Pi Full Monitor Documentation

Overview

Pi Full Monitor is a Python-based CLI tool designed for monitoring the performance and health of a Raspberry Pi device in real-time. It provides insights into CPU usage, memory, disk, network activity, and running processes. The tool is built with a visually appealing dashboard using the rich library.

• Simple Installation: Comes with a setup script to install all dependencies.
• Cross-Platform: Designed for Raspberry Pi but can work on any Linux-based system.

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Features

• Real-time Monitoring: Automatically refreshes system statistics every 2 seconds.
• Comprehensive Metrics:
  • CPU Usage and Temperature
  • Memory Usage
  • Disk Usage
  • Network Activity (Sent and Received Data)
  • Top Processes by CPU and Memory Usage

ROADMAP

The tool also will monitor connected SDR devices:

• RTL-SDR: Checks if the RTL-SDR is connected using rtl_test.
• HackRF: Monitors HackRF devices using hackrf_info.
• Airspy: Detects Airspy devices with airspy_info.
• bladeRF: Verifies bladeRF connectivity using bladeRF-cli.

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Installation

Prerequisites

Ensure the following are installed on your Raspberry Pi:

• Python 3.6 or newer
• pip package manager
• venv module

Steps

1. Clone the repository:

   git clone https://github.com/exfil0/pi_full_monitor.git

2. Navigate to the project directory:

   cd pi_full_monitor

3. Make the installation script executable:

   chmod +x install.sh

4. Run the installation script:

   ./install.sh

   The script will:
   • Create a Python virtual environment.
   • Install all required dependencies.
   • Set up the tool for use.

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Usage

1. Run the tool using the following command:

   pi_full_monitor

   If the command is not found, ensure the virtual environment is activated or the alias is correctly configured:

   source venv/bin/activate
   python3 -m pi_monitor

2. Press Ctrl+C to exit the monitoring dashboard gracefully.

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Dashboard Metrics

The dashboard displays the following metrics:

General System Stats

Metric	Description
CPU Usage	Percentage of CPU being utilized.
CPU Temp	Current temperature of the CPU.
Memory Usage	Percentage and absolute memory usage (used/total).
Disk Usage	Percentage and absolute disk usage (used/total).
Network Sent	Total bytes sent over the network since boot.
Network Received	Total bytes received over the network since boot.

Top Processes

A separate table lists the top processes sorted by CPU and memory usage, providing visibility into resource-intensive applications.

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Development

Project Structure

pi_full_monitor/
├── pi_monitor/                  # Main package directory
│   ├── __init__.py              # Initializes the package
│   ├── __main__.py              # Entry point for the tool
│   ├── monitor.py               # Core monitoring logic
│   ├── utils.py                 # Utility functions (e.g., formatting, process handling)
├── venv/                        # Virtual environment (created during installation)
├── install.sh                   # Installation script
├── README.md                    # Documentation file
├── requirements.txt             # Python dependencies
├── pyproject.toml               # Build configuration for setuptools
├── setup.py                     # Package setup script

Key Files

• pi_monitor/monitor.py: Contains the logic for gathering and displaying system metrics.
• pi_monitor/utils.py: Helper functions for formatting sizes, fetching processes, etc.
• install.sh: Automates the setup process for the virtual environment and dependencies.

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Troubleshooting

Issue: Command pi_full_monitor not found

• Ensure the virtual environment is activated:

  source venv/bin/activate

• Verify the installation:

  pip show pi-full-monitor

Issue: Missing Python Dependencies

• Run the following command to manually install dependencies:

  pip install -r requirements.txt

Issue: Permission Denied for install.sh

• Make the script executable:

  chmod +x install.sh

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License

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

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Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a feature branch:

   git checkout -b feature-name

3. Commit your changes and push:

   git commit -m "Add feature-name"
   git push origin feature-name

4. Open a pull request.

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Contact

For issues or suggestions, feel free to open an issue on the GitHub repository.