uproot5 VS StaticCompiler.jl

> 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

Besides PyROOT, you can also use uproot to read ROOT files, if you want to avoid the ROOT-dependency. The current version (uproot4) does not yet support writing ROOT files, but the previous/deprecated version (uproot3) does. (Please note: uproot is not maintained by the ROOT project team).

Yes, julia can be called from other languages rather easily, Julia functions can be exposed and called with a C-like ABI [1], and then there's also various packages for languages like Python [2] or R [3] to call Julia code.

With PackageCompiler.jl [4] you can even make AOT compiled standalone binaries, though these are rather large. They've shrunk a fair amount in recent releases, but they're still a lot of low hanging fruit to make the compiled binaries smaller, and some manual work you can do like removing LLVM and filtering stdlibs when they're not needed.

Work is also happening on a more stable / mature system that acts like StaticCompiler.jl [5] except provided by the base language and people who are more experienced in the compiler (i.e. not a janky prototype)

[1] https://docs.julialang.org/en/v1/manual/embedding/

[2] https://pypi.org/project/juliacall/

[3] https://www.rdocumentation.org/packages/JuliaCall/

[4] https://github.com/JuliaLang/PackageCompiler.jl

[5] https://github.com/tshort/StaticCompiler.jl

PackageCompiler, but it' s a fat runtime and not cross compile. A thin runtime is currently not possible without sacrifices for feature as https://github.com/tshort/StaticCompiler.jl.

https://github.com/tshort/StaticCompiler.jl/issues/59 Would working on this feasible?

I just read the project's documentation at https://github.com/tshort/StaticCompiler.jl. It does produce a "hello world" application that is only 8.4k in size 👍. I do like that it can work on Mac OS. Hopefully Windows support will come soon.

See https://github.com/tshort/StaticCompiler.jl

You're probably dancing around the edges of what [PackageCompiler.jl](https://github.com/JuliaLang/PackageCompiler.jl) is capable of targeting. There are a few new capabilities coming online, namely [separating codegen from runtime](https://github.com/JuliaLang/julia/pull/41936) and [compiling small static binaries](https://github.com/tshort/StaticCompiler.jl), but you're likely to hit some snags on the bleeding edge.

using StaticCompiler # `] add https://github.com/tshort/StaticCompiler.jl` to get latest master