scikit-hep

Metapackage of Scikit-HEP project data analysis packages for Particle Physics.

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scikit-hep: metapackage for Scikit-HEP

.. image:: https://scikit-hep.org/assets/images/Scikit--HEP-Project-blue.svg :target: https://scikit-hep.org

.. image:: https://img.shields.io/gitter/room/gitterHQ/gitter.svg :target: https://gitter.im/Scikit-HEP/community

.. image:: https://img.shields.io/pypi/v/scikit-hep.svg :target: https://pypi.python.org/pypi/scikit-hep

.. image:: https://img.shields.io/conda/vn/conda-forge/scikit-hep.svg :target: https://anaconda.org/conda-forge/scikit-hep

.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1043949.svg :target: https://doi.org/10.5281/zenodo.1043949

.. image:: https://github.com/scikit-hep/scikit-hep/workflows/CI/badge.svg :target: https://github.com/scikit-hep/scikit-hep/actions?query=workflow%3ACI+branch%3Amaster

.. image:: https://coveralls.io/repos/github/scikit-hep/scikit-hep/badge.svg?branch=master :target: https://coveralls.io/github/scikit-hep/scikit-hep?branch=master

Project info

The Scikit-HEP project <http://scikit-hep.org/>_ 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 <http://scikit-hep.org/get-in-touch.html>_ 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:

.. code-block:: bash

python -m pip install scikit-hep

or you can use Conda through conda-forge:

.. code-block:: bash

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.py 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:

.. code-block:: python

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

System:
    python: 3.8.6 (default, Sep 24 2020, 21:45:12)  [GCC 8.3.0]
executable: /usr/local/bin/python
   machine: Linux-4.19.104-microsoft-standard-x86_64-with-glibc2.2.5

Python dependencies:
       pip: 20.2.3
setuptools: 50.3.0
     numpy: 1.20.3
     scipy: 1.6.3
    pandas: 1.2.4
matplotlib: 3.4.2

Scikit-HEP package version and dependencies:
       awkward0: 0.15.5
        awkward: 1.2.3
boost_histogram: 1.0.2
  decaylanguage: 0.11.0
       hepstats: 0.4.0
       hepunits: 2.1.1
           hist: 2.3.0
     histoprint: 2.1.0
        iminuit: 2.6.1
         mplhep: 0.3.7
       particle: 0.15.0
          skhep: 3.2.0
         uproot: 4.0.8
        uproot3: 3.14.4
uproot3_methods: 0.10.1
         vector: 0.8.2

Note on the versioning system:

  • A version scikit-hep x.y`` is compatible with the releases of all package dependents versions a.b.cfor allc``.
  • Major version updates are prepared every time (at least) a "package component" does the same.
  • Minor version updates are the typical updates, when (at least) a package goes from version a.b to `a.(b+1).
  • Patch version updates are only done if there is some reason on the side of the metapackage itself.

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