Earlier quoted context omitted.
Hehehe oh yeah, I almost forget about that because I stopped years ago bothering to actually make the tools into separate files that I start from the shell. It is more like Julia is my shell. I'll just have packages with common tools I use and launch them by calling functions from the REPL. I'll just have packages for doing doing image file conversions in batch, modifying source code, changing configuration files etc…
Aren't many bash programs written in C? So this is implying Julia is somehow faster than C? Obviously that can't quite be true, but I can definitely imagine that the algorithms implemented in Julia could be fast faster than other algorithms - since the community has such a heavy influence of very hardcore mathematicians that have a string stress towards speed. Probably most of the algorithms in Julia are state of the…
High level functional style code with things like map and filter can frequently be JIT compiled to optimal machine code.
Fortran is considered faster for numerical code than C and well polished Fortran libraries like BLAS is already getting outperformed by Julia.
For typical systems programming with need to tight control of memory and real time system C will still have the edge. But for anything crunching lots of numbers like data analysis or machine learning Julia will likely outperform everybody else.