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🖥️ System Performance Analyzer

Python 3.11+ Live App

A Streamlit web application that monitors system performance in real time (CPU, RAM, swap, battery, network and per-process usage), detects anomalies with a lightweight ML pipeline and generates downloadable PDF reports.

Built as a fully modular Python project with JWT-based session persistence, bcrypt-hashed credentials, role-based admin access and SQLite-backed storage designed to be readable, low-latency and easy to deploy.

⚠️ Live Demo - For reference only. It Monitors the cloud container, not your machine. Shows how the app works on your own machine when run locally.

✨ Features

  • 🔐 Authentication - username/password login with bcrypt + JWT session cookies (survives reload)
  • 🔍 Live monitoring - sample CPU, RAM, swap, battery, network throughput and the top-N processes on a fixed interval, persisted to SQLite
  • 📊 Interactive analytics - Plotly charts for system, process and network metrics, browsable per day
  • 🧠 Anomaly detection - Isolation Forest on CPU/RAM, z-score ranking on processes, threshold alerts on network spikes
  • 🏥 Health score - single 0-100 grade (A-F) summarising the day's behaviour
  • 📥 PDF reports - one-click download with all charts, generated on demand via ReportLab
  • 👥 Admin panel - toggle self-signup, cap monitoring duration, manage users, download a DB backup

🧱 Project structure

System-Performance-Analyzer/
├── main.py
├── requirements.txt
├── pyproject.toml
├── .streamlit/config.toml
├── .python-version
├── .gitignore
├── LICENSE
├── README.md
├── .env
└── src/
    ├── analysis.py
    ├── config.py
    ├── database.py
    ├── logger.py
    ├── ml_engine.py
    ├── report_generator.py
    ├── user_auth.py
    ├── user_session.py
    ├── services/
    │   ├── base_service.py
    │   ├── network_monitor.py
    │   ├── process_monitor.py
    │   ├── service_orchestrator.py
    │   └── system_metrics.py
    └── pages/
        ├── admin.py
        ├── auth_page.py
        ├── dashboard.py
        ├── monitor.py
        ├── report.py
        └── setting.py

🚀 Quick start (local)

# 1. Clone the repository
git clone https://github.com/abhishek-tiwari-nitrr/System-Performance-Analyzer.git
cd System-Performance-Analyzer

# 2. Install dependencies
uv sync

# 3. Configure secrets - create a .env file in the project root

# 4. Run
uv run streamlit run main.py

Open .env and fill in your values:

ADMIN_USER=admin-username
ADMIN_PASSWORD=admin-password
SPA_SECRET_KEY=long-random-secret-key

📺 Demo

System Performance Analyzer Demo

Tech Stack

Layer Libraries
UI Streamlit, Plotly, Custom CSS
Backend Python 3.10+
Storage SQLite
Auth Bcrypt (passwords), PyJWT (stateless sessions)
ML scikit learn
Reports Matplotlib (chart rendering), ReportLab (PDF)
Telemetry Psutil
Package Management Tool UV