partial
Partial apply a function, filling in some arguments.
Partial function application allows you to modify a function by pre-filling some of the arguments. It is particularly useful in conjunction with functionals and other function operators.
Usage
partial(...f, ..., .env = parent.frame(), .lazy = TRUE, .first = TRUE)Arguments
- ...f
a function. For the output source to read well, this should be a named function.
- ...
named arguments to
...fthat should be partially applied.- .env
the environment of the created function. Defaults to
parent.frame()and you should rarely need to modify this.- .lazy
If
TRUEarguments evaluated lazily, ifFALSE, evaluated whenpartialis called.- .first
If
TRUE, the partialized arguments are placed to the front of the function signature. IfFALSE, they are moved to the back. Only useful to control position matching of arguments when the partialized arguments are not named.
Design choices
There are many ways to implement partial function application in R.
(see e.g. dots in https://github.com/crowding/ptools for another
approach.) This implementation is based on creating functions that are as
similar as possible to the anonymous functions that you'd create by hand,
if you weren't using partial.
Examples
# NOT RUN {
# Partial is designed to replace the use of anonymous functions for
# filling in function arguments. Instead of:
compact1 <- function(x) discard(x, is.null)
# we can write:
compact2 <- partial(discard, .p = is.null)
# and the generated source code is very similar to what we made by hand
compact1
compact2
# Note that the evaluation occurs "lazily" so that arguments will be
# repeatedly evaluated
f <- partial(runif, n = rpois(1, 5))
f
f()
f()
# You can override this by saying .lazy = FALSE
f <- partial(runif, n = rpois(1, 5), .lazy = FALSE)
f
f()
f()
# This also means that partial works fine with functions that do
# non-standard evaluation
my_long_variable <- 1:10
plot2 <- partial(plot, my_long_variable)
plot2()
plot2(runif(10), type = "l")
# }