Python scikit-hep

Open-source Python projects categorized as scikit-hep

Top 7 Python scikit-hep Projects

  • awkward

    Manipulate JSON-like data with NumPy-like idioms.

  • Project mention: Efficient Jagged Arrays | news.ycombinator.com | 2023-07-03

    there's a whole ecosystem in Python originally developed for high energy physics data processing: https://github.com/scikit-hep/awkward all because Numpy demands square N-dimensional array

    Same technique used everywhere, here's a simple Julia pkg for the same thing: https://github.com/JuliaArrays/ArraysOfArrays.jl/blob/3a6f5b...

    But Julia at least has the decency to just support ragged Vector{Vector} out of the box, and it's not that slow

  • iminuit

    Jupyter-friendly Python interface for C++ MINUIT2

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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  • pyhf

    pure-Python HistFactory implementation with tensors and autodiff

  • uproot5

    ROOT I/O in pure Python and NumPy.

  • Project mention: Potential of the Julia programming language for high energy physics computing | news.ycombinator.com | 2023-12-04

    > I wasn't proposing ROOT to be reimplemented in JS. That was what the GP attributed to me.

    Sorry for assuming that. I really felt the pain of thinking of possibility of combining two things I hate so much together (JS+ROOT)

    > "Laypeople" may also think that code is optimized to the last cycle in something like HEP simulations. It's made fast enough and the optimization is nowhere near the level of e.g. graphics heavy games.

    I understand that in other areas there might be more sophisticated optimizations, but does not change things much inside HEP field community. And it is not optimized only for simulations but for other things too. It is not one problem optimization.

    > Real-time usage like high frequency large data collection will probably never happen on the "single language". But I'd guess ROOT is not used at that level either? Also at least last time I checked, ROOT is moving to Python (probably not for the hottest loops of the simulation though).

    I did not mean to indicate that ROOT is being used to handle the online processing (In HEP terms). It is usually handled via optimized C++ compiled code. My idea is that you will probably never use JS or any interpreted language (or anything other than C++ to be pessimistic) for that. ROOT at the end of the day is much closer to C++ than anything else. So learning curve wouldn't be that much if you come with some C++ knowledge initially.

    > Also at least last time I checked, ROOT is moving to Python (probably not for the hottest loops of the simulation though).

    I think you mean PyROOT [1]? This is the official python ROOT interface It provides a set of Python bindings to the ROOT C++ libraries, allowing Python scripts to interact directly with ROOT classes and methods as if they were native Python. But that does not represent and re-writing. It makes things easier for end users who are doing analysis though, while be efficient in terms of performance, especially for operations that are heavily optimized in ROOT.

    There is also uproot [2] which is a purely Python-based reader and writer of ROOT files. It is not a part of the official ROOT project and does not depend on the ROOT libraries. Instead, uproot re-implements the I/O functionalities of ROOT in Python. However, it does not provide an interface to the full range of ROOT functionalities. It is particularly useful for integrating ROOT data into a Python-based data analysis pipeline, where libraries like NumPy, SciPy, Matplotlib, and Pandas ..etc are used.

    > Off-topic: C++ interpretation like done in ROOT seems like a really bad idea.)

    I will agree with you. But to be fair the purpose of ROOT is interactive data analysis but over the decades a lot of things gets added, and many experiments had their own soft forks and things started to get very messy quickly. So that there is no much inertia to fix problems and introduce improvements.

    [1] https://root.cern/manual/python/

    [2] https://github.com/scikit-hep/uproot5

  • particle

    Package to deal with particles, the PDG particle data table, PDGIDs, etc. (by scikit-hep)

  • hist

    Histogramming for analysis powered by boost-histogram

  • uproot-browser

    A TUI viewer for ROOT files

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

Python scikit-hep related posts

  • Histogramming libraries for Python updated (boost-histogram / Hist)

    2 projects | /r/Python | 21 Sep 2021

Index

What are some of the best open-source scikit-hep projects in Python? This list will help you:

Project Stars
1 awkward 793
2 iminuit 273
3 pyhf 271
4 uproot5 218
5 particle 144
6 hist 122
7 uproot-browser 70

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