TASK MANAGER

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🖥️ Advanced Python Task Manager – Web Dashboard V2

Real-Time Monitoring • WebSockets • Login • Gauges • Processes • Logs • CLI + GUI + Web

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.

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📛 Badges

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📚 Table of Contents

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

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🧰 Introduction

This repository contains two versions of a Python task manager:

✅ 1. Basic Version

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

🚀 2. Advanced Task Manager Web Dashboard V2

A professional monitoring dashboard featuring:

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

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📦 Project Versions

Version	Description	Location
Basic Task Manager	Lightweight system resource monitor	basic_task_manager.py
Advanced Web Dashboard V2	Full Web Monitoring Suite	web-dashboard-v2/
Tkinter GUI	Desktop GUI	task_manager_tkinter.py
PyQt GUI	Modern GUI	task_manager_pyqt.py

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✨ Features

🔰 Basic Version

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

🚀 Advanced Version

• 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

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🧾 Basic Version

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}")

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🚀 Advanced Version

🔥 Web Dashboard V2 Features:

• 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

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🏗️ Architecture

┌─────────────────────────────────────────┐
│               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   │
└───────────────────┘

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🗂️ ER Diagram

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

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🔄 Flow Diagram

[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]

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📌 Use Cases

Use Case	Description
System Monitoring	Watch CPU/RAM/Disk live
Server Dashboard	Deploy on server and monitor
Education	Learn psutil, WebSockets, Flask
Diagnostics	Debug performance problems
GUI Development	Tkinter / PyQt practice

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🌍 Real-Life Examples

• 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

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⚖️ Pros & Cons

✅ Pros

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

❌ Cons

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

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⚙️ Installation

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

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▶️ How to Run

For the advanced dashboard:

python app.py

Open:

http://127.0.0.1:5000

For basic version:

python task_manager.py

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🤝 Contribution

Steps:

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

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⭐ Support

If you like the project:

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

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📜 License

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

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