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-2023.8.1.tar.gz (25.3 kB view details)

Uploaded Source

Built Distribution

scikit_hep-2023.8.1-py3-none-any.whl (22.3 kB view details)

Uploaded Python 3

File details

Details for the file scikit-hep-2023.8.1.tar.gz.

File metadata

  • Download URL: scikit-hep-2023.8.1.tar.gz
  • Upload date:
  • Size: 25.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.4

File hashes

Hashes for scikit-hep-2023.8.1.tar.gz
Algorithm Hash digest
SHA256 8d775a5a7f9dcd652b4f64a35f1b5c96fa78a72df0ec02ccfced750809edeb75
MD5 10bb0d95aa72380f937e20b911e8a4b8
BLAKE2b-256 de35d6f5b09d5ab8601ea9f232196fa1a14698d6831153643275931db570ed5e

See more details on using hashes here.

File details

Details for the file scikit_hep-2023.8.1-py3-none-any.whl.

File metadata

File hashes

Hashes for scikit_hep-2023.8.1-py3-none-any.whl
Algorithm Hash digest
SHA256 e88085c160996c1f29083c98dc562f2d34771f75966583dde4804104d4571c6e
MD5 3edf6b7a60d4caaf2ef1f340221cc1ca
BLAKE2b-256 106042d405f06f599eaa05f6e8ef245d3409833f7f1e491ef704a823b55805ac

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