[Rd] Conventions: Use of globals and main functions

Duncan Murdoch murdoch@dunc@n @end|ng |rom gm@||@com
Sun Aug 25 13:29:16 CEST 2019

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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