Best way to create a wrapper for C library for Continuous version of Tensor Train

Specific Domains Numerics
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Hello,

I would like to create a wrapper for the C library https://github.com/goroda/Compressed-Continuous-Computation that implements a low-rank approximation of multi-dimensional functions in the same spirit as ApproxFun.

Here is the arxiv paper:

Is there a Julia package to easily construct the wrapper?

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Calling C functions is relatively “easy”. See e.g.

https://docs.julialang.org/en/v1/manual/calling-c-and-fortran-code/

and some JuliaCon talks, for example Huda Nassar’s workshop from JuliaCon 2020.

If you need to generate a lot of functions that look similar, you can automate this with metaprogramming.

Of course, you can also just port the library to Julia…

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https://github.com/JuliaInterop/Clang.jl
The link is also in the documentation above ( somewhere at the end)

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Thank you @Tamas_Papp for mentioning this paper in ApproxFun for vector-valued function - #8 by Tamas_Papp.
So far I have called the Python wrapper c3py of the C library in Julia and its working well. But I want to avoid wrapper of a wrapper and I need to add a few functions.

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