semvec/pypi-packages huggingface dataset:
auditor-apel-plugin 0.10.1
AUDITOR plugin for sending accounting data to APEL
Requires Python: >=3.9

# AUDITOR-APEL-plugin

Plugin for AUDITOR to report job records to APEL

## License

Licensed under

 - BSD-2-Clause Plus Patent License ([LICENSE](https://github.com/ALU-Schumacher/AUDITOR/tree/main/plugins/apel/LICENSE))

### Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you shall be licensed as above, without any additional terms or conditions.
libadctf 0.1.2
A Python library
Requires Python: >=3.14

# libadctf

A Python library for [describe your library's purpose here].

## Installation

### From PyPI (when published)

```bash
pip install libadctf
```

### Development installation with uv

```bash
# Clone the repository
git clone https://github.com/yourusername/libadctf.git
cd libadctf

# Install in development mode
uv pip install -e .
```

## Development

This project uses `uv` for dependency management and packaging.

### Setting up development environment

```bash
# Install development dependencies
uv pip install -e ".[dev]"
```

### Running tests

```bash
pytest
```

### Building the package

```bash
uv build
```

### Publishing to PyPI

```bash
# Build the package
uv build

# Publish to PyPI (requires API token)
uv publish
```

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
bsccm 1.2.1
Access the Berkeley Single Cell Computational Microscopy
Requires Python: >=3.6

[![DOI](https://zenodo.org/badge/331695371.svg)](https://zenodo.org/doi/10.5281/zenodo.10392182)
# Berkeley Single Cell Computational Microscopy Dataset

See the [project website](https://waller-lab.github.io/BSCCM/) and [paper](https://arxiv.org/abs/2402.06191) for more information.

For using the `bsccm` python package for using the dataset, see the [Getting Started Jupyter notebook](https://github.com/Waller-Lab/BSCCM/blob/main/Getting_started.ipynb).

Raw data is hosted [here](https://doi.org/10.5061/dryad.sxksn038s), but it is easiest to download using the python package as shown in the notebook