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I'd love to know from any resident Julia experts: what are your favorite examples of active, high-quality Julia packages? And perhaps more importantly, what is

I'd love to know from any resident Julia experts: what are your favorite examples of active, high-quality Julia packages? And perhaps more importantly, what is missing?

ChrisRackauckas 8y ago
This is my summary: https://discourse.julialang.org/t/what-package-s-are-state-of-the-art-or-attract-you-to-julia-and-make-you-stay-there-not-easily-replicateable-in-e-g-python-r-matlab/11294/4 https://discourse.julialang.org/t/what-package-s-are-state-o...
babahoyo 8y ago
If you are coming from R I would say that DataFrames and DataFramesMeta are just as good as dplyr. But thats just a super small, less scientific, corner of the entire excellent ecosystem
rrock 8y ago
For me, Images.jl. The design is just great, and a lot of work (mostly from Tim Holy at WUSTL) went into the array handling code of base Julia and of Images.jl to make it all fast and easy to use. I'll give you one quick example of the design. Images are just arrays of "Colors". The upside is that you can write generic code that handles arrays of Colors of any kind, meaning you don't have to worry about iterating over the color axis. You also don't have to worry about whether your 100x100x3 array is three images (at different times or locations) or one image with three RGB channels. All of this comes at little to no cost in terms of speed. Check the docs here: http://juliaimages.github.io/latest/ http://juliaimages.github.io/latest/ But fair warning, it still needs some fixes for 0.7/1.0. We're on it!
eigenspace 8y ago
The thread Chris linked to has some great discussion on the state of the art packages. With respect to your question about what’s missing: Coming from Python, I think one might be surprised by how much less one feels the need to rely on packages in Julia. The language has some very powerful abstractions that really makes one rely less on packages than you’d expect. Julia has really inhereted a lot of great lessons from Lisp and that’s made the language an absolute treat for ‘rolling your own’. Meanwhile, some lessons from more modern languages have also made Julia much more effective at sharing your abstractions with others much easier and effective than any Lisp I’ve ever seen.

I'd love to know from any resident Julia experts: what are your favorite examples of active, high-quality Julia packages? And perhaps more importantly, what is missing?

ChrisRackauckas 8y ago

This is my summary: https://discourse.julialang.org/t/what-package-s-are-state-of-the-art-or-attract-you-to-julia-and-make-you-stay-there-not-easily-replicateable-in-e-g-python-r-matlab/11294/4 https://discourse.julialang.org/t/what-package-s-are-state-o...

babahoyo 8y ago

If you are coming from R I would say that DataFrames and DataFramesMeta are just as good as dplyr. But thats just a super small, less scientific, corner of the entire excellent ecosystem

rrock 8y ago

For me, Images.jl. The design is just great, and a lot of work (mostly from Tim Holy at WUSTL) went into the array handling code of base Julia and of Images.jl to make it all fast and easy to use. I'll give you one quick example of the design. Images are just arrays of "Colors". The upside is that you can write generic code that handles arrays of Colors of any kind, meaning you don't have to worry about iterating over the color axis. You also don't have to worry about whether your 100x100x3 array is three images (at different times or locations) or one image with three RGB channels. All of this comes at little to no cost in terms of speed. Check the docs here: http://juliaimages.github.io/latest/ http://juliaimages.github.io/latest/ But fair warning, it still needs some fixes for 0.7/1.0. We're on it!

eigenspace 8y ago

The thread Chris linked to has some great discussion on the state of the art packages. With respect to your question about what’s missing: Coming from Python, I think one might be surprised by how much less one feels the need to rely on packages in Julia. The language has some very powerful abstractions that really makes one rely less on packages than you’d expect. Julia has really inhereted a lot of great lessons from Lisp and that’s made the language an absolute treat for ‘rolling your own’. Meanwhile, some lessons from more modern languages have also made Julia much more effective at sharing your abstractions with others much easier and effective than any Lisp I’ve ever seen.