Skip to main content

Metapackage of Scikit-HEP project libraries for Particle Physics.

Project description

https://scikit-hep.org/assets/images/Scikit--HEP-Project-blue.svg https://img.shields.io/gitter/room/gitterHQ/gitter.svg https://img.shields.io/pypi/v/scikit-hep.svg https://img.shields.io/conda/vn/conda-forge/scikit-hep.svg https://zenodo.org/badge/DOI/10.5281/zenodo.1043949.svg https://github.com/scikit-hep/scikit-hep/workflows/CI/badge.svg https://codecov.io/gh/scikit-hep/scikit-hep/graph/badge.svg?branch=master

Project info

The Scikit-HEP project is a community-driven and community-oriented project with the aim of providing Particle Physics at large with an ecosystem for data analysis in Python embracing all major topics involved in a physicist’s work. The project started in Autumn 2016 and its packages are actively developed and maintained.

It is not just about providing core and common tools for the community. It is also about improving the interoperability between HEP tools and the Big Data scientific ecosystem in Python, and about improving on discoverability of utility packages and projects.

For what concerns the project grand structure, it should be seen as a toolset rather than a toolkit.

Getting in touch

There are various ways to get in touch with project admins and/or users and developers.

scikit-hep package

scikit-hep is a metapackage for the Scikit-HEP project.

Installation

You can install this metapackage from PyPI with pip:

python -m pip install scikit-hep

or you can use Conda through conda-forge:

conda install -c conda-forge scikit-hep

All the normal best-practices for Python apply; you should be in a virtual environment, etc.

Package version and dependencies

Please check the setup.cfg and requirements.txt files for the list of Python versions supported and the list of Scikit-HEP project packages and dependencies included, respectively.

For any installed scikit-hep the following displays the actual versions of all Scikit-HEP dependent packages installed, for example:

>>> import skhep
>>> skhep.show_versions()

System:
    python: 3.10.10 | packaged by conda-forge | (main, Mar 24 2023, 20:08:06) [GCC 11.3.0]
executable: /srv/conda/envs/notebook/bin/python
   machine: Linux-5.15.0-72-generic-x86_64-with-glibc2.27

Python dependencies:
       pip: 23.1.2
     numpy: 1.24.3
     scipy: 1.10.1
    pandas: 2.0.2
matplotlib: 3.7.1

Scikit-HEP package version and dependencies:
        awkward: 2.2.2
boost_histogram: 1.3.2
  decaylanguage: 0.15.3
       hepstats: 0.6.1
       hepunits: 2.3.2
           hist: 2.6.3
     histoprint: 2.4.0
        iminuit: 2.21.3
         mplhep: 0.3.28
       particle: 0.22.0
          pylhe: 0.6.0
       resample: 1.6.0
          skhep: 2023.06.09
         uproot: 5.0.8
         vector: 1.0.0

Note on the versioning system:

This package uses Calendar Versioning (CalVer).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scikit_hep-2024.9.1.tar.gz (25.4 kB view details)

Uploaded Source

Built Distribution

scikit_hep-2024.9.1-py3-none-any.whl (22.3 kB view details)

Uploaded Python 3

File details

Details for the file scikit_hep-2024.9.1.tar.gz.

File metadata

  • Download URL: scikit_hep-2024.9.1.tar.gz
  • Upload date:
  • Size: 25.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.1 CPython/3.12.6

File hashes

Hashes for scikit_hep-2024.9.1.tar.gz
Algorithm Hash digest
SHA256 d89e0de198c8dbabfdae97938a9a0398dd22a7b0749743b92c155914dd382c2d
MD5 af85d963ef798b0ac3b432476de041d9
BLAKE2b-256 3d2b50d3796748b9f7925c61102f8b97bcf3a1ee19fb02cbc70ed30985d2d0ac

See more details on using hashes here.

File details

Details for the file scikit_hep-2024.9.1-py3-none-any.whl.

File metadata

File hashes

Hashes for scikit_hep-2024.9.1-py3-none-any.whl
Algorithm Hash digest
SHA256 8fada00e17909627b5b392059919f1821a289b3f39ea7441d2fcbc1e936aa5ad
MD5 6b0e3eaf46050d1cabf8c9af2a9aada9
BLAKE2b-256 af8d942d3c22c17114dc07bd555e4ad8fec0a5df668e481196928a7a5275b8fe

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page