Personally, I think Python's success is down to the productivity of its peudocode-like syntax letting you hack prototypes out fast and easy. In turn, that makes building libraries more attractive, and these things build on each other. FORTRAN is very fast but it's a less forgiving syntax, especially coming from Python.
In that regard, I'm surprised Nim hasn't taken off for scientific computing. It has a similar syntax to Python with good Python iterop (eg Nimpy), but is competitive with FORTRAN in both performance and bit twiddling. I would have thought it'd be an easier move to Nim than to FORTRAN (or Rust/C/C++). Does anyone working in SciComp have any input on this - is it just a lack of exposure/PR, or something else?
In that regard, I'm surprised Nim hasn't taken off for scientific computing. It has a similar syntax to Python with good Python iterop (eg Nimpy), but is competitive with FORTRAN in both performance and bit twiddling. I would have thought it'd be an easier move to Nim than to FORTRAN (or Rust/C/C++). Does anyone working in SciComp have any input on this - is it just a lack of exposure/PR, or something else?