Interoperability between R Language & other Languages
summary
R has a huge library ecosystem but is slow for loops so code gets vectorized or moved into C/C++; use Rcpp to compile inline C++ and expose functions back to R. SQL Server 2016 runs R inside queries; HaskellR lets Haskell call R and even pass functions. org-mode (with ~40 org-babel languages) reliably glues mixed-language literate files, while Jupyter and Beaker notebooks exchange data frames (Feather/pandas translation) but are more finicky to set up.
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chapters (20)
- 0:00Introduction
- 2:31Why mix languages
- 4:12How to optimize R
- 5:42A few R quirks
- 9:49C package interface
- 12:08Simple Rcpp example
- 14:37SQL Server 2016
- 16:50Haskell
- 19:27Emacs org-mode
- 22:42org-babel languages
- 23:54Structure of an org-mode file goto
- 25:36Language interop
- 27:07Jupyter notebooks
- 28:55Some languages with Jupyter kernels
- 31:03Beaker example
- 32:45Languages supported in Beaker notebooks
- 34:54R Markdown example
- 35:32Languages supported in R Markdown
- 35:56Summary
- 38:20Contact
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