rio implements format-specific S3 methods for each type of file that
can be imported from or exported to. This happens via internal S3
generics, .import
and .export
. It is possible
to write new methods like with any S3 generic (e.g.,
print
).
As an example, .import.rio_csv
imports from a
comma-separated values file. If you want to produce a method for a new
filetype with extension myfile
, you simply have to create a
function called .import.rio_myfile
that implements a
format-specific importing routine and returns a data.frame. rio will
automatically recognize new S3 methods, so that you can then import your
file using: import("file.myfile")
.
The way to develop export
method is same:
.export.rio_csv
. The first two parameters of
.export
are file
(file name) and
x
(data frame to be exported).
As general guidance, if an import method creates many attributes,
these attributes should be stored — to the extent possible — in
variable-level attributes fields. These can be gathered to the
data.frame level by the user via gather_attrs
.
The following example shows how the arff import and export methods are implemented internally.
This is the example from the ledger
package (MIT) by Dr
Trevor L David .
.import.rio_ledger <- register # nolint
register <- function(file, ..., toolchain = default_toolchain(file), date = NULL) {
.assert_toolchain(toolchain)
switch(toolchain,
"ledger" = register_ledger(file, ..., date = date),
"hledger" = register_hledger(file, ..., date = date),
"beancount" = register_beancount(file, ..., date = date),
"bean-report_ledger" = {
file <- .bean_report(file, "ledger")
on.exit(unlink(file))
register_ledger(file, ..., date = date)
},
"bean-report_hledger" = {
file <- .bean_report(file, "hledger")
on.exit(unlink(file))
register_hledger(file, ..., date = date)
}
)
}