I can understand legacy libraries. I cannot understand new projects and mission criticle systems.
For Fortran's use case you want to turn math into running code and all this C /C++ OOP stuff gets in way.
Also any language that doesn't have arrays built in is not going to get the time of day from a technical programmer.
You want the maximum performance out of your code so Python might be good for prototyping but you want to convert that to the fastest code in production.
Turning math into code is just as easy in both languages. The only addition that is different is adding types is mandatory in C++. You'd see more "float" or "long double"s in C/C++ code. No other difference.
> Also any language that doesn't have arrays built in is not going to get the time of day from a technical programmer.
Julia and Python have arrays built in, C++ has an array type, and C/C++ have pointers.
> You want the maximum performance out of your code so Python might be good for prototyping but you want to convert that to the fastest code in production.
With very little work you can turn prototype python code into production code with Cython. C speeds with python orchestration.
This leaves out the other languages on the block like Haskell and D which are better suited for other tasks.
I did have a quick hours training on how to operate the PDP 11 though.