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JuliaCall: Seamless Integration Between R and 'Julia'

Provides an R interface to 'Julia', which is a high-level, high-performance dynamic programming language for numerical computing, see <https://julialang.org/> for more information. It provides a high-level interface as well as a low-level interface. Using the high level interface, you could call any 'Julia' function just like any R function with automatic type conversion. Using the low level interface, you could deal with C-level SEXP directly while enjoying the convenience of using a high-level programming language like 'Julia'.

Version: 0.17.6
Depends: R (≥ 3.4.0)
Imports: utils, Rcpp (≥ 0.12.7), knitr (≥ 1.28), rjson
LinkingTo: Rcpp
Suggests: testthat, rmarkdown, rappdirs, sass
Published: 2024-12-07
DOI: 10.32614/CRAN.package.JuliaCall
Author: Changcheng Li [aut, cre], Christopher Rackauckas [ctb], Randy Lai [ctb], Dmitri Grominski [ctb], Nagi Teramo [ctb]
Maintainer: Changcheng Li <cxl508 at psu.edu>
BugReports: https://github.com/JuliaInterop/JuliaCall/issues
License: MIT + file LICENSE
URL: https://github.com/JuliaInterop/JuliaCall
NeedsCompilation: yes
SystemRequirements: Julia >= 1.0.0, RCall.jl
Citation: JuliaCall citation info
Materials: README NEWS
In views: NumericalMathematics
CRAN checks: JuliaCall results

Documentation:

Reference manual: JuliaCall.pdf
Vignettes: JuliaCall in Jupyter R Notebook (source, R code)
Julia in RMarkdown (source, R code)

Downloads:

Package source: JuliaCall_0.17.6.tar.gz
Windows binaries: r-devel: JuliaCall_0.17.6.zip, r-release: JuliaCall_0.17.6.zip, r-oldrel: JuliaCall_0.17.6.zip
macOS binaries: r-release (arm64): JuliaCall_0.17.6.tgz, r-oldrel (arm64): JuliaCall_0.17.6.tgz, r-release (x86_64): JuliaCall_0.17.6.tgz, r-oldrel (x86_64): JuliaCall_0.17.6.tgz
Old sources: JuliaCall archive

Reverse dependencies:

Reverse imports: BayesFluxR, bigsimr, diffeqr, iai, RTIGER, sMTL
Reverse suggests: knitr

Linking:

Please use the canonical form https://CRAN.R-project.org/package=JuliaCall to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.