An R package that provides a bidirectional interface for calling Julia code from R and mapping objects between both languages.
rjulia is an R package that provides an interface between R and Julia programming languages. It enables R users to execute Julia code from within R sessions and seamlessly transfer data objects between the two environments, allowing them to combine R's statistical ecosystem with Julia's performance advantages.
Data scientists and researchers who primarily work in R but want to leverage Julia's computational speed for specific tasks, or developers maintaining codebases that span both R and Julia ecosystems.
It offers a straightforward way to integrate Julia's high-performance computing capabilities into R workflows without requiring users to completely switch ecosystems, providing the best of both languages for statistical and scientific computing.
R package which integrating R and Julia
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Allows running Julia scripts from R and transferring data, as shown with functions like `julia_eval('1+1')` in the simple example.
Handles data frames, factors, and NA values by requiring Julia packages DataArrays and DataFrames, enabling smooth object mapping as mentioned in the Installing section.
Works on Linux and Windows, with detailed installation instructions for both systems using devtools, as outlined in the README.
`julia_init()` automatically finds Julia home, simplifying initialization without manual path configuration, as demonstrated in the examples.
Tied to outdated Julia versions (v0.5 or older) and requires recompilation for each upgrade, as stated in Known Problems, limiting forward compatibility.
On Windows, it can crash R due to gcc toolchain issues and requires specific RStudio versions or unofficial Julia builds, making it unreliable for general use.
Rapid Julia API changes necessitate frequent reinstalls with devtools, adding complexity for users who update their software stack regularly.