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Julia v1.0 has been released

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Re: Julia v1.0 has been released

#21

Post by sgillen »

sleavey wrote: post #9

Having never used it, I wonder, could Julia replace Python as the de-facto standard in scientific computing and data analysis? What does it do well?

Python has so much inertia at this point that it seems unlikely to happen in the near future.

Probably not quite to the scale as C/C++ vs rust for systems programming, but a similar idea. Rust has all these great features but most people doing systems know C, all their code is already in C, and so the cost of switching is very high.

Not that a switch will never happen, it's just that no matter how good Julia is any transition is going to take a long time. (I do think Julia is a good language though)

Re: Julia v1.0 has been released

#22

Post by peatmoss »

In the past when I’ve poked around with Julia, I used Emacs Speaks Statistics. If you’re familiar with using R in this context, you’ll probably find developing and interacting with Julia to be quite easy.

If the Julia community could manage to get Julia support into RStudio, I think we’d see a more accelerated uptake. I’ve heard rumblings that RStudio has at least thought of supporting Python in RStudio (more than they do now with R Notebooks). I can’t help thinking that if RStudio were to add support for an additional language, that Julia might be a good choice.

All in all I’d prefer to do data things in Racket or another lisp, but Julia feels good. I could see both the Python and R communities being tempted. Here’s hoping!

Re: Julia v1.0 has been released

#23

Post by cultus »

collinf wrote: post #15
sleavey wrote: post #9

Having never used it, I wonder, could Julia replace Python as the de-facto standard in scientific computing and data analysis? What does it do well?

My only fleeting experience with Julia is in a Numerical Analysis Course three years ago... but it has 1-indexed arrays so its good for scaring away all people who are programmers before analysts/scientists! Really though, I think it has a better type system and a syntax that translates easier to mathematical expressions. Other than that, Python's breadth of packages will be hard to overcome.

You get used to the 1-based indexing pretty quick. It's a non-issue. 1-based indexing is the standard in math, and also Matlab and Fortran. For the primary use-case of Julia, it makes sense. Julia REALLY tries to be easy for Matlab users, who still dwarf Python users in science.

Re: Julia v1.0 has been released

#24

Post by tmalsburg2 »

sleavey wrote: post #9

Having never used it, I wonder, could Julia replace Python as the de-facto standard in scientific computing and data analysis? What does it do well?

Python is not the de-facto standard to my knowledge. It really depends on the field and task. R is huge in my research area, MatLab is king in some other areas, and Fortran is still being used for large-scale number crunching. Will Julia replace all these? That's the ambition but I doubt it's going to happen. For instance, R has a unique and vast ecosystem of extension packages. It would take decades to build something comparable in Julia.

Re: Julia v1.0 has been released

#26

Post by chriselrod »

collinf wrote: post #15
sleavey wrote: post #9

Having never used it, I wonder, could Julia replace Python as the de-facto standard in scientific computing and data analysis? What does it do well?

My only fleeting experience with Julia is in a Numerical Analysis Course three years ago... but it has 1-indexed arrays so its good for scaring away all people who are programmers before analysts/scientists! Really though, I think it has a better type system and a syntax that translates easier to mathematical expressions. Other than that, Python's breadth of packages will be hard to overcome.

I know it is not the default, but this package has no overhead over the default arrays according to recent benchmarks, and provides 0-indexed arrays: https://github.com/JuliaArrays/OffsetArrays.jl

I confess, not being the default is a big thing. I've definitely had times where I thought "this would be easier with 0 indexed arrays", but it can then be harder to commit to adding a dependency and making that change vs just adding awkward looking "+1"s to all the indexes. Coming from math/science, there's lots of times 1-indexing makes more sense / is more familiar. It's normal there to start counting from 1, so it can be easier to translate.

Re: Julia v1.0 has been released

#27

Post by sundarurfriend »

stellalo wrote: post #19
sundarurfriend wrote: post #11

Edit: It has happened! Relevant pull request: https://github.com/JuliaLang/julia/pull/28521 Video from Juliacon: https://youtu.be/1jN5wKvN-Uk?t=1h18s --- ~~Note that this is the first release candidate version[1]:~~ > As a prerelease, 1.0-rc1 should not be considered production-ready. It’s intended to give developers a chance to get ready for the release of 1.0 by trying it out and testing for issues. Most users shou…

It looks like this HN entry, however, refers to the stable 1.0 release

It's pretty weird, I'd assume it was a mistaken tagging except that the commit [1] is very clear in its intent. I still don't think they'd suddenly have decided to rush through it all and release 1.0 like this, so I'm still assuming there's a mistake or misunderstanding here.

[1] https://github.com/JuliaLang/julia/commit/5d4eaca0c9fa3d555c...

Re: Julia v1.0 has been released

#29

Post by jjoonathan »

peatmoss wrote: post #22

In the past when I’ve poked around with Julia, I used Emacs Speaks Statistics. If you’re familiar with using R in this context, you’ll probably find developing and interacting with Julia to be quite easy. If the Julia community could manage to get Julia support into RStudio, I think we’d see a more accelerated uptake. I’ve heard rumblings that RStudio has at least thought of supporting Python in RStudio (more than th…

What parts of RStudio do you prefer over Jupyter?
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