESTful API toolkit
Pandas	Latest	Data manipulation and analysis
ReportLab	Latest	PDF generation
Matplotlib	3.5+	Chart generation (backend)
django-cors-headers	Latest	CORS support
django-allauth	Latest	Social authentication (Future)
dj-rest-auth	Latest	REST authentication
PyJWT	Latest	JSON Web Tokens
python-dotenv	Latest	Environment variable management
Gunicorn	Latest	WSGI HTTP Server (production)

Frontend Technologies

Web Application

Technology	Version	Purpose
React	19.2.0	UI library
Vite	7.2.4	Build tool and dev server
TailwindCSS	3.4.17	Utility-first CSS framework
Chart.js	4.5.1	Data visualization
react-chartjs-2	5.3.1	React wrapper for Chart.js
Axios	1.13.3	HTTP client
@react-oauth/google	0.13.4	Google OAuth integration (Future)

Desktop Application

Technology	Version	Purpose
PyQt5	5.x	Desktop GUI framework
Matplotlib	3.5+	Plotting library
Requests	Latest	HTTP client
Pandas	Latest	Data processing

DevOps & Tools

Tool	Purpose
Docker	Containerization
docker-compose	Multi-container orchestration
Git	Version control
ESLint	JavaScript linting

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📁 Project Structure

ChemData-Visualizer/
├── 📂 backend/                          # Django REST API Server
│   ├── 📂 api/                          # API Application
│   │   ├── 📂 migrations/               # Database migrations
│   │   ├── 📜 __init__.py
│   │   ├── 📜 admin.py                  # Django admin config
│   │   ├── 📜 models.py                 # Data models (Dataset, EquipmentRecord)
│   │   ├── 📜 serializers.py            # DRF serializers
│   │   ├── 📜 urls.py                   # API URL routing
│   │   └── 📜 views.py                  # API views and business logic
│   ├── 📂 core/                         # Project Settings
│   │   ├── 📜 __init__.py
│   │   ├── 📜 asgi.py                   # ASGI config
│   │   ├── 📜 settings.py               # Django settings
│   │   ├── 📜 urls.py                   # Root URL config
│   │   └── 📜 wsgi.py                   # WSGI config
│   ├── 📂 media/                        # User uploads (CSV, PDF)
│   ├── 📂 venv/                         # Virtual environment
│   ├── 📜 .env                          # Environment variables
│   ├── 📜 .env.example                  # Environment template
│   ├── 📜 db.sqlite3                    # SQLite database
│   ├── 📜 Dockerfile                    # Docker image definition
│   ├── 📜 manage.py                     # Django CLI
│   ├── 📜 requirements.txt              # Python dependencies
│   ├── 📜 create_user.py                # Admin user creation script
│   ├── 📜 reset_pass.py                 # Password reset utility
│   └── 📜 README.md                     # Backend documentation
│
├── 📂 web-frontend/                     # React Web Application
│   ├── 📂 src/                          # Source code
│   │   ├── 📂 assets/                   # Images, icons
│   │   ├── 📂 components/               # React components
│   │   ├── 📂 pages/                    # Page components
│   │   ├── 📂 services/                 # API service layer
│   │   ├── 📂 utils/                    # Utility functions
│   │   ├── 📜 App.jsx                   # Root component
│   │   ├── 📜 main.jsx                  # Entry point
│   │   └── 📜 index.css                 # Global styles
│   ├── 📂 public/                       # Static assets
│   ├── 📜 .dockerignore                 # Docker ignore rules
│   ├── 📜 Dockerfile                    # Docker image definition
│   ├── 📜 package.json                  # npm dependencies
│   ├── 📜 vite.config.js                # Vite configuration
│   ├── 📜 tailwind.config.js            # Tailwind configuration
│   ├── 📜 postcss.config.js             # PostCSS configuration
│   └── 📜 eslint.config.mjs             # ESLint rules
│
├── 📂 desktop-frontend/                 # PyQt5 Desktop Application
│   ├── 📂 ui/                           # UI modules
│   │   ├── 📜 __init__.py
│   │   ├── 📜 auth.py                   # Login/Signup windows
│   │   ├── 📜 dashboard.py              # Main dashboard UI
│   │   └── 📜 styles.py                 # QSS stylesheets
│   ├── 📂 assets/                       # Desktop assets
│   ├── 📜 config.py                     # Configuration
│   ├── 📜 main.py                       # Application entry point
│   ├── 📜 requirements.txt              # Python dependencies
│   └── 📜 README.md                     # Desktop app documentation
│
├── 📂 docs/                             # Additional documentation
├── 📜 docker-compose.yml                # Docker Compose config
├── 📜 .gitignore                        # Git ignore rules
├── 📜 .env                              # Root environment variables
├── 📜 .env.example                      # Environment template
├── 📜 sample_equipment_data.csv         # Sample dataset
├── 📜 large_equipment_data.csv          # Large test dataset
├── 📜 DEPLOYMENT_GUIDE.md               # Deployment instructions
└── 📜 README.md                         # This file

