Dear community,
I am writing my first package with the aim to publish it on
Bioconductor. To structure the code and make it (human) readable I have
defined some helper functions, that will not be exported.
The main function (which will be user available) makes some data
structuring, defines some variables and will then call a helper function
in a lapply-call on a list of data.frames.
Now I find myself passing >>10 arguments (basically everything that was
defined in the main function before the lapply call) to the helper
function when executed by lapply. All arguments (except the index of the
current data.frame from the list which is lapplyd over) are static for
all the runs.
My question is now: What is considered best practice in this case?
should I put all parameters in a list? Is there a way to pass the whole
"parent" environment (the locale of the main function) to lapply, or
should I keep all the single parameters?
Maybe a "pseudo code" example is useful; this is how my problem is
structured:
main_function <- function(alot, of, paramters) {
var01 <- foo
...
varXX <- bar
data_list <- list(data01, data02, data03, ... , dataYY)
lapply(
seq_along(data_list),
function(
i,
var01,
...
varXX
) {
stuff
helper_function(var01, ... , varXX)
},
var01 = var01,
...
varXX = varXX
)
}
Thank you very much!
Best,
Severin
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