scikit-hep / Scikit Hep
Programming Languages
Projects that are alternatives of or similar to Scikit Hep
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: 21.0.1
setuptools: 54.1.2
numpy: 1.20.1
scipy: 1.6.1
pandas: 1.2.3
matplotlib: 3.3.4
Scikit-HEP package version and dependencies:
awkward0: 0.15.5
awkward: 1.1.2
boost_histogram: 1.0.0
decaylanguage: 0.10.2
hepstats: 0.3.1
hepunits: 2.1.0
hist: 2.2.0
histoprint: 2.0.0
iminuit: 2.4.0+ROOT-v6-23-01-RF-binSampling-685-ga642cc22e3
mplhep: 0.2.17
particle: 0.14.0
skhep: 3.0.0
uproot3_methods: 0.10.0
uproot3: 3.14.4
uproot: 4.0.6
Note on the versioning system:
- A version
scikit-hep x.y`` is compatible with the releases of all package dependents versions
a.b.cfor all
c``. - Major version updates are prepared every time (at least) a "package component" does the same.
- Typical updates go with a minor version, so when (at least) a package goes from version
a.b
to ```x.(y+1)``. - Patch version updates are only done if there is some reason on the side of the metapackage itself.