Lecture "Introduction to the Scikit-HEP Big Data Python ecosystem for analysis in Particle Physics" for the ESCAPE Summer School on Data Science for Astronomers, Astroparticle and Particle Physics held as a virtual event on 7-18 June 2021.
A nice rendering of the notebooks can be obtained with nbviewer at https://nbviewer.jupyter.org/github/eduardo-rodrigues/2021-06-14_ESCAPESummerSchool/tree/master/.
| The School is organized in the framework and with the support of the European Science Cluster of Astronomy & Particle physics ESFRI research infrastructures (ESCAPE), funded by the European Union's Horizon 2020 - Grant N. 824064. |
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Data analysis in High Energy Physics (HEP) has evolved considerably in recent years. In particular, the role of Python has gained much momentum, sharing at present the show with C++ as a language of choice. Several (community) domain-specific projects have seen the day, providing (HEP) data analysis packages that profit from, and talk to well with, the huge Python scientific ecosystem, which navigates around NumPy and friends. This lecture introduces the Scikit-HEP project, which I started in late 2016 with a few colleagues from various backgrounds and domains of expertise. Scikit-HEP is a community-driven and community-oriented project with the aim of providing Particle Physics at large with a Big Data ecosystem for analysis in Python. It has developed considerably in the past couple of years, and is now part of the official software stack of the experiments ATLAS, Belle II, CMS and KM3NeT. In this lecture ample time will be provided to "play around" with the material, in Jupyter notebooks.
One can straightforwardly run this notebook presentation on Binder, with no installation requirements on the user side (Be aware that the environment to set up is relatively large and it may take about 5 minutes for the notebooks to be up and running online.)
Just click on
Anything can be altered along the way.
Note that the notebooks use Python 3, though most (but not all!) packages also support Python 2 for now.
Alternatively, you may want to download the repository and play with the notebooks, saving for example some of the plots they produce.
git clone https://github.com/eduardo-rodrigues/2021-06-14_ESCAPESummerSchool.git
cd 2021-06-14_ESCAPESummerSchool