Reading through the docs, looks like they have 1-indexed arrays..?
1-based indexing is a non-issue
Julia 1.0
81–90 of 446 posts
Re: Julia 1.0
#82Every release I am downloading Julia and trying to wrestle through some tutorials. Every time (0.4.0, 0.6.0, 1.0.0) I get stuck at some error, usually during the pre-compiling of some dependency.
For example, I have downloaded julia-1.0.0. I try to follow this tutorial here, linked in this post by someone: http://juliadb.org/latest/manual/tutorial.html
Then I do this and get an error:
julia> using JuliaDB [ Info: Precompiling JuliaDB [a93385a2-3734-596a-9a66-3cfbb77141e6] ERROR: LoadError: UndefVarError: start not defined Stacktrace:
Every time. Even the screenshot of Julia code that julialang.org used to have was not runnable per admission of core devs.
What am I doing wrong? How are you able to run large Julia programs successfully?
Edit:
Let's try tutorial at https://www.analyticsvidhya.com/blog/2017/10/comprehensive-t.... First command: Pkg.add("IJulia"): command fails to install dependency Conda.
Same for the tutorial at http://ucidatascienceinitiative.github.io/IntroToJulia/Html/...
Sigh. Give up
Re: Julia 1.0
#83Does it support light-weight threads (co-routines) channels yet? (and if it does, does it multiplex them on mulitple CPUs?). I had a look a few years ago, and then it did not.
I think this is so badly needed to get an easy route to pipeline paralellism, which is simply everywhere in today's data analysis "pipelines".
Re: Julia 1.0
#84I have high hopes for Julia becoming the defacto open-source scientific language. Despite Python and R both having a massive head start, I'm willing to bet that talented engineers and scientists will be drawn to Julia to implement their next-generation frameworks owing to the powerful features that it offers. For example, the fact that an array of unions such as Array{Union{Missing,T}} is represented in memory as a m…
I am a machine learning library developer and I don’t share your feelings. For example the specific example you cite, I feel, should never be something scientists or engineers actively think about, only language implementers.
Once you make that distinction, then whether you write it as a Cython module exposed in Python or you can use native language features to do it in Julia, nobody cares. It’s encapsulated away from people who use numerical libraries, as it should be.
I also spend time developing these “runtime overhead avoidant” backend numerical libraries, and I would say I’ve seen no significant reason to prefer Julia over Cython.
Don’t getme wrong, Julia is great, just not offering anything fundamentally different. And since there’s already a critical mass of people with engineering and optimization experience in the Cython & Python extension module stack, I’d expect that community to continue dominating Julia just by attrition alone.
Re: Julia 1.0
#85I 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.
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Re: Julia 1.0
#86I 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.
I do love Julia, but start up and import time can make scripting a little rough. Hopefully PackageCompiler.jl will solve that soon.
Re: Julia 1.0
#87I 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/…
Those benchmarks draw a lot of hate, because anyone coming from language X will get offended at how unoptimized code in language X is. Also true if X == Julia. For example, they never turn off boundschecks, which disables vectorization.
The point is mostly to (a) show the difference between fast languages compiled to efficient assembly and (b) represent code someone new to a language may bang out to get something done (while avoiding performance pitfalls) and avoid the benchmark game.
That said, I agree. I try (poorly) not to advertise speed, because people coming from languages like R will rarely fail to write type unstable code that is slow, observe JIT compilations that make Julia a little laggy, and then come away disappointed.
Things like the type system and meta-programming shown off in your examples are amazing, and also not something you can reproduce in other languages by adding binary dependencies.
Re: Julia 1.0
#88Earlier quoted context omitted.
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?
At Intel I developed a few product modeling tools in Julia, including one that's now used in the introduction of every new product. The only real annoyances that I ran into were related to dependency management in Pkg2, but I think Pkg3 should solve all of that. I'm quite new at Rigetti, but I would suggest keeping an eye on our GitHub page.