On 25/08/2019 12:08 a.m., Cyclic Group Z_1 via R-devel wrote:
In R scripts (as opposed to packages), even in reproducible scripts, it seems
fairly conventional to use the global workspace as a sort of main function, and
thus R scripts often populate the global environment with many variables, which
may be mutated. Although this makes sense given R has historically been used
interactively and this practice is common for scripting languages, this appears
to disagree with the software-engineering principle of avoiding a mutating
global state. Although this is just a rule of thumb, in R scripts, the frequent
use of global variables is much more pronounced than in other languages.
On the other hand, in Python, it is common to use a main function (through the `def
main():` and `if __name__ == "__main__":` idioms). This is mentioned both in
the documentation as well as in the writing of Python's main creator. Although this is
more beneficial in Python than in R because Python code is structured into modules, which
serve as both scripts and packages, whereas R separates these conceptually, a similar
practice of creating a main function would help avoid the issues from mutating global
state common to other languages and facilitate maintainability, especially for longer
scripts.
Although many great R texts (Advanced R, Art of R Programming, etc.) caution against
assignment in a parent enclosure (e.g., using `<<-`, or `assign`), I have not
seen many promote the use of a main function and avoiding mutating global variables
from top level.
Would it be a good idea to promote use of main functions and limiting
global-state mutation for longer scripts and dedicated applications (not
one-off scripts)? Should these practices be mentioned in the standard
documentation?
Lexical scoping means that all of the problems of global variables are
available to writers who use main(). You could treat the evaluation
frame of your main function exactly like the global workspace: define
functions within it, read and modify local variables from those
functions, etc.
The benefit of using main() if you avoid defining all the other
functions within it is that other functions normally operate on their
arguments with few side effects. You achieve this in R by putting those
other functions in packages, and running those functions in short
scripts. That's how I've always recommended large projects be
organized. You don't want a long script for anything, and you don't
want multiple source files unless they're in a package.
Duncan Murdoch
This question was motivated largely by this discussion on Reddit:
https://www.reddit.com/r/rstats/comments/cp3kva/is_mutating_global_state_acceptable_in_r/
. Apologies beforehand if any of these (partially subjective) assessments are
in error.
Best,
CG
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