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https://github.com/4211421036/githubiotpy

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
https://github.com/4211421036/githubiotpy

cli esp32 esp8266 github-actions github-iot matplotlib numpy pypi-packages python tkinter

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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

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README 

        
# GitHubIoT Documentation





  GitHubIoT Logo




Before Started Develoment this Application. Please Readme Wiki repository GitHub IoT for Arduino IDE Application at [https://github.com/4211421036/githubiot/wiki](https://github.com/4211421036/githubiot/wiki), following step by step. And The last, your can develoment webApp with GA  [https://github.com/marketplace/actions/generate-iot-dashboard](https://github.com/marketplace/actions/generate-iot-dashboard) automation step by step. Thank You!



## Table of Contents



- [Introduction](#introduction)

- [Installation](#installation)

- [Quick Start](#quick-start)

- [Features](#features)

- [Usage](#usage)

  - [Command Line Interface](#command-line-interface)

  - [Using as a Module](#using-as-a-module)

- [Application Structure](#application-structure)

  - [Core Components](#core-components)

  - [User Interface](#user-interface)

  - [Data Handling](#data-handling)

- [Configuration](#configuration)

  - [Configuration File](#configuration-file)

  - [Runtime Configuration](#runtime-configuration)

- [Customization](#customization)

  - [Themes](#themes)

  - [Chart Types](#chart-types)

  - [Animation Settings](#animation-settings)

- [Troubleshooting](#troubleshooting)

  - [Common Issues](#common-issues)

  - [Debug Mode](#debug-mode)

- [API Reference](#api-reference)

  - [Main Methods](#main-methods)

  - [Data Processing Functions](#data-processing-functions)

- [Contributing](#contributing)

- [License](#license)

- [Authors](#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.



> [!Note]

> GitHubIoT is designed to work with JSON data feeds, making it compatible with most IoT platforms and REST APIs.



## Installation



You can install GitHubIoT using pip:



```bash

pip install githubiot

```



or using Docker command line:

```bash

docker pull galihridhoutomo/githubiot

```



### Prerequisites



- Python 3.7 or higher

- Required dependencies:

  - Matplotlib

  - NumPy

  - Requests

  - TkInter



> [!Important]

> Make sure you have the latest version of pip to avoid compatibility issues.



## Quick Start



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



```bash

githubiot --create-app

```



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



```bash

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

```



and the last step



```bash

githubiot --run

```



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



```bash

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:



| Command | Description |

|---------|-------------|

| `githubiot --create-app` | Create a new application template |

| `githubiot --build` | Build the application to an executable |

| `githubiot --run` | Run the application |

| `githubiot --json-url URL` | Set custom JSON URL |

| `githubiot --name NAME` | Set custom application name |

| `githubiot -v, --version` | Show version information |



### Using as a Module



You can also integrate GitHubIoT into your own Python projects:



```python

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:



```json

{

  "url": "https://api.example.com/data",

  "app_name": "GitHubIoT App"

}

```



> [!Warning]

> Do not manually edit the configuration file while the application is running. Use the application interface or CLI commands to modify settings.



### 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:



```bash

githubiot --debug

```



This will provide additional console output to help diagnose issues.



## API Reference



### Main Methods



| Method | Description |

|--------|-------------|

| `githubiot.start()` | Initializes and starts the application |

| `githubiot.load_config()` | Loads configuration from file |

| `githubiot.update_config()` | Updates configuration settings |

| `githubiot.build()` | Builds executable version |



### Data Processing Functions



| Function | Description |

|----------|-------------|

| `load_data()` | Fetches data from JSON source |

| `refresh_data()` | Updates data from source |

| `generate_sample_data()` | Creates sample data for testing |

| `create_graph()` | Renders visualization from data |



## Contributing



Contributions to GitHubIoT are welcome! Please follow these steps:



1. [Fork](https://github.com/4211421036/githubiotpy/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](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



```bibtex

@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 = {GitHub repository},

}

```



---





  GitHubIoT - Building the Future with Integrated Microcontroller Solutions