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: 0.17.5
Depends: R (≥ 3.4.0)
Imports: utils, Rcpp (≥ 0.12.7), knitr (≥ 1.28), rjson
LinkingTo: Rcpp
Suggests: testthat, rmarkdown, rappdirs, sass
Published: 2022-09-08
DOI: 10.32614/CRAN.package.JuliaCall
Author: Changcheng Li [aut, cre], Randy Lai [ctb], Dmitri Grominski [ctb], Nagi Teramo [ctb]
Maintainer: Changcheng Li <cxl508 at psu.edu>
BugReports: https://github.com/Non-Contradiction/JuliaCall/issues
License: MIT + file LICENSE
URL: https://github.com/Non-Contradiction/JuliaCall
NeedsCompilation: yes
SystemRequirements: Julia >= 0.6.0, RCall.jl
Citation: JuliaCall citation info
Materials: README NEWS
In views: NumericalMathematics
CRAN checks: JuliaCall results


Reference manual: JuliaCall.pdf
Vignettes: JuliaCall in Jupyter R Notebook
Julia in RMarkdown


Package source: JuliaCall_0.17.5.tar.gz
Windows binaries: r-devel: JuliaCall_0.17.5.zip, r-release: JuliaCall_0.17.5.zip, r-oldrel: JuliaCall_0.17.5.zip
macOS binaries: r-release (arm64): JuliaCall_0.17.5.tgz, r-oldrel (arm64): JuliaCall_0.17.5.tgz, r-release (x86_64): JuliaCall_0.17.5.tgz, r-oldrel (x86_64): JuliaCall_0.17.5.tgz
Old sources: JuliaCall archive

Reverse dependencies:

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


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