Metadata-Version: 2.4
Name: vizzbreeze
Version: 1.0.1
Summary: A high-performance streamlined transactional web-dashboard for advanced graph analytics and risk audit.
Author: Mila Alex
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.9
Requires-Dist: numpy>=1.25.0
Requires-Dist: openpyxl>=3.1.0
Requires-Dist: pandas>=2.1.0
Requires-Dist: plotly>=5.18.0
Requires-Dist: streamlit>=1.35.0
Description-Content-Type: text/markdown

# VizzBreeze

A lightweight, high-performance transactional web-dashboard designed for advanced data flow analytics, multi-stage routing visualization, and statistical risk audit. Built natively on top of Streamlit, Pandas, and Plotly.

## Key Features

- **Flat Transaction Processing Engine**: Optimized for fast processing of un-aggregated logs (e.g., Client ➔ Fund ➔ Asset).
- **Global Session Synchronization**: Seamlessly locks metric column selections, typography sizes, and alignments across all workspace views.
- **Auto-Scroll Suppression**: Enhanced layout architecture prevents viewport jumps during widget updates and data updates.
- **Advanced Graph Matrix Analytics**: Includes high-fidelity stacked charts, multi-dimensional Parcats layouts, Density Matrices, and automated IQR risk audit profiling tools.

## Quick Start

You can install and launch the interactive analytical control room globally using just two commands in your terminal:

```bash
pip install vizzbreeze
vizzbreeze-run
```

**Test Dataset**: To explore the dashboard features instantly, you can use the pre-configured spreadsheet **`sample_data_unaggregated.xlsx`** located in the root folder of this repository. Just drag and drop it into the sidebar upload zone!

## Core Analytical Tabs

1. **Flows**: Explore multi-stage multi-dimensional category paths with thin, light axis labels and custom high-contrast hover tooltips.
2. **Funnel**: Track progressive conversion drops along specific workflow layers.
3. **Structural Breakdown**: Classic stacked column bar charts configured with responsive axis titles that update on the fly based on active filters.
4. **Bento**: An asymmetrical modular tile framework designed to compress complex multi-level dimensions into a clean, prioritized grid dashboard.
5. **Density Matrix**: High-density dashboard to scan cluster intersections instantly.
5. **Anomaly & Risk Audit**: Automated statistical anomaly profiling that detects process outliers without freezing the browser engine.

## Requirements

- Python >= 3.9
- Streamlit >= 1.35.0
- Pandas >= 2.1.0
- Plotly >= 5.18.0

## License

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