invoke
Invoke functions.
Description
This pair of functions make it easier to combine a function and list
of parameters to get a result. invoke is a wrapper around
do.call that makes it easy to use in a pipe. invoke_map
makes it easier to call lists of functions with lists of parameters.
Usage
invoke(.f, .x = NULL, ..., .env = NULL) invoke_map(.f, .x = list(NULL), ..., .env = NULL) invoke_map_lgl(.f, .x = list(NULL), ..., .env = NULL) invoke_map_int(.f, .x = list(NULL), ..., .env = NULL) invoke_map_dbl(.f, .x = list(NULL), ..., .env = NULL) invoke_map_chr(.f, .x = list(NULL), ..., .env = NULL) invoke_map_raw(.f, .x = list(NULL), ..., .env = NULL) invoke_map_dfr(.f, .x = list(NULL), ..., .env = NULL) invoke_map_dfc(.f, .x = list(NULL), ..., .env = NULL)
Arguments
.f |
For |
.x |
For |
... |
Additional arguments passed to each function. |
.env |
Environment in which |
Life cycle
These functions are retired in favour of exec(). They are no
longer under active development but we will maintain them in the
package undefinitely.
-
invoke()is retired in favour of the simplerexec()function reexported from rlang.exec()evaluates a function call built from its inputs and supports tidy dots:# Before: invoke(mean, list(na.rm = TRUE), x = 1:10) # After exec(mean, 1:10, !!!list(na.rm = TRUE))
-
invoke_map()is is retired without replacement because it is more complex to understand than the corresponding code usingmap(),map2()andexec():# Before: invoke_map(fns, list(args)) invoke_map(fns, list(args1, args2)) # After: map(fns, exec, !!!args) map2(fns, list(args1, args2), function(fn, args) exec(fn, !!!args))
See Also
Examples
# Invoke a function with a list of arguments
invoke(runif, list(n = 10))
# Invoke a function with named arguments
invoke(runif, n = 10)
# Combine the two:
invoke(paste, list("01a", "01b"), sep = "-")
# That's more natural as part of a pipeline:
list("01a", "01b") %>%
invoke(paste, ., sep = "-")
# Invoke a list of functions, each with different arguments
invoke_map(list(runif, rnorm), list(list(n = 10), list(n = 5)))
# Or with the same inputs:
invoke_map(list(runif, rnorm), list(list(n = 5)))
invoke_map(list(runif, rnorm), n = 5)
# Or the same function with different inputs:
invoke_map("runif", list(list(n = 5), list(n = 10)))
# Or as a pipeline
list(m1 = mean, m2 = median) %>% invoke_map(x = rcauchy(100))
list(m1 = mean, m2 = median) %>% invoke_map_dbl(x = rcauchy(100))
# Note that you can also match by position by explicitly omitting `.x`.
# This can be useful when the argument names of the functions are not
# identical
list(m1 = mean, m2 = median) %>%
invoke_map(, rcauchy(100))
# If you have pairs of function name and arguments, it's natural
# to store them in a data frame. Here we use a tibble because
# it has better support for list-columns
if (rlang::is_installed("tibble")) {
df <- tibble::tibble(
f = c("runif", "rpois", "rnorm"),
params = list(
list(n = 10),
list(n = 5, lambda = 10),
list(n = 10, mean = -3, sd = 10)
)
)
df
invoke_map(df$f, df$params)
}