[Rd] Runnable R packages

Gergely Daróczi d@roczig @ending from r@pporter@net
Mon Jan 7 22:09:07 CET 2019


Dear David, sharing some related (subjective) thoughts below.

On Mon, Jan 7, 2019 at 9:53 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)

I think it rather encourages developers to create (internal) R
packages and use those from the batch jobs. This way the structure is
pretty clean, sharing code between scripts is easy, unit testing can
be done within the package etc.

> 2) It provides no way to deal with dependencies on other packages

See above: create R package(s) and use those from the scripts.

> 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.

You can provide your app as a Docker image, so that the end-user
simply calls a "docker pull" and then "docker run" -- that can be done
from a user-friendly script as well.
Of course, this requires Docker to be installed, but if that's a
problem, probably better to "ship" the app as a web application and
share a URL with the user, eg backed by shinyproxy.io

>
> 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
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-devel using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel



More information about the R-devel mailing list