writing functions vs. line-by-line interpretation in an R workflow

Question

Much has been written here about developing a workflow in R for statistical projects. The most popular workflow seems to be Josh Reich's LCFD model. With a main.R containing code:

source('load.R')
source('clean.R')
source('func.R')
source('do.R')

so that a single source('main.R') runs the entire project.

Q: Is there a reason to prefer this workflow to one in which the line-by-line interpretive work done in load.R, clean.R, and do.R is replaced by functions which are called by main.R?

I can't find the link now, but I had read somewhere on SO that when programming in R one must get over their desire to write everything in terms of function calls---that R was MEANT to be written is this line-by-line interpretive form.

Q: Really? Why?

I've been frustrated with the LCFD approach and am going to probably write everything in terms of function calls. But before doing this, I'd like to hear from the good folks of SO as to whether this is a good idea or not.

EDIT: The project I'm working on right now is to (1) read in a set of financial data, (2) clean it (quite involved), (3) Estimate some quantity associated with the data using my estimator (4) Estimate that same quantity using traditional estimators (5) Report results. My programs should be written in such a way that it's a cinch to do the work (1) for different empirical data sets, (2) for simulation data, or (3) using different estimators. ALSO, it should follow literate programming and reproducible research guidelines so that it's simple for a newcomer to the code to run the program, understand what's going on, and how to tweak it.

Answer 1

I think that any temporary stuff created in source'd files won't get cleaned up. If I do:

x=matrix(runif(big^2),big,big)
z=sum(x)

and source that as a file, x hangs around although I don't need it. But if I do:

ff=function(big){
 x = matrix(runif(big^2),big,big)
 z=sum(x)
 return(z)
}

and instead of source, do z=ff(big) in my script, the x matrix goes out of scope and so gets cleaned up.

Functions enable neat little re-usable encapsulations and don't pollute outside themselves. In general, they don't have side-effects. Your line-by-line scripts could be using global variables and names tied to the data set in current use, which makes them unre-usable.

I sometimes work line-by-line, but as soon as I get more than about five lines I see that what I have really needs making into a proper reusable function, and more often than not I do end up re-using it.