RCall.jl
AreWeRustYet
Our great sponsors
RCall.jl | AreWeRustYet | |
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8 | 8 | |
310 | 485 | |
1.0% | - | |
5.5 | 3.8 | |
15 days ago | 7 months ago | |
Julia | ||
GNU General Public License v3.0 or later | Creative Commons Zero v1.0 Universal |
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.
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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
AreWeRustYet
- Rust – Are We Game Yet?
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"Surpassing" Go & the near-future of Rust: in what domains will Rust succeed?
This is fascinating to me. It's my understanding that Rust is generally a system programming language, whereas Go is general-purpose... and what's more, it's up against the likes of C. But in spite of this, Rust is very clearly establishing a presence in most mainstream domains.
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Expanded standard/promoted libraries?
Btw i use any of many areweyet projects to figure out the most popular crate by github repo stars.
- AreWeRustYet – a list of Are We THING Yet sites
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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
For more info about how stable things are: https://github.com/UgurcanAkkok/AreWeRustYet
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Maybe We Can Have Nice Things
There are compilations of these websites like https://github.com/UgurcanAkkok/AreWeRustYet And I'm sure there are others.
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Looking for advice on Path to Rust Developer Job
Depending on your favorite area (gaming, web, ML/AI, backend, etc) perhaps take a look at this list of sites https://github.com/UgurcanAkkok/AreWeRustYet and pick some. Get familiar with your favorite projects, contribute, and build a code portfolio.
What are some alternatives?
Makie.jl - Interactive data visualizations and plotting in Julia
cargo-supply-chain - Gather author, contributor and publisher data on crates in your dependency graph.
org-mode - This is a MIRROR only, do not send PR.
cxx - Safe interop between Rust and C++
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.
rustc-perf - Website for graphing performance of rustc
PyCall.jl - Package to call Python functions from the Julia language
enso - Hybrid visual and textual functional programming.
Revise.jl - Automatically update function definitions in a running Julia session
jlrs - Julia bindings for Rust
cmssw - CMS Offline Software
cargo-crev - A cryptographically verifiable code review system for the cargo (Rust) package manager.