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Julia v1.0 has been released

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Re: Julia v1.0 has been released

#31

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Having migrated my Python+Fortran code to Julia in October last year I would say yes. For reasons why I would read the documentation basics, check the benchmarks and play with a bit of code. I was sceptical when my advisor originally suggested it but now I dread the thought of scientific software in any other language.

IMO industry will start switching once a Scikit-learn or Caret equivalent for Julia shows up. PyCall.jl and RCall.jl should take care of everything else until the rest of the ecosystem catches up.

Last time I tried to move all my stuff to Julia I ran into issues with the data frame equivalent package. It seemed the devs and community were in debate as to whether Julia and the dataframe should be more pure numerical focused a la matlab or python/pandas and appropriate for data analysis. As such null values were handled weird or not supported, which made it practically useless for all of my use cases.

I’d love to know if that was still the case though, because I’d so much rather use Julia than Python for my analysis and stuff.

Re: Julia v1.0 has been released

#32
post #23
post #15

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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.

> Julia REALLY tries to be easy for Matlab users

Not so much currently:

https://discourse.julialang.org/t/why-eye-has-been-deprecate...

Re: Julia v1.0 has been released

#33
Is Julia a decent substitute for non numerically focused tasks?

I’ve been thinking about learning a new lang recently, and while Julia does seem to be a real alternative to python for analysis, I can’t see how ergonomic it would be for simple (or convoluted, why not?) scripts.

The reverse keeps me from investing more time in Go (and Rust), though

Re: Julia v1.0 has been released

#34

Earlier quoted context omitted.

Having migrated my Python+Fortran code to Julia in October last year I would say yes. For reasons why I would read the documentation basics, check the benchmarks and play with a bit of code. I was sceptical when my advisor originally suggested it but now I dread the thought of scientific software in any other language.

IMO industry will start switching once a Scikit-learn or Caret equivalent for Julia shows up. PyCall.jl and RCall.jl should take care of everything else until the rest of the ecosystem catches up.

Not necessarily, I recommend the talk given today at JuliaCon by the head of an actuary research group at Aviva - a very large insurance company:

https://www.youtube.com/watch?v=_jx1VmWxgVY

They've been using it sucessfully for quite some time.

Re: Julia v1.0 has been released

#35
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 somethi…

If there were pandas, sklearm and Keras equivalents (don’t even need feature compleye, just mostly there) I would abandon python literally today.

Re: Julia v1.0 has been released

#36

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…

> All in all I’d prefer to do data things in Racket or another lisp

Do you have any suggestions/resources specific to this? I almost exclusively work with python but am starting to learn Racket (mostly just for fun). But if I could do some analysis in Racket, that would be awesome as well.

Re: Julia v1.0 has been released

#37

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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...

The annual juliacon is happening right now. So yes the last few weeks of this release process have been very rushed. Only around 160 packages have made releases that pass their tests using Julia 1.0.0 at the moment, out of 1900ish total registered packages.

Re: Julia v1.0 has been released

#40
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?

I thought that was what R was meant to do? But, yes, Julia was designed with something like that in mind from what I recall.

R is actually only 3 years younger than Python (25yrs and 28yrs respectively).
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