semvec/pypi-packages huggingface dataset:
warc-cache 1.0.4
Easy WARC records disk cache.
Requires Python: >=3.8

[![PyPi](https://img.shields.io/pypi/v/warc-cache?style=flat-square)](https://pypi.org/project/warc-cache/)
[![CI](https://img.shields.io/github/actions/workflow/status/janheinrichmerker/warc-cache/ci.yml?branch=main&style=flat-square)](https://github.com/janheinrichmerker/warc-cache/actions/workflows/ci.yml)
[![Code coverage](https://img.shields.io/codecov/c/github/janheinrichmerker/warc-cache?style=flat-square)](https://codecov.io/github/janheinrichmerker/warc-cache/)
[![Python](https://img.shields.io/pypi/pyversions/warc-cache?style=flat-square)](https://pypi.org/project/warc-cache/)
[![Issues](https://img.shields.io/github/issues/janheinrichmerker/warc-cache?style=flat-square)](https://github.com/janheinrichmerker/warc-cache/issues)
[![Commit activity](https://img.shields.io/github/commit-activity/m/janheinrichmerker/warc-cache?style=flat-square)](https://github.com/janheinrichmerker/warc-cache/commits)
[![Downloads](https://img.shields.io/pypi/dm/warc-cache?style=flat-square)](https://pypi.org/project/warc-cache/)
[![License](https://img.shields.io/github/license/janheinrichmerker/warc-cache?style=flat-square)](LICENSE)

# 💾 warc-cache

Easy WARC records disk cache.

## Installation

Install the package from PyPI:

```shell
pip install warc-cache
```

## Usage

TODO

## Development

To build this package and contribute to its development you need to install the `build`, and `setuptools` and `wheel` packages:

```shell
pip install build setuptools wheel
```

(On most systems, these packages are already pre-installed.)

Then, install the package and test dependencies:

```shell
pip install -e .[tests]
```

You can now verify your changes against the test suite.

```shell
ruff check .                   # Code format and LINT
mypy .                         # Static typing
bandit -c pyproject.toml -r .  # Security
pytest .                       # Unit tests
```

Please also add tests for your newly developed code.

### Build wheels

Wheels for this package can be built with:

```shell
python -m build
```

## Support

If you hit any problems using this package, please file an [issue](https://github.com/janheinrichmerker/warc-cache/issues/new).
We're happy to help!

## License

This repository is released under the [MIT license](LICENSE).
bactovision 0.1.2
A package for bacterial image processing
Requires Python: >=3.8

# BactoVision
## A jupyter widget for annotating and visualizing bacterial growth data

[![Documentation](https://img.shields.io/badge/docs-mkdocs-blue)](https://StarostinV.github.io/bactovision/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python Version](https://img.shields.io/badge/python-3.8%2B-blue)](https://www.python.org/downloads/)
[![PyPI version](https://badge.fury.io/py/bactovision.svg)](https://badge.fury.io/py/bactovision)
[![Tests](https://github.com/StarostinV/bactovision/actions/workflows/test.yml/badge.svg)](https://github.com/StarostinV/bactovision/actions/workflows/test.yml)
[![codecov](https://codecov.io/gh/StarostinV/bactovision/branch/main/graph/badge.svg)](https://codecov.io/gh/StarostinV/bactovision)


<p align="center">
  <img src="docs/images/bactovision-logo.png" width="300" alt="BactoVision">
</p>


Bactovision provides a widget for jupyter notebook for fast semi-automated annotation of bacterial growth images. It is used in the following paper:

_Tyrosine auxotrophy shapes Staphylococcus aureus nasal colonization and interactions with commensal communities_ L. Camus et al. 2025 (submitted)


## Installation

Use pip to install the package:

```bash
pip install bactovision
```

or install from source:

```bash
git clone git@github.com:StarostinV/bactovision.git
cd bactovision
pip install .
```

## Documentation

Please see the full documentation [here](https://StarostinV.github.io/bactovision/).

## Basic usage

Start a jupyter notebook:

```bash
jupyter notebook
```

In the notebook, create a widget:

```python
from bactovision import BactoWidget

# Create a widget with an image
widget = BactoWidget('path/to/image.png')

# Display the widget
widget
```

<p align="center">
  <img src="docs/images/widget-cut.png" width="700" alt="BactoVision">
</p>


To get the mask and the metrics after the annotation is completed, run:

```python
annotation_mask = widget.get_annotation_mask()
metrics = widget.get_metrics()
```