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└ (y/n) [y]:
Surprised it defaults to [y] option, especially since packages can be pretty heavy with artifacts and lots of dependencies to precompile. One accidental extra Return and you might be sitting there for five minutes.
> keepat!(v, i)
Not a fan of the name. The ! indicates the mutation as the article points out, but keeponlyat! would have been much clearer and immediately obvious, and more than justifies its length IMO.
Lots of nice quality of life improvements in this version. One that the article doesn't mention is `julia --project=@myenv` [1] - being able to specify a shared environment as the starting environment for the REPL.
[1] https://github.com/JuliaLang/julia/blob/v1.7.0-rc1/NEWS.md
Contrary to some folks here I've had a pretty good experience learning Julia while adding support for it as an scripting language in an open-source data IDE I'm building [0].
It makes a lot more sense as a language to me than R (which is also a supported scripting language), but I'm slowly coming around to R too.
It's also neat that all hosted Github Actions images come with Julia built in so it's pretty easy to be working with it in automated environments as well.
Exactly. We are training a very large neural model using [1]. We would not fix much if we decided to embed the Julia code inside a CPython wrapper or something...