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RCall.jl | jlrs | |
---|---|---|
8 | 9 | |
311 | 393 | |
1.3% | - | |
5.5 | 8.1 | |
21 days ago | 5 months ago | |
Julia | Rust | |
GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
RCall.jl
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Makie, a modern and fast plotting library for Julia
I don't use it personally, but RCall.jl[1] is the main R interop package in Julia. You could call libraries that have no equivalent in Julia using that and write your own analyses in Julia instead.
[1] https://github.com/JuliaInterop/RCall.jl
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Making Python 100x faster with less than 100 lines of Rust
You can have your cake and eat it with the likes of
* PythonCall.jl - https://github.com/cjdoris/PythonCall.jl
* NodeCall.jl - https://github.com/sunoru/NodeCall.j
* RCall.jl - https://github.com/JuliaInterop/RCall.jl
I tend to use Julia for most things and then just dip into another language’s ecosystem if I can’t find something to do the job and it’s too complex to build myself
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Interoperability in Julia
To inter-operate Julia with the R language, the RCall package is used. Run the following commands on the Julia REPL
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Convert Random Forest from Julia to R
https://github.com/JuliaInterop/RCall.jl may help
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I'm considering Rust, Go, or Julia for my next language and I'd like to hear your thoughts on these
If you need to bindings to your existing R packages then Julia is the way. Check out RCall.jl
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translate R code to Julia code
I have no experience with R, but maybe this will be of use: https://github.com/JuliaInterop/RCall.jl
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Julia 1.6: what has changed since Julia 1.0?
You can use RCall to use R from Julia: https://github.com/JuliaInterop/RCall.jl
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Julia Update: Adoption Keeps Climbing; Is It a Python Challenger?
I worked with R and Python during the last 3 years but learning and dabbling with Julia since 0.6. Since the availability of [PyCall.jl] and [RCall.jl], the transition to Julia can already be easier for Python/R users.
I agree that most of the time data wrangling is super confortable in R due to the syntax flexibility exploited by the big packages (tidyverse/data.table/etc). At the same time, Julia and R share a bigger heritage from Lisp influence that with Python, because R is also a Lisp-ish language (see [Advanced R, Metaprogramming]). My main grip from the R ecosystem is not that most of the perfomance sensitive packages are written in C/C++/Fortran but are written so deeply interconnect with the R environment that porting them to Julia that provide also an easy and good interface to C/C++/Fortran (and more see [Julia Interop] repo) seems impossible for some of them.
I also think that Julia reach to broader scientific programming public than R, where it overlaps with Python sometimes but provides the Matlab/Octave public with an better alternative. I don't expected to see all the habits from those communities merge into Julia ecosystem. On the other side, I think that Julia bigger reach will avoid to fall into the "base" vs "tidyverse" vs "something else in-between" that R is now.
[PyCall.jl]: https://github.com/JuliaPy/PyCall.jl
[RCall.jl]: https://github.com/JuliaInterop/RCall.jl
[Julia Interop]: https://github.com/JuliaInterop
[Advanced R, Metaprogramming] by Hadley Wickham: https://adv-r.hadley.nz/metaprogramming.html
jlrs
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Question: How well-suited is using Rust for complicated mathematics?
And in the rare case that Julia isn't enough, Julia-Rust interop is pretty good! Julia can call Rust using ccall and Rust can call Julia using the jlrs crate.
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jlrs 0.17: GAT-powered generic targets, Julia 1.9 support, build improvements, and more!
Github
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Julia is missing 'pycall' for Rust
While there is Jlrs , there is no seamless and easy way to call Rust. We need 'rustcall' on a level of 'pycall'.
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What's everyone working on this week (43/2022)?
I have a roadmap issue with some ideas/designs/arguments https://github.com/Taaitaaiger/jlrs/issues/66
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I don't want to abandon Rust for Julia
An option for Julia/Rust interop is jlrs
- How to interact Julia and Rust?
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I'm considering Rust, Go, or Julia for my next language and I'd like to hear your thoughts on these
jlrs automates some of this, using stack frames to garantee that Julia won't gc the references you're holding in Rust. It also provides ways to coerce Rust structs into Julia structs, and it does a bunch of other stuff I'm probably forgetting.
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jlrs 0.9: Julia 1.6 support
Github
What are some alternatives?
Makie.jl - Interactive data visualizations and plotting in Julia
DaemonMode.jl - Client-Daemon workflow to run faster scripts in Julia
org-mode - This is a MIRROR only, do not send PR.
ModelingToolkit.jl - An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Chain.jl - A Julia package for piping a value through a series of transformation expressions using a more convenient syntax than Julia's native piping functionality.
PackageCompiler.jl - Compile your Julia Package
Revise.jl - Automatically update function definitions in a running Julia session
juliaup - Julia installer and version multiplexer
cmssw - CMS Offline Software
AreWeRustYet - Awesome list of "Are We *thing* Yet" for Rust
PyCall.jl - Package to call Python functions from the Julia language
enso - Hybrid visual and textual functional programming.