Convert RDS into R file - r

Question

I had a .rds file code which im told it is a file with R codes. I tried to access it by using readRDS and is able to view the output. May I know how can I convert the .rds into .r file or any editable format so that I could make some edits and view the codes? I have tried looking for solutions but I could not find any related ones.
Link to the .rds file https://drive.google.com/file/d/1SGgKA1ejkF7_uq_27E6Qpaq_fdAcDL8O/view?usp=sharing

Answer 1

Assuming the rds file contains R code, rather than data (which it can, because rds format can save any object including functions and expressions)... then, we can use dput to export the contents into a human readable format.
Here's a simple example:
hello = function() {
print("Hello world")
}
saveRDS(hello, 'hello.rds')
dput(readRDS('hello.rds'), file='hello.r')
The file hello.r now contains the following:
function ()
{
print("Hello world")
}
If we do the same thing with your original file (i.e., dput(readRDS('Fundamental_Model.rds'), file='hello.r')), we get:
list(Fundamental_Model = structure(list(handle = <pointer: (nil)>,
raw = as.raw(c(0x00, 0x00, 0x00, 0x3f, 0x0b, 0x00, 0x00,
# ... many lines omitted
0x00, 0x00, 0x00, 0x6e, 0x69, 0x74, 0x65, 0x72, 0x03, 0x00,
0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x31, 0x32, 0x38)), niter = 129,
call = xgb.train(data = df_train, nrounds = best.nrounds,
paras = xgb.params), params = list(paras = list(colsample_bytree = 0.85,
subsample = 0.85, booster = "gbtree", max_depth = 6,
eta = 0.03, eval_metric = "rmse", objective = "reg:linear",
gamma = 0), silent = 1), callbacks = list(cb.print.evaluation = structure(function (env = parent.frame())
{
if (length(env$bst_evaluation) == 0 || period == 0 ||
NVL(env$rank, 0) != 0)
return()
i <- env$iteration
if ((i - 1)%%period == 0 || i == env$begin_iteration ||
i == env$end_iteration) {
stdev <- if (showsd)
env$bst_evaluation_err
else NULL
msg <- format.eval.string(i, env$bst_evaluation,
stdev)
cat(msg, "\n")
}
}, call = cb.print.evaluation(period = print_every_n), name = "cb.print.evaluation")),
feature_names = c("X6", "X7", "X8", "X9", "X10", "X11", "X12",
"X13", "X14", "X15", "X16"), nfeatures = 11L), class = "xgb.Booster"))