SELF VS FLAP

Could you go into more detail? If you're referring to https://github.com/FluidNumerics/SELF, I've just taken a look and it does seem like their documentation on how to build is lacking. Usually if that's the case, you can dig for whatever their CI configuration is and manually follow those steps, but it's not clear here: they have a mechanism to build Singularity containers (ci/run_tests) but everything else in ci seems unrelated. Their CONTRIBUTING.md is out of date and incomplete, and as you've already seen their build system (Makefile, install.sh, test.sh) is a total mess. Pretty much all modern scientific codes are using at least CMake now. (It's either that or hacked-up and hardcoded recursive make, rather than autoconf.)

You can freely download SELF source code online at https://github.com/fluidnumerics/self

SELF Github Repository : https://github.com/fluidnumerics/self

I'm definitely a fan of Fortran for writing CFD and numerical PDE solvers (https://github.com/FluidNumerics/SELF) in general. Fortran was my first programming language, and I'm not a "geezer geek" (I'm 30 years old). While I also program in C and C++ on some projects, Fortran is my go-to. As others have already mentioned, the array syntax in Fortran is fantastic. It really helps to be able to work out algorithms on paper and translate cleanly into multi-dimensional arrays.

is not powerful enough, FLAP is one (not the only, see some compiled in fortranwiki) equivalent to argparse (in Python) for Fortran. You then enter a workflow to compile modules, later the main program, and eventually join the object files into an executable. Manually for example with gfortran as compiler, this is in line of

We'll be building out more of the command line interface using the Fortran command Line Argument Parser for poor people (FLAP; https://github.com/szaghi/FLAP) to add triggers for executing convergence tests. In the process, we'll also be doing some tecplot output visualization with Paraview