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🚀 Quick Start

Prerequisites

Ensure you have the following installed:

Tool	Version	Download
Python	3.10 or higher	python.org
Node.js	18.x or higher	nodejs.org
npm	9.x or higher	Included with Node.js
Git	Latest	git-scm.com
Docker Desktop	Latest (Optional)	docker.com

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Option 1: 🐳 Quick Start with Docker (Recommended)

The fastest way to get the entire stack running.

1. Clone the Repository

   git clone <repository-url>
   cd ChemData-Visualizer

2. Start All Services

   docker-compose up --build

3. Access the Applications

   • Web App: http://localhost:5173
   • API: http://localhost:8000
   • API Admin: http://localhost:8000/admin

4. Create Superuser (Optional - for Django Admin)

   docker-compose exec backend python manage.py createsuperuser

Tip

To stop all services: docker-compose down

To rebuild after changes: docker-compose up --build

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Option 2: 🔧 Manual Development Setup

For individual component development and debugging.

Terminal 1: Backend Server

# Navigate to backend
cd backend

# Create virtual environment
python -m venv venv

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

# Install dependencies
pip install -r requirements.txt

# Setup environment variables
cp .env.example .env
# Edit .env with your settings

# Run migrations
python manage.py migrate

# Create superuser (optional)
python manage.py createsuperuser

# Start development server
python manage.py runserver

Backend will run on: http://127.0.0.1:8000

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Terminal 2: Web Frontend

# Navigate to web frontend
cd web-frontend

# Install dependencies
npm install

# Start development server
npm run dev

Web app will run on: http://localhost:5173

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Terminal 3: Desktop Application

# Navigate to desktop frontend
cd desktop-frontend

# Install dependencies
pip install -r requirements.txt

# Run application
python main.py

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⚙️ Configuration

Environment Variables

Backend (.env)

Create a .env file in the backend/ directory:

Variable	Description	Example	Required
SECRET_KEY	Django secret key	your-secret-key-here	✅
DEBUG	Debug mode	True (dev), False (prod)	✅
ALLOWED_HOSTS	Allowed host domains	localhost,127.0.0.1	✅
GOOGLE_CLIENT_ID	Google OAuth client ID	your-client-id (Optional - Commented out)	❌
GOOGLE_CLIENT_SECRET	Google OAuth secret	your-client-secret (Optional - Commented out)	❌
DATABASE_URL	PostgreSQL connection (optional)	postgresql://user:pass@localhost/dbname	❌

Example .env file:

SECRET_KEY=django-insecure-your-secret-key-here-change-in-production
DEBUG=True
ALLOWED_HOSTS=localhost,127.0.0.1
# GOOGLE_CLIENT_ID=your-google-client-id.apps.googleusercontent.com
# GOOGLE_CLIENT_SECRET=your-google-client-secret

Caution

Never commit your .env file to version control. Always use .env.example as a template.

