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-2024.1.1.tar.gz (25.4 kB view details)

Uploaded Source

Built Distribution

scikit_hep-2024.1.1-py3-none-any.whl (22.3 kB view details)

Uploaded Python 3

File details

Details for the file scikit-hep-2024.1.1.tar.gz.

File metadata

  • Download URL: scikit-hep-2024.1.1.tar.gz
  • Upload date:
  • Size: 25.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.7

File hashes

Hashes for scikit-hep-2024.1.1.tar.gz
Algorithm Hash digest
SHA256 82f8736f338e678f0d5b616a27dc9d53c8f28852d1fd39637c3cc031a16946e9
MD5 d3c572d71fe3bcf3b7afd3933b7c9bae
BLAKE2b-256 f9e5e118781c86fc510bfffe984f2b646b78bfed01e55d0be7e59c60bc692462

See more details on using hashes here.

File details

Details for the file scikit_hep-2024.1.1-py3-none-any.whl.

File metadata

File hashes

Hashes for scikit_hep-2024.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 18eca1706875710521115ea931ffd217b6e9897762ea9ed12484820f6ddd0bfb
MD5 0f934ad1a6e62aca9e3c3a64de5356d5
BLAKE2b-256 6ee15a44daf1311b3821ccee342bddea57eb362f8b775dba536bff22952cddc1

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