Dear David, sharing some related (subjective) thoughts below. On Mon, Jan 7, 2019 at 9:53 PM David Lindelof <linde...@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@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
