3 ms·

You have to use it inside a REPL, like R or Matlab. Julia using LLVM and compiling on-the-fly is not sloppy design, it's a design tradeoff (and a great one, if

You have to use it inside a REPL, like R or Matlab. Julia using LLVM and compiling on-the-fly is not sloppy design, it's a design tradeoff (and a great one, if you really need speed). Julia is not a scripting language, it's a language for mathematical analysis. Also going back to your example the solution would be to use ImageMagick.jl from Julia, and extend the library (4 extra lines with ccall) if it's not available, and send a pull request to help the community.

enriquto 8y ago
> Julia is not a scripting language, it's a language for mathematical analysis. Ok, this clarifies the matter a lot. So julia is not intended to be a general-purpose programming language. Are you involved in julia development? (Besides, I strongly dislike the design tradeoff of not being a good unix citizen.)
- agumonkey 8y ago
  Not Scripting != Not general purpose
- ddragon 8y ago
  Julia is a general-purpose programming language. The language itself is actually really good as a scripting language, including integrating well with shell, C, Fortran, R and Python, for example: https://docs.julialang.org/en/latest/manual/running-external-programs/#Pipelines-1 https://docs.julialang.org/en/latest/manual/running-external... The only trade-off here is the restricted resources the Julia devs can afford. Focusing on the scientific computation niche, the Julia compiler was built to compile code just ahead of time, since this way it can create code as fast as compiled languages while still being dynamic like any interpreted language (such as Matlab and Python). But there is nothing in the language that prevents it from being fully interpreted (and therefore having minimal compile time overhead, but generating poorly optimized code for long running processes), or alternatively pre-compiling and caching to have both (which is being worked on: https://github.com/JuliaLang/PackageCompiler.jl https://github.com/JuliaLang/PackageCompiler.jl )
- xiphias2 8y ago
  I'm not a Julia developer, but the great thing with Julia is that the libraries are exceptionally easy to read and extend, because the core developers make a strong effort to write clean code. Just look at ImageMagick.jl and you'll see, but I have the same experience with other libraries as well. Also the language itself supports extending code (multiple dispatch really helps it to stay clean).

enriquto 8y ago

> Julia is not a scripting language, it's a language for mathematical analysis. Ok, this clarifies the matter a lot. So julia is not intended to be a general-purpose programming language. Are you involved in julia development? (Besides, I strongly dislike the design tradeoff of not being a good unix citizen.)

agumonkey 8y ago
Not Scripting != Not general purpose
ddragon 8y ago
Julia is a general-purpose programming language. The language itself is actually really good as a scripting language, including integrating well with shell, C, Fortran, R and Python, for example: https://docs.julialang.org/en/latest/manual/running-external-programs/#Pipelines-1 https://docs.julialang.org/en/latest/manual/running-external... The only trade-off here is the restricted resources the Julia devs can afford. Focusing on the scientific computation niche, the Julia compiler was built to compile code just ahead of time, since this way it can create code as fast as compiled languages while still being dynamic like any interpreted language (such as Matlab and Python). But there is nothing in the language that prevents it from being fully interpreted (and therefore having minimal compile time overhead, but generating poorly optimized code for long running processes), or alternatively pre-compiling and caching to have both (which is being worked on: https://github.com/JuliaLang/PackageCompiler.jl https://github.com/JuliaLang/PackageCompiler.jl )
xiphias2 8y ago
I'm not a Julia developer, but the great thing with Julia is that the libraries are exceptionally easy to read and extend, because the core developers make a strong effort to write clean code. Just look at ImageMagick.jl and you'll see, but I have the same experience with other libraries as well. Also the language itself supports extending code (multiple dispatch really helps it to stay clean).