Metadata-Version: 2.4
Name: bioviz-kit
Version: 0.3.2
Summary: Framework-agnostic plotting utilities for biological and clinical data visualization
Author-email: Victoria Cheung <victoriakcheung@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Victoria Cheung
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
        Acknowledgement: This project builds on work originally developed at
        Revolution Medicines.
        
Project-URL: Homepage, https://github.com/vic-cheung/bioviz-kit
Project-URL: Issue Tracker, https://github.com/vic-cheung/bioviz-kit/issues
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=2.0
Requires-Dist: matplotlib>=3.6
Requires-Dist: seaborn>=0.12
Requires-Dist: adjusttext>=0.8
Requires-Dist: loguru>=0.7
Requires-Dist: pydantic<3,>=1.10
Requires-Dist: ipykernel>=7.1.0
Requires-Dist: statsmodels>=0.14.6
Provides-Extra: testing
Requires-Dist: pytest; extra == "testing"
Dynamic: license-file

bioviz-kit
==========

Framework-agnostic visualization library for publication-ready clinical and biological data plots.

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)

## Features

- **Publication-ready styling** – Clean, professional visualizations out of the box
- **Framework-agnostic** – Works with any data pipeline or analysis framework
- **Customizable configurations** – Extensive theming and layout options
- **Clinical & bioinformatics focused** – Specialized plot types for common analyses

## Installation

bioviz-kit
==========

Framework-agnostic visualization library for publication-ready clinical and biological data plots.

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)

## Features

- **Publication-ready styling** – Clean, professional visualizations out of the box
- **Framework-agnostic** – Works with any data pipeline or analysis framework
- **Customizable configurations** – Extensive theming and layout options
- **Clinical & bioinformatics focused** – Specialized plot types for common analyses

## Installation

Install from PyPI:

```bash
pip install bioviz-kit
```

Or install in development mode:

```bash
pip install -e .
```

## Requirements

- Python 3.11+
- pandas
- matplotlib
- seaborn
- adjustText

## Usage

```python
from bioviz import lineplot, oncoplot

# Generate styled plots with minimal configuration
fig = lineplot.generate_styled_lineplot(df, config)
fig = oncoplot.generate_styled_oncoplot(df, config)
```

See [examples/](examples/) for complete usage examples.

## Examples

- Example files live in the `examples/` directory. Recommended practices:
    - Keep runnable `.py` scripts for quick CLI usage and reproducible examples.
    - Provide companion `.ipynb` notebooks for narrative tutorials and figures. Convert with `jupytext` or `nbconvert` if needed:

```bash
pip install jupytext
jupytext --to notebook examples/my_example.py -o examples/my_example.ipynb
```

    - Name files with short, descriptive snake_case (optionally numeric prefixes for ordered tutorials, e.g. `01_quickstart.ipynb`).
    - Add a short header comment or top-level README in `examples/` describing each example's purpose and required inputs.

## Documentation and ReadTheDocs

TBD

## Design Philosophy

- Lightweight `DefaultStyle` provided; easily extended with custom themes


## Licensing

- `bioviz-kit` is released under the MIT License © 2025 Victoria Cheung.

### Thanks

This package was spun out of internal tooling I wrote at Revolution Medicines.
Many thanks to the team there for allowing the code to be open sourced.