Desktop Application (config.py)

Modify desktop-frontend/config.py to point to your API:

API_URL = "http://127.0.0.1:8000/api/"

For production, update to your deployed API URL:

API_URL = "https://api.yourcompany.com/api/"

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📡 API Endpoints

Base URL

http://127.0.0.1:8000/api/

Authentication Endpoints

Method	Endpoint	Description	Authentication
POST	/api/auth/registration/	Register new user account	Public
POST	/api/api-token-auth/	Login and get JWT token	Public
POST	/accounts/google/login/	Google OAuth2 authentication (Future)	Public
POST	/api/auth/logout/	Logout and invalidate token	Required

Registration Example:

POST /api/auth/registration/
{
  "username": "john_doe",
  "email": "john@example.com",
  "password": "securepassword123"
}

Login Example:

POST /api/api-token-auth/
{
  "username": "john_doe",
  "password": "securepassword123"
}

Response:
{
  "token": "9944b09199c62bcf9418ad846dd0e4bbdfc6ee4b"
}

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Dataset Management Endpoints

Method	Endpoint	Description	Authentication
GET	/api/datasets/	List user's datasets	Required
POST	/api/upload/	Upload new CSV dataset	Required
GET	/api/datasets/{id}/	Get dataset details	Required
DELETE	/api/datasets/{id}/	Delete dataset	Required
GET	/api/datasets/global/	List all datasets (admin)	Required

Upload Dataset Example:

curl -X POST http://127.0.0.1:8000/api/upload/ \
  -H "Authorization: Token your-auth-token" \
  -F "file=@sample_equipment_data.csv" \
  -F "name=Equipment_Test_Jan2024"

Response:

{
  "id": 1,
  "name": "Equipment_Test_Jan2024",
  "file": "/media/uploads/Equipment_Test_Jan2024.csv",
  "uploaded_at": "2024-01-20T10:30:00Z",
  "record_count": 150
}

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Analytics & Statistics Endpoints

Method	Endpoint	Description	Authentication
GET	/api/datasets/{id}/stats/	Get statistical analysis	Required
GET	/api/datasets/{id}/data/	Get raw equipment records	Required
GET	/api/datasets/{id}/pdf/	Download PDF report	Required

Statistics Example:

GET /api/datasets/1/stats/

Response:
{
  "total_records": 150,
  "average_flowrate": 45.6,
  "average_pressure": 120.4,
  "average_temperature": 75.2,
  "equipment_distribution": {
    "Pump": 50,
    "Valve": 30,
    "Tank": 40,
    "Reactor": 30
  },
  "equipment_stats": [
    {
      "equipment_type": "Pump",
      "avg_flowrate": 52.3,
      "avg_pressure": 135.7,
      "avg_temperature": 72.1
    }
  ]
}

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🗄️ Database Schema

Entity Relationship Diagram

erDiagram
    User ||--o{ Dataset : owns
    Dataset ||--o{ EquipmentRecord : contains

    User {
        int id PK
        string username UK
        string email UK
        string password_hash
        datetime date_joined
        boolean is_active
        boolean is_staff
    }

    Dataset {
        int id PK
        int user_id FK
        string name
        string file_path
        datetime uploaded_at
        int record_count
    }

    EquipmentRecord {
        int id PK
        int dataset_id FK
        string equipment_name
        string equipment_type
        float flowrate
        float pressure
        float temperature
        datetime timestamp
    }

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Model Descriptions

User Model

Extended Django authentication model.

Field	Type	Description
id	Integer	Primary key
username	String(150)	Unique username
email	Email	User email address
password	String	Hashed password
is_active	Boolean	Account status
date_joined	DateTime	Registration timestamp

Dataset Model

Represents uploaded CSV files.

Field	Type	Description
id	Integer	Primary key
user	ForeignKey	Owner (User model)
name	String(255)	Dataset name
file	FileField	Path to CSV file
uploaded_at	DateTime	Upload timestamp

EquipmentRecord Model

Individual equipment measurements.

Field	Type	Description
id	Integer	Primary key
dataset	ForeignKey	Parent dataset
equipment_name	String(100)	Equipment identifier
equipment_type	String(50)	Type (Pump/Valve/Tank/Reactor)
flowrate	Float	Flow rate measurement
pressure	Float	Pressure measurement
temperature	Float	Temperature measurement
timestamp	DateTime	Measurement time

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🎨 UI/UX Design

Color Palette

Color	Hex	Usage
Primary Teal	#0d9488	Buttons, accents, highlights
Slate 900	#0f172a	Headers, dark backgrounds
Slate 800	#1e293b	Secondary backgrounds
Slate 700	#334155	Borders, dividers
White	#ffffff	Text on dark, card backgrounds
Success Green	#10b981	Success messages, positive metrics
Warning Amber	#f59e0b	Warnings, alerts
Error Red	#ef4444	Errors, critical alerts

Design System

• Typography: System fonts (San Francisco, Segoe UI, Roboto)
• Spacing: 4px grid system (4, 8, 12, 16, 24, 32, 48, 64px)
• Border Radius: Consistent 8px for cards, 4px for buttons
• Shadows: Subtle elevation for depth (box-shadow)
• Transitions: 150-300ms ease-in-out for smooth interactions

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📊 Sample Data

The project includes sample CSV files for testing:

sample_equipment_data.csv

Small dataset with basic equipment records.

large_equipment_data.csv

Larger dataset (1000+ records) for performance testing.

