A complete system monitoring suite built in Python using:

• Flask
• Flask-SocketIO
• psutil
• Chart.js
• WebSockets
• Tkinter / PyQt (optional GUIs)

Includes the simple version AND the full enterprise-grade version.

1. Introduction
2. Project Versions
3. Features
4. Basic Version Code Overview
5. Advanced Web Dashboard V2
6. Architecture
7. ER Diagram
8. Flow Diagram
9. Use Cases
10. Real-Life Applications
11. Pros & Cons
12. Installation
13. How to Run
14. Contribution Guide
15. Support
16. License

This repository contains two versions of a Python task manager:

A simple CLI script using psutil to fetch CPU, RAM, and Disk usage.

A professional monitoring dashboard featuring:

• WebSockets (real-time)
• Beautiful gauge UI
• Dark/Light theme
• Authentication
• Logs + Processes
• Network statistics
• GPU usage
• Modular architecture

• CPU usage
• RAM usage
• Disk usage
• Simple CLI output

• Real-time WebSocket updates (1/sec)
• Stylish gauge meters
• Top CPU processes table
• System logs panel
• Network monitoring
• GPU (NVIDIA) monitoring
• Login authentication
• Session-based theme toggle (dark/light)
• REST API (theme)
• Export logs (optional)
• Fully responsive HTML dashboard

import psutil def get_system_resources(): cpu_usage = psutil.cpu_percent(interval=1) mem = psutil.virtual_memory() mem_used = mem.used / (1024**3) mem_tot = mem.total / (1024**3) stats = { "CPU" : f"{cpu_usage}%", "Memory" : f"{mem_used:.2f} / {mem_tot:.2f} GB" } for partition in psutil.disk_partitions(): try: usage = psutil.disk_usage(partition.mountpoint) used_gb = usage.used / (1024**3) total_gb = usage.total / (1024**3) stats[f"Disk ({partition.mountpoint})"] = ( f"{used_gb:.2f} / {total_gb:.2f} GB" ) except PermissionError: continue return stats resource = get_system_resources() for name, usage in resource.items(): print(f"{name} : {usage}")

• Real-time WebSocket pushing
• Flask server
• Authentication system
• Gauges (CPU / RAM / Disk / GPU)
• Dark/Light themes
• Process manager
• Logging terminal
• Full web UI

Folder structure:

web-dashboard-v2/ │── app.py │── templates/ │── static/ │── requirements.txt 

┌─────────────────────────────────────────┐ │ User Browser │ │ ┌─────────────┐ WebSocket ┌────────┐│ │ │ dashboard.js│◀──────────────▶SocketIO││ │ └──────┬──────┘ └────────┘│ └────────┼──────────────────────────────────┘ │ Flask REST / Static ┌────────▼────────┐ │ Flask App │ │ Authentication │ │ Routing API │ │ Theme Control │ └────────┬─────────┘ │ calls ┌────────▼─────────┐ │ System Layer │ │ (psutil) │ │ CPU/RAM/Disk/GPU │ │ Process Manager │ └───────────────────┘ 

┌────────────┐ │ Users │ │────────────│ │ id │ │ username │ │ password │ │ theme │ └────────────┘ ▲ │ session │ ┌────────────┐ │ Sessions │ │────────────│ │ user_id │ │ timestamp │ └────────────┘ 

[User] │ ▼ [Login Page] ──incorrect──> [Error] │correct ▼ [Dashboard.html] │ ▼ WebSocket [SocketIO Server] │ polls every sec ▼ [get_system_data()] │ ▼ [psutil → CPU/RAM/Disk/Processes/GPU] │ ▼ send JSON [Browser UI Updates] 

• Monitoring a local PC
• Monitoring Docker containers
• Monitoring a Raspberry Pi home server
• Monitoring GPU workloads (AI training)
• Real-time dashboard in NOC rooms
• Teaching students about system internals

• Real-time updates
• Clean UI
• Uses standard Python libraries
• Cross-platform
• Web-based (access from anywhere)

• Requires Python installation
• Must be run manually
• WebSocket requires open port
• Not a replacement for full NOC tools (like Grafana)

git clone https://github.com/alok-kumar8765/task-manager.git cd web-dashboard-v2 pip install -r requirements.txt

python app.py

Open:

http://127.0.0.1:5000 

python task_manager.py

1. Fork repo
2. Create a new branch
3. Add changes
4. Submit Pull Request

git pull git add . git commit -m "Enhanced dashboard" git push

If you like the project:

🌟 Star the repository 🍴 Fork it 🐛 Report issues 💬 Request features

MIT License — free to use for personal and commercial projects.