mango-dashboard 0.1.0a3

Library with a collection of useful classes and methods to DRY

Mango Dashboard

Mango Dashboard is an interactive web application built with Streamlit that provides tools for exploring and visualizing data files. It includes two main modules: File Explorer and Time Series Dashboard.

Features

File Explorer

• Interactive file explorer: Navigate through folders and files visually
• Multiple format visualization: Supports CSV, Excel, JSON, HTML, images (PNG, JPG, JPEG) and Markdown
• Data editing: Edit and save CSV, Excel and JSON files directly from the interface
• Flexible configuration: Customize layout with multiple rows and columns
• GCP support: Integration with Google Cloud Storage for remote files
• Directory tree: Hierarchical visualization of folder structure

Time Series Dashboard

• Time series analysis: Specialized tools for temporal data
• Data loading: Interface for uploading and processing time series files
• Visualizations: Interactive charts for temporal analysis
• Forecast templates: Predefined templates for forecasting models

Installation

Prerequisites

• Python 3.8 or higher
• pip or uv for dependency management

Project Installation

1. Clone the repository:

git clone <repository-url>
cd mango

2. Install dependencies:

# Using pip
pip install -e mango_dashboard/

# Or using uv
uv sync mango_dashboard/

3. Install additional dependencies (if needed):

pip install streamlit pandas plotly pillow

Usage

File Explorer

Basic command

# From the mango project root
cd C:\Users\NataliaGorrin\Desktop\Proyectos_baobab\mango

# Using the CLI
python -m mango_dashboard.file_explorer.cli.dashboard file_explorer --path "path/to/your/folder"

# Or running directly
streamlit run mango_dashboard/mango_dashboard/file_explorer/dashboards/file_explorer_app.py -- --path "path/to/your/folder"

Available parameters

• --path or -p: Path of the folder to explore (default: current directory)
• --editable or -e: Enable dashboard editing (0=no, 1=yes, -1=default)
• --config_path or -c: Path to the JSON configuration file
• --gcp_credentials_path: Path to Google Cloud credentials (GCP only)

Usage examples

Explore a local folder:

python -m mango_dashboard.file_explorer.cli.dashboard file_explorer --path "path/to/your/folder"

Explore with custom configuration:

python -m mango_dashboard.file_explorer.cli.dashboard file_explorer --path "./data" --config_path "./my_config.json" --editable 1

Explore files in Google Cloud Storage:

python -m mango_dashboard.file_explorer.cli.dashboard file_explorer --path "gs://my-bucket/data" --gcp_credentials_path "./credentials.json"

Time Series Dashboard

# Run the time series dashboard
python -m mango_dashboard.time_series.cli.dashboard time_series

Configuration

JSON Configuration File

The File Explorer uses a JSON configuration file to customize the interface:

{
    "title": "My Custom Dashboard",
    "header": "Data Explorer",
    "icon": ":chart_with_upwards_trend:",
    "layout": "wide",
    "dir_path": "/path/to/my/data",
    "n_rows": 2,
    "n_cols_1": 1,
    "n_cols_2": 2,
    "editable": true,
    "dict_layout": {
        "file_1_1": "/path/to/file1.csv",
        "file_2_1": "/path/to/file2.html",
        "file_2_2": "/path/to/file3.xlsx"
    }
}

Configuration Parameters

• title: Application title
• header: Main header
• icon: Page icon (emoji or icon code)
• layout: Page layout ("wide" or "centered")
• dir_path: Default directory path
• n_rows: Number of rows in the layout
• n_cols_X: Number of columns in row X
• editable: Whether the dashboard is editable
• dict_layout: Mapping of files to specific positions

Supported File Formats

Visualization

• CSV: Editable tables with pandas
• Excel (.xlsx): Multiple sheets with tabs
• JSON: Table visualization or raw JSON
• HTML: Embedded Plotly charts
• Images: PNG, JPG, JPEG with size controls
• Markdown: Rendered as HTML

Editing

• CSV: Data editor with pandas
• Excel: Sheet editor
• JSON: Table editor or raw JSON

Advanced Features

Google Cloud Storage Integration

• Support for gs:// paths
• Authentication with JSON credential files
• Remote bucket and object exploration

Visualization Customization

• Width and height control for images and HTML charts
• Flexible layout with multiple rows and columns
• Persistent configuration in JSON files

Editing Features

• Inline editing of tabular data
• Automatic change saving
• Support for multiple output formats

Project Structure

mango_dashboard/
├── mango_dashboard/
│   ├── file_explorer/
│   │   ├── cli/
│   │   │   └── dashboard.py          # CLI for File Explorer
│   │   └── dashboards/
│   │       ├── file_explorer_app.py  # Main application
│   │       └── file_explorer_handlers.py  # File handlers
│   └── time_series/
│       ├── cli/
│       │   └── dashboard.py          # CLI for Time Series
│       └── dashboards/
│           └── time_series_app.py    # Time series application
├── README.md
└── pyproject.toml

Troubleshooting

Error: "File does not exist"

Make sure to run the command from the mango project root:

cd C:\Users\NataliaGorrin\Desktop\Proyectos_baobab\mango

Error: "TypeError: stat: path should be string, bytes, os.PathLike or integer, not NoneType"

This error has been fixed in the current version. If it persists, make sure you're using the latest version of the code.

Windows path issues

For Windows paths, use double quotes:

python -m mango_dashboard.file_explorer.cli.dashboard file_explorer --path "G:\Mi unidad\data"

Contributing

1. Fork the project
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

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

Contact

For technical support or questions: [e-mail]

Changelog

Current Version

• ✅ Fixed gcp_path None error
• ✅ Improved Windows path support
• ✅ Enhanced user interface
• ✅ Complete documentation