galihridhoutomo/githubiot repository overview

⁠GitHubIoT Documentation

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⁠Table of Contents

• Introduction⁠
• Installation⁠
• Quick Start⁠
• Features⁠
• Usage⁠
  • Command Line Interface⁠
  • Using as a Module⁠
• Application Structure⁠
  • Core Components⁠
  • User Interface⁠
  • Data Handling⁠
• Configuration⁠
  • Configuration File⁠
  • Runtime Configuration⁠
• Customization⁠
  • Themes⁠
  • Chart Types⁠
  • Animation Settings⁠
• Troubleshooting⁠
  • Common Issues⁠
  • Debug Mode⁠
• API Reference⁠
  • Main Methods⁠
  • Data Processing Functions⁠
• Contributing⁠
• License⁠
• Authors⁠

⁠Introduction

GitHubIoT is a comprehensive toolkit designed to simplify the visualization of IoT (Internet of Things) data with seamless GitHub integration. The application provides an intuitive graphical interface for real-time data monitoring, analysis, and configuration, making it ideal for both beginners and experienced developers working with IoT devices.

⁠Installation

You can install GitHubIoT using pip:

pip install githubiot

⁠Prerequisites

• Python 3.7 or higher
• Required dependencies:
  • Matplotlib
  • NumPy
  • Requests
  • TkInter

⁠Quick Start

After installation, you can quickly start the application with default settings:

githubiot --create-app

This will launch the application with default configurations. For a customized setup:

githubiot --name "My IoT Dashboard" --json-url "https://my-iot-api.com/data"

and the last step

githubiot --run

if you build this app to .exe application Desktop. Can be interact CLI githubiot below

githubiot --build

⁠Features

• Real-time Data Visualization: Monitor IoT data streams in real-time
• Multiple Chart Types: Support for various visualization methods
• Customizable Themes: Choose from multiple built-in themes or create your own
• Animation Control: Enable/disable animations for performance optimization
• Graph Export: Save visualizations in various formats (PNG, PDF, etc.)
• Responsive Interface: Adapts to different screen sizes
• JSON Data Integration: Connect to any JSON data source
• Configurable Settings: Customize application behavior through configuration files

⁠Usage

⁠Command Line Interface

GitHubIoT provides a comprehensive command line interface for various operations:

⁠Using as a Module

You can also integrate GitHubIoT into your own Python projects:

import githubiot

# Start with custom parameters
githubiot.start(
    name="My IoT Dashboard",
    url_json="https://api.example.com/data",
    icon="https://example.com/icon.ico",
    status="build"  # or "run"
)

⁠Application Structure

⁠Core Components

The application is built around the JSONGraphApp class, which manages the following key aspects:

1. Configuration Management: Loads and applies settings from a configuration file
2. UI Construction: Creates the menu system and UI widgets
3. Data Handling: Fetches and processes data from JSON sources
4. Graph Rendering: Visualizes data using Matplotlib
5. Animation Control: Manages real-time animation of data

⁠User Interface

The UI consists of:

• Main visualization area
• Toolbar for common actions
• Menu system with File, Options, and Help menus
• Theme selection and customization options

⁠Data Handling

The application can:

• Connect to remote JSON data sources
• Generate sample data when connection fails
• Process and transform data for visualization
• Refresh data on demand

⁠Configuration

⁠Configuration File

GitHubIoT uses a config.json file for persistent settings:

{
  "url": "https://api.example.com/data",
  "app_name": "GitHubIoT App"
}

⁠Runtime Configuration

The application can detect and apply configuration changes at runtime. When you modify settings externally, the application will update automatically.

⁠Customization

⁠Themes

GitHubIoT supports multiple visualization themes:

• Default
• Classic
• Dark Background
• GGPlot
• Seaborn
• Solarize Light
• BMH
• Tableau Colorblind-friendly
• FiveThirtyEight
• Custom themes

To cycle through themes, use the "Change Theme" option in the File menu.

⁠Chart Types

While the current implementation focuses on line charts for EM wave visualization, the architecture supports extending to other chart types:

• Line charts
• Bar charts
• Scatter plots
• Area charts

⁠Animation Settings

Animation can be toggled on/off from the Options menu. This is particularly useful when:

• Working with very large datasets
• Running on resource-constrained devices
• Generating static exports

⁠Troubleshooting

⁠Common Issues

1. Data Not Loading

   • Verify your internet connection
   • Check that the JSON URL is correct and accessible
   • Ensure the JSON format matches the expected structure

2. Application Crashes

   • Update to the latest version
   • Check for conflicting Python packages
   • Verify that all dependencies are installed correctly

3. Visualization Issues

   • Try changing the theme
   • Restart the application
   • Verify your data structure

⁠Debug Mode

For advanced troubleshooting, you can run the application in debug mode:

githubiot --debug

This will provide additional console output to help diagnose issues.

⁠API Reference

⁠Main Methods

⁠Data Processing Functions

⁠Contributing

Contributions to GitHubIoT are welcome! Please follow these steps:

1. Fork⁠ the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Open a Pull Request

Please ensure your code follows the project's coding standards and includes appropriate tests.

⁠License

This project is licensed under the MIT LICENCE https://github.com/4211421036/githubiotpy/LICENCE⁠ - see the LICENSE file for details.

⁠Authors

1. GALIH RIDHO UTOMO
2. Fionita Fahra Azzahra

⁠Cite

Please cite this respotory, if your use in the publication

@misc{githubiot,
author = {Utomo, Galih Ridho, Fionita Fahra Azzahra},
title = {GitHub IoT a comprehensive toolkit designed to simplify the visualization of IoT (Internet of Things) data with seamless GitHub integration. The application provides an intuitive graphical interface for real-time data monitoring, analysis, and configuration, making it ideal for both beginners and experienced developers working with IoT devices microcontroler (ESP32 or ESP8266) realtime},
year = {2025},
howpublished = {\url{https://hub.docker.com/r/galihridhoutomo/githubiot}},
note = {Docker Packages},
}

GitHubIoT - Building the Future with Integrated Microcontroller Solutions