CSV Format

Equipment Name,Equipment Type,Flowrate (m³/h),Pressure (bar),Temperature (°C)
Pump_001,Pump,45.6,120.4,75.2
Valve_002,Valve,0.0,85.3,68.9
Tank_003,Tank,0.0,10.2,25.4

---

🔧 Development

Backend Development

cd backend

# Run tests
python manage.py test api

# Create migrations
python manage.py makemigrations

# Apply migrations
python manage.py migrate

# Create superuser
python manage.py createsuperuser

# Open Django shell
python manage.py shell

# Collect static files (production)
python manage.py collectstatic

Frontend Development

cd web-frontend

# Install dependencies
npm install

# Start dev server
npm run dev

# Build for production
npm run build

# Preview production build
npm run preview

# Run linter
npm run lint

Desktop Development

cd desktop-frontend

# Install dependencies
pip install -r requirements.txt

# Run application
python main.py

# Build executable (PyInstaller)
pip install pyinstaller
pyinstaller --noconsole --onefile main.py

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🐳 Docker Deployment

Build and Run

# Build and start all services
docker-compose up --build

# Run in detached mode
docker-compose up -d

# View logs
docker-compose logs -f

# Stop services
docker-compose down

# Remove volumes (caution: deletes data)
docker-compose down -v

Production Configuration

Update docker-compose.yml for production:

services:
  backend:
    environment:
      - DEBUG=False
      - SECRET_KEY=${SECRET_KEY}
      - ALLOWED_HOSTS=yourdomain.com

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📝 API Documentation

For detailed API documentation, see:

• Backend README - Complete API reference
• Postman Collection - Import into Postman

---

🧪 Testing

Backend Tests

cd backend
python manage.py test api -v 2

Frontend Tests (if configured)

cd web-frontend
npm test

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🚢 Deployment

See DEPLOYMENT_GUIDE.md for detailed deployment instructions including:

• Production server setup
• PostgreSQL database configuration
• Nginx reverse proxy
• SSL/TLS certificates
• Environment variable management
• Continuous deployment

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🐛 Troubleshooting

Common Issues

Issue	Solution
Port 8000 already in use	Change backend port or kill existing process
CORS errors	Verify CORS_ALLOWED_ORIGINS in backend settings
Docker build fails	Clear Docker cache: docker system prune
Upload fails	Check MEDIA_ROOT permissions in backend
Desktop app won't connect	Verify API_URL in config.py points to running backend
Database locked	Close other connections to SQLite

Debug Mode

Enable verbose logging:

Backend:

# settings.py
LOGGING = {
    'version': 1,
    'disable_existing_loggers': False,
    'handlers': {
        'console': {'class': 'logging.StreamHandler'},
    },
    'root': {'handlers': ['console'], 'level': 'DEBUG'},
}

Frontend:

// Enable React DevTools
window.__REACT_DEVTOOLS_GLOBAL_HOOK__ =
  window.__REACT_DEVTOOLS_GLOBAL_HOOK__ || {};

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🤝 Contributing

Contributions are welcome! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Code Style

• Python: Follow PEP 8, use Black formatter
• JavaScript: Follow Airbnb style guide, use ESLint
• Commits: Use conventional commits format

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📄 License

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

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👨‍💻 Author

Mausam Kar

• Portfolio: mausam04.vercel.app
• GitHub: @Mausam5055

Built with ❤️ using Django, React, and PyQt5

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🙏 Acknowledgments

• Django and DRF communities
• React and Vite teams
• PyQt5 and Riverbank Computing
• Chart.js contributors
• All open-source library maintainers

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⬆ Back to Top

Made with passion for chemical engineering and data science