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The biggest value prop for me is when you need something done fast that’s not already in scipy etc. In python you will need to write a C extension or fumble wit

The biggest value prop for me is when you need something done fast that’s not already in scipy etc. In python you will need to write a C extension or fumble with numba / cython / whatever, in Julia you just write it. I also think writing out math is much more concise in Julia, no more np.whatever(np.sin(x.detach()) + cos(np.sqrt(y)).mean().

usgroup 6y ago
It seems about the right time to give it a go. How is the package ecosystem in your experience? Can I expect fairly decent support for numerical optimisation stuff , graphing? Munging xml/Json/etc? Will I find that I have to write my own oauth2 client library to call API? Etc
- amkkma 6y ago
  >numerical optimisation stuff Yes, far exceeding python actually. - https://github.com/jump-dev/JuMP.jl https://github.com/jump-dev/JuMP.jl - https://github.com/JuliaNLSolvers https://github.com/JuliaNLSolvers Are just some. > graphing Excellent support. - https://github.com/JuliaPlots https://github.com/JuliaPlots - https://github.com/JuliaPlots/Makie.jl https://github.com/JuliaPlots/Makie.jl >Munging xml/Json etc - https://github.com/quinnj/JSON3.jl https://github.com/quinnj/JSON3.jl - https://github.com/JuliaData https://github.com/JuliaData - https://github.com/Algocircle/Cascadia.jl https://github.com/Algocircle/Cascadia.jl - https://github.com/queryverse/Query.jl https://github.com/queryverse/Query.jl >oauth2 etc - https://github.com/JuliaCloud https://github.com/JuliaCloud - https://github.com/JuliaWeb/HTTP.jl https://github.com/JuliaWeb/HTTP.jl for anything not available yet, you can call it from python using PyCall.jjl