`scikit-hep`: metapackage for Scikit-HEP

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. Packages from Scikit-HEP are presently used by several major experiments.

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 broad 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 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: 3.12.3 | packaged by conda-forge | (main, Apr 15 2024, 18:20:11) [MSC v.1938 64 bit (AMD64)]
executable: C:\Users\eduar\miniconda3\python.exe
   machine: Windows-11-10.0.26100-SP0

Python dependencies:
setuptools: 75.1.0
       pip: 24.2
     numpy: 2.0.1
     scipy: 1.15.1
    pandas: 2.2.3
matplotlib: 3.10.0

Scikit-HEP package version and dependencies:
        awkward: 2.8.1
boost_histogram: 1.5.0
  decaylanguage: 0.18.6
       hepstats: 0.9.2
       hepunits: 2.3.5
           hist: 2.8.0
     histoprint: 2.6.0
        iminuit: 2.30.1
         mplhep: 0.3.55
       particle: 0.25.2
          pylhe: 0.9.1
       resample: 1.10.1
     scikit-hep: 2025.4.1
         uproot: 5.6.0
         vector: 1.6.1

Note on the versioning system:

This package uses Calendar Versioning (CalVer).

Contributors

We would like to acknowledge the contributors that made this project possible (emoji key):

_{Eduardo Rodrigues} 🚧 💻 📖	_{Henry Schreiner} 🚧 💻 📖	_{Matthieu Marinangeli} 💻 📖	_{Jim Pivarski} 💻 📖	_{Brian Pollack} 💻 📖	_VanyaBelyaev 💻 📖	_{Nils Braun} 💻 📖
_{Matthew Feickert} 💻 📖	_{Andrzej Novak} 💻	_{Alex Pearwin} 📖	_{Alexander Mazurov} 💻	_{Chris Burr} 💻	_{Noel Dawe} 💻	_{Lukas Koch} 💻 📖
_{Hans Dembinski} 💻 📖	_{Jeremy McRae} 💻	_{Jonas Eschle} 💻

This project follows the all-contributors specification.

Metadata

Release files for scikit-hep 2026.10.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for scikit-hep 2026.10.1
File	Size	Uploaded
scikit_hep-2026.10.1.tar.gz	8.4 kB	Oct 6, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for scikit-hep 2026.10.1
File	Interpreter	ABI	Platform	Reset
scikit_hep-2026.10.1-py3-none-any.whl 6.9 kB Oct 6, 2026	Python 3	none	any	Details

Total release size: 15.3 kB

Release files / scikit_hep-2026.10.1.tar.gz

Download URL	scikit_hep-2026.10.1.tar.gz
Size	8.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`e3551ff64b038b67f5d93879066f5a0ad9871d3ab11ec0115ec4d8f79a0584ee`
BLAKE2b-256 checksum How to use checksums	`1f2624ca65d6c202518307253db24fb5b420ced4e7bf59897a78820db2e464df`
Upload date	Oct 6, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/scikit-hep/scikit-hep
Publishing commit: github.com/scikit-hep/scikit-hep/tree/5b13363b495e637fdb34d64c9cfd866b1bef8fc3

Workflow

Publishing configuration: github.com/scikit-hep/scikit-hep/blob/5b13363b495e637fdb34d64c9cfd866b1bef8fc3/.github/workflows/cd.yml
Publishing logs: github.com/scikit-hep/scikit-hep/actions/runs/37484473928/attempts/1

Artifact

Subject: scikit_hep-2026.10.1.tar.gz
SHA-256 checksum: e3551ff64b038b67f5d93879066f5a0ad9871d3ab11ec0115ec4d8f79a0584ee Verifying attestations

Release files / scikit_hep-2026.10.1-py3-none-any.whl

Download URL	scikit_hep-2026.10.1-py3-none-any.whl
Size	6.9 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`93fabbb74c17a9600e5fb52abebd3067b041933230de852d90242757fb322bff`
BLAKE2b-256 checksum How to use checksums	`24f7ff7f560da1c700e72dfd4bad835f7d16e1efa0b1704fdb02000b854f0dc9`
Upload date	Oct 6, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/7.0.0 CPython/3.13.14`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/scikit-hep/scikit-hep
Publishing commit: github.com/scikit-hep/scikit-hep/tree/5b13363b495e637fdb34d64c9cfd866b1bef8fc3

Workflow

Publishing configuration: github.com/scikit-hep/scikit-hep/blob/5b13363b495e637fdb34d64c9cfd866b1bef8fc3/.github/workflows/cd.yml
Publishing logs: github.com/scikit-hep/scikit-hep/actions/runs/37484473928/attempts/1

Artifact

Subject: scikit_hep-2026.10.1-py3-none-any.whl
SHA-256 checksum: 93fabbb74c17a9600e5fb52abebd3067b041933230de852d90242757fb322bff Verifying attestations