semvec/pypi-packages huggingface dataset:
melctl-client 5.5.2
Command-line client for LuxProvide API (MelCtl)

This package provides the base MelCtl command-line client.

- Documentation_
- Repository_

About MelCtl
============

MelCtl provides a set of APIs to interact with LuxProvide_'s HPC (High
Performance Computer) and Cloud services.

The MelCtl command-line client allows our customers and internal users
to interact with MelCtl APIs.

The base package (`MelCtl client`_) provides basic plugins
(e.g. authentication). Supplementary packages such as
`melctl_client_plugins_customer` provides extra plugins to interact with
more services from the command line.

About LuxProvide_
=================

LuxProvide is Luxembourg’s one-stop-shop High Performance Computing
Centre, with missions to provide high performance computing
capabilities, high-speed connectivity and advanced applications on a
national, European and international scale, serving the public and
private sectors.


.. _Documentation: https://luxprovide.github.io/melctl-client/
.. _Repository: https://github.com/LuxProvide/melctl-client/
.. _LuxProvide: https://luxprovide.lu/
.. _MelCtl client: https://pypi.org/project/melctl-client/
fasthep 0.1.0
A meta package for the FAST-HEP toolkit
Requires Python: >=3.7

# fasthep

[![Actions Status][actions-badge]][actions-link]
[![Documentation Status][rtd-badge]][rtd-link]

[![PyPI version][pypi-version]][pypi-link]
[![PyPI platforms][pypi-platforms]][pypi-link]

[![GitHub Discussion][github-discussions-badge]][github-discussions-link]
[![Gitter][gitter-badge]][gitter-link]

FAST-HEP provides tools for analysis of high-energy physics data. It is designed
to be used in conjunction [SciKit-HEP](https://scikit-hep.org/) packages such as
[uproot](https://github.com/scikit-hep/uproot5) and
[awkward-array](https://github.com/scikit-hep/awkward) and more. On the data
processing side it leverages [Numba](https://numba.pydata.org/) and
[Cupy](https://cupy.dev/) to provide fast and efficient implementations of
common analysis tasks. For distributed computing, Dask is used as the primary
backend.

## Installation

The meta-package `fasthep` can be installed via `pip` or `conda`:

```bash
pip install fasthep
```

by default, this will install only the core packages such as the FAST-HEP CLI
and logging packages. To install the full package, including the optional
dependencies, use:

```bash
pip install fasthep[full]
```

You can also cherry-picker the optional dependencies you want to install:

```bash
pip install fasthep[plotting, carpenter, validate]
```

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[actions-badge]:            https://github.com/FAST-HEP/fasthep/workflows/CI/badge.svg
[actions-link]:             https://github.com/FAST-HEP/fasthep/actions
[github-discussions-badge]: https://img.shields.io/static/v1?label=Discussions&message=Ask&color=blue&logo=github
[github-discussions-link]:  https://github.com/orgs/FAST-HEP/discussions
[gitter-badge]:             https://badges.gitter.im/FAST-HEP/community.svg
[gitter-link]:              https://gitter.im/FAST-HEP/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge
[pypi-link]:                https://pypi.org/project/fasthep/
[pypi-platforms]:           https://img.shields.io/pypi/pyversions/fasthep
[pypi-version]:             https://img.shields.io/pypi/v/fasthep
[rtd-badge]:                https://readthedocs.org/projects/fasthep/badge/?version=latest
[rtd-link]:                 https://fasthep.readthedocs.io/en/latest/?badge=latest

<!-- prettier-ignore-end -->