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knitr: elegant, flexible, and fast dynamic report generation with R

Language engines

Use other languages in knitr


We can use any languages in knitr, including but not limited to R. Here are some simple demos with Python, Awk, Ruby, Haskell, Bash, Perl, Graphviz, TikZ, SAS, Scala, and CoffeeScript, etc:

These languages are easy to deal with because they can be called by pure command line, e.g. python -c can execute the code passed in as a character string.

The Rcpp engine is different, however. The C++ code is compiled through the Rcpp package. See Rcpp.Rmd (output) for example. Similarly, C code is compiled via R CMD SHLIB (example/output).

A special engine cat can be used to save the content of a code chunk to a file using the cat() function; see the example 095 for an application.

The object knit_engines stores a series of named functions to handle code from different languages, and you are free to define a function to deal with a custom language. See engine.R for examples on how I deal with Python and Awk.

I do not really know much about other languages, so please feel free to contribute more language engines to knitr.

Note these languages work not only in Markdown, but also in other formats like LaTeX.

Except engine='R' (default), all chunks are executed in separate sessions, so the variables cannot be directly shared. If we want to make use of objects created in previous chunks, we usually have to write them to files (as side effects). For the bash engine, we can use Sys.setenv() to export variables from R to bash (example). Another approach is to use the (experimental) runr package.