How to do stuff with Julia: https://rosetta.alhur.es/compare/Python/Julia/#
Julia 1.0
31–40 of 446 posts
Re: Julia 1.0
#32Module Linker, my browser extension for browsing code on GitHub, has support for Julia: https://module-linker.alhur.es/#/julia
Re: Julia 1.0
#33Wonderful! The one untold story is the more I use it the better the programmer I become. It is so easy to benchmark and profile code. It has a great community that will help you how to write high performance code. Congrats!
I really hope for Julia to become mainstream and maybe replace Python as the defacto lang for data science. Julia is an incredible language. Kudos to the team developing it.
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Re: Julia 1.0
#34I use both R and Python in my work but when we move our models to production it's not real time, just a batch execution like once in a day. I'd like to hear from anyone who uses Julia in their actual job/work. Is it worth learning Julia, hoping to use it in work some day?
I used Julia in my day-to-day work at my previous job (Intel) and in my new position (Rigetti). There's quite a few companies that are using it in production now.
Glad to hear more about how are you deploying Julia in production.
Re: Julia 1.0
#35Apart from the library ecosystem, what attracts you to Julia?
The language design. A great deal of care went into making a language that is both expressive and performant. That’s a great combo for scientific work— or any work, for that matter.
Re: Julia 1.0
#36I use both R and Python in my work but when we move our models to production it's not real time, just a batch execution like once in a day. I'd like to hear from anyone who uses Julia in their actual job/work. Is it worth learning Julia, hoping to use it in work some day?
I used Julia in my day-to-day work at my previous job (Intel) and in my new position (Rigetti). There's quite a few companies that are using it in production now.
That's really cool! I checked Rigetti's github but there seem to be no open source Julia projects there (although, somewhat surprisingly, lots of Common Lisp!). Are you free to say what Julia is being used for at Rigetti (and Intel), and whether there are any plans to release things as open source in the future?
Re: Julia 1.0
#37I use both R and Python in my work but when we move our models to production it's not real time, just a batch execution like once in a day. I'd like to hear from anyone who uses Julia in their actual job/work. Is it worth learning Julia, hoping to use it in work some day?
I've been using it in production since version 0.5. It's a joy for creating high performance numerical code without having to leave the comfort of a productive and interactive scientific computing environment. Perhaps surprisingly it's also a great glue language, where I think it does a better job of replacing shell scripts than python.
Re: Julia 1.0
#38I use both R and Python in my work but when we move our models to production it's not real time, just a batch execution like once in a day. I'd like to hear from anyone who uses Julia in their actual job/work. Is it worth learning Julia, hoping to use it in work some day?
We are using Julia to develop a clinical trial simulator for drug dosage prediction and personalized medicine applications as a joint MIT, University of Maryland Baltimore, and JuliaComputing project. It will be open sourced in January, and at the same time we will be starting a clinical trial to test the methods in a real-world setting.
Re: Julia 1.0
#39I'm a quite happy Julia user, however I feel there are still some warts in the language that should have warranted a bit more time before banging 1.0 on the badge.
Exception handling in julia is poor, which reminds me of how exceptions are (not/poorly) handled in R. Code can trap exceptions, but not directly by type as you _would_ expect. Instead, the user is left to check the type of the exception in the catch block. Aside for creating verbose blocks of boilerplate at every catch, it's very error prone.
Very few packages do it right, and like in R, exceptions either blow up in your face or they simply fail silently as the exception is handled incorrectly upstream by being too broad.
Errors, warnings and notices are also often written as if the only use-case scenario is the user watching the output interactively. Like with R, it's possible but quite cumbersome to consistently fetch the output of a julia program and be certain that "stdout" contains only what >youThat being said, I do love multiple dispatch, and julia overall has one of the most pragmatic implementations I've come across over time, which also makes me forget that I don't really like 1-based array indexes.
Re: Julia 1.0
#40I use both R and Python in my work but when we move our models to production it's not real time, just a batch execution like once in a day. I'd like to hear from anyone who uses Julia in their actual job/work. Is it worth learning Julia, hoping to use it in work some day?
I think sometimes people are distracted by Julia's performance, according to https://github.com/JuliaLang/Microbenchmarks Julia is not the fastest language/compiler (maybe LuaJIT is).
Julia is not only good for its performance, but also its multiple dispatch, its type system and more. Because of those features we have https://github.com/JuliaGPU/CUDAnative.jl, more elegant package interface, like https://github.com/JuliaOpt/JuMP.jl and there is more.
I still believe there is no silver bullet, if you want something Python then you get another Python. But think about this: is the full Python's dynamic feature really what we need in works like simulation, HPC, etc.? Probably no. I think Julia is kinda of balance for the related field (like for scientific computing). Just like in the old days, people start using FORTRAN, MATLAB, Lisp as the most advanced tools at that time. We start using Julia now.