A simple standalone system for exporting c++ functions so that they can be called from Julia. Does NOT require the Julia SDK.
The main reason I wrote this was to be able to test c++ code in an interactive notebook-type interface combined with lots of visualization capabilities.
These standalone files implement a simple system for exporting functions from c++ so that they can be called from Julia. It includes an interactive load/unload ability so that you can recompile your code and load new versions while debugging.
NOTE that only very basic functionality is provided. In particular not many argument types are supported. This is easily fixable. Even in this primitive state I was easily able to accomplish what I wanted - the ability to interactively produce a 3d realtime VR visualization of data manipulated inside of an interactive notebook.
This code should build fine on any system. There are no dependencies and no Julia SDK is needed. A trivial CMake file is provided but if you're not using Cmake, all you have to do is link the 2 .cpp files into a loadable .dll/.so file.
No add-on packages for Julia are necessary to use this. Install Julia from https://julialang.org/downloads/.
You can run the included test.jl by typing "julia test.jl" after building the dll. You might need to edit the path string in that file depending on where you built it to.
You will first include "importcpp.jl" in your julia session. After that you can use ImportCPP( "path/to/dll_name" ). Note that you should leave off the .so or .dll extension. When you load the dll it will tell you what to type to unload it. If you call an exported function that has been unloaded, you will get an error.
ImportCpp works by loading a symbol table of exported functions and parameter types from the dll. It then uses Julia's ability to construct and compile code at run time to build an AST tree defining the function binding, and then compiles it to native code. I'd never written this kind of code in Julia or for that matter much of any Julia code. I'm sure it could be a lot better but it didn't take long to write, it works, and yer gets what yer pay for :-).
These screenshots are me graphing a c++ implementation of "A Convenient Generalization of Schlick’s Bias and Gain Functions" (https://arxiv.org/pdf/2010.09714.pdf) inside of Jupyterlab. To bring up a Julia jupyter notebook session in your browser, install the Julia package IJulia using the built in package manager. Then type "using IJulia; jupyterlab()" at the julia> prompt and a web interface will come up. It may take a little bit of time to start up the first time as it compiles the code.
C++ code in Emacs
Plotting the c++ function interactively