[Rd] Runnable R packages

Murray Stokely murr@y @ending from @tokely@org
Mon Jan 7 22:26:55 CET 2019

Some other major tech companies have in the past widely use Runnable R
Archives (".Rar" files), similar to Python .par files [1], and integrate
them completely into the proprietary R package build system in use there.
I thought there were a few systems like this that had made their way to
CRAN or the UseR conferences, but I don't have a link.

Building something specific to your organization on top of the python .par
framework to archive up R, your needed packages/shared libraries, and other
dependencies with a runner script to R CMD RUN your entry point in a
sandbox is pretty straightforward way to have control in a way that makes
sense for your environment.

      - Murray

[1] https://google.github.io/subpar/subpar.html

On Mon, Jan 7, 2019 at 12:53 PM David Lindelof <lindelof using ieee.org> wrote:

> Dear all,
> I’m working as a data scientist in a major tech company. I have been using
> R for almost 20 years now and there’s one issue that’s been bugging me of
> late. I apologize in advance if this has been discussed before.
> R has traditionally been used for running short scripts or data analysis
> notebooks, but there’s recently been a growing interest in developing full
> applications in the language. Three examples come to mind:
> 1) The Shiny web application framework, which facilitates the developent of
> rich, interactive web applications
> 2) The httr package, which provides lower-level facilities than Shiny for
> writing web services
> 3) Batch jobs run by data scientists according to, say, a cron schedule
> Compared with other languages, R’s support for such applications is rather
> poor. The Rscript program is generally used to run an R script or an
> arbitrary R expression, but I feel it suffers from a few problems:
> 1) It encourages developers of batch jobs to provide their code in a single
> R file (bad for code structure and unit-testability)
> 2) It provides no way to deal with dependencies on other packages
> 3) It provides no way to "run" an application provided as an R package
> For example, let’s say I want to run a Shiny application that I provide as
> an R package (to keep the code modular, to benefit from unit tests, and to
> declare dependencies properly). I would then need to a) uncompress my R
> package, b) somehow, ensure my dependencies are installed, and c) call
> runApp(). This can get tedious, fast.
> Other languages let the developer package their code in "runnable"
> artefacts, and let the developer specify the main entry point. The
> mechanics depend on the language but are remarkably similar, and suggest a
> way to implement this in R. Through declarations in some file, the
> developer can often specify dependencies and declare where the program’s
> "main" function resides. Consider Java:
> Artefact: .jar file
> Declarations file: Manifest file
> Entry point: declared as 'Main-Class'
> Executed as: java -jar <jarfile>
> Or Python:
> Artefact: Python package, typically as .tar.gz source distribution file
> Declarations file: setup.py (which specifies dependencies)
> Entry point: special __main__() function
> Executed as: python -m <package>
> R has already much of this machinery:
> Artefact: R package
> Declarations file: DESCRIPTION
> Entry point: ?
> Executed as: ?
> I feel that R could benefit from letting the developer specify, possibly in
> DESCRIPTION, how to "run" the package. The package could then be run
> through, for example, a new R CMD command, for example:
> R CMD RUN <package> <args>
> I’m sure there are plenty of wrinkles in this idea that need to be ironed
> out, but is this something that has ever been considered, or that is on R’s
> roadmap?
> Thanks for reading so far,
> David Lindelöf, Ph.D.
> +41 (0)79 415 66 41 or skype:david.lindelof
> http://computersandbuildings.com
> Follow me on Twitter:
> http://twitter.com/dlindelof
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