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
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

Documentation:

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

Downloads:

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

Linking:

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