CERN Root

• uproot5

  4 233 8.9 Python

  ROOT I/O in pure Python and NumPy.

  

  There is no many reasons why new analyses should default to using ROOT instead of more user friendly and sane options like uproot [1]. Maybe some people have some legacy workflow or their experiments have many custom patches on top of ROOT (common practice) for other things but for physics analysis you might be self torturing yourself.

  Also I really like their 404 page [2]. And no it is not about room 404 :)

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

  [2] https://root.cern/404/

• SaaSHub

  www.saashub.com featured

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

  

• taichi

  39 25,412 8.2 C++

  Productive, portable, and performant GPU programming in Python.

  

  The haughtiness is not for nothing. Since Dec 2023, they made a lame excuse that Pytorch didn't support 3.12: https://github.com/taichi-dev/taichi/issues/8365#issuecommen...

  Later, even when Pytorch added support for 3.12, nothing changed (so far) in Taichi.

• jank

  31 1,595 9.5 C++

  A Clojure dialect hosted on LLVM with native C++ interop

  

  I definitely asked for it. I'm using Cling for JIT compiling my native Clojure dialect: https://github.com/jank-lang/jank

  Without Cling, this sort of thing wouldn't be feasible in C++. Not in the way which Clojure dialects work. The runtime is a library and the generated code is just using that library.

• root

  33 2,641 10.0 C++

  The official repository for ROOT: analyzing, storing and visualizing big data, scientifically

  

• UnROOT.jl

  1 99 8.3 Julia

  Native Julia I/O package to work with CERN ROOT files objects (TTree and RNTuple)

  

  One common criticism of uproot is that it's not flexible when per-row computation gets complicated because for-loops in Python is too slow. For that one can either use Numba (when it works), or, here's the shameless plug, use Julia: https://github.com/JuliaHEP/UnROOT.jl

• UnROOT_RDataFrame_MiniBenchmark

  1 3 5.2 C++

  both things you mentioned are different ways of saying "one-vector-at-a-time" style programming. The irreducible complexity of data analysis is there no matter how you do it, and "one-vector-at-a-time" sometimes feel like shoehorning (other terms people come up with include vector-style mental gymnastics).

  Just a recent example, a double-for loop looks like this in Awkward array: https://github.com/Moelf/UnROOT_RDataFrame_MiniBenchmark/blo...

• hep

  7 231 7.5 Go

  hep is the mono repository holding all of go-hep.org/x/hep packages and tools

  

  that's odd. TEfficiency is a relatively simple thing to read/write :

  - https://github.com/go-hep/hep/blob/main/groot/rhist/efficien...

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