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This function constructs and evaluates a call to .fn. It has two primary uses:

  • To call a function with arguments stored in a list (if the function doesn't support dynamic dots). Splice the list of arguments with !!!.

  • To call every function stored in a list (in conjunction with map()/ lapply())

Usage

exec(.fn, ..., .env = caller_env())

Arguments

.fn

A function, or function name as a string.

...

<dynamic> Arguments for .fn.

.env

Environment in which to evaluate the call. This will be most useful if f is a string, or the function has side-effects.

Examples

args <- list(x = c(1:10, 100, NA), na.rm = TRUE)
exec("mean", !!!args)
#> [1] 14.09091
exec("mean", !!!args, trim = 0.2)
#> [1] 6

fs <- list(a = function() "a", b = function() "b")
lapply(fs, exec)
#> $a
#> [1] "a"
#> 
#> $b
#> [1] "b"
#> 

# Compare to do.call it will not automatically inline expressions
# into the evaluated call.
x <- 10
args <- exprs(x1 = x + 1, x2 = x * 2)
exec(list, !!!args)
#> $x1
#> x + 1
#> 
#> $x2
#> x * 2
#> 
do.call(list, args)
#> $x1
#> [1] 11
#> 
#> $x2
#> [1] 20
#> 

# exec() is not designed to generate pretty function calls. This is
# most easily seen if you call a function that captures the call:
f <- disp ~ cyl
exec("lm", f, data = mtcars)
#> 
#> Call:
#> lm(formula = .Primitive("quote")(disp ~ cyl), data = structure(list(
#>     mpg = c(21, 21, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 
#>     19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4, 30.4, 
#>     33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8, 
#>     19.7, 15, 21.4), cyl = c(6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 
#>     8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 
#>     8, 4), disp = c(160, 160, 108, 258, 360, 225, 360, 146.7, 
#>     140.8, 167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 
#>     78.7, 75.7, 71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 
#>     351, 145, 301, 121), hp = c(110, 110, 93, 110, 175, 105, 
#>     245, 62, 95, 123, 123, 180, 180, 180, 205, 215, 230, 66, 
#>     52, 65, 97, 150, 150, 245, 175, 66, 91, 113, 264, 175, 335, 
#>     109), drat = c(3.9, 3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 
#>     3.92, 3.92, 3.92, 3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 
#>     4.93, 4.22, 3.7, 2.76, 3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 
#>     4.22, 3.62, 3.54, 4.11), wt = c(2.62, 2.875, 2.32, 3.215, 
#>     3.44, 3.46, 3.57, 3.19, 3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 
#>     5.25, 5.424, 5.345, 2.2, 1.615, 1.835, 2.465, 3.52, 3.435, 
#>     3.84, 3.845, 1.935, 2.14, 1.513, 3.17, 2.77, 3.57, 2.78), 
#>     qsec = c(16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 
#>     20, 22.9, 18.3, 18.9, 17.4, 17.6, 18, 17.98, 17.82, 17.42, 
#>     19.47, 18.52, 19.9, 20.01, 16.87, 17.3, 15.41, 17.05, 18.9, 
#>     16.7, 16.9, 14.5, 15.5, 14.6, 18.6), vs = c(0, 0, 1, 1, 0, 
#>     1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 
#>     0, 1, 0, 1, 0, 0, 0, 1), am = c(1, 1, 1, 0, 0, 0, 0, 0, 0, 
#>     0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 
#>     1, 1, 1, 1), gear = c(4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 
#>     3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3, 3, 3, 4, 5, 5, 5, 5, 5, 
#>     4), carb = c(4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 
#>     4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 2, 2, 4, 6, 8, 2)), row.names = c("Mazda RX4", 
#> "Mazda RX4 Wag", "Datsun 710", "Hornet 4 Drive", "Hornet Sportabout", 
#> "Valiant", "Duster 360", "Merc 240D", "Merc 230", "Merc 280", 
#> "Merc 280C", "Merc 450SE", "Merc 450SL", "Merc 450SLC", "Cadillac Fleetwood", 
#> "Lincoln Continental", "Chrysler Imperial", "Fiat 128", "Honda Civic", 
#> "Toyota Corolla", "Toyota Corona", "Dodge Challenger", "AMC Javelin", 
#> "Camaro Z28", "Pontiac Firebird", "Fiat X1-9", "Porsche 914-2", 
#> "Lotus Europa", "Ford Pantera L", "Ferrari Dino", "Maserati Bora", 
#> "Volvo 142E"), class = "data.frame"))
#> 
#> Coefficients:
#> (Intercept)          cyl  
#>      -156.6         62.6  
#> 

# If you need finer control over the generated call, you'll need to
# construct it yourself. This may require creating a new environment
# with carefully constructed bindings
data_env <- env(data = mtcars)
eval(expr(lm(!!f, data)), data_env)
#> 
#> Call:
#> lm(formula = disp ~ cyl, data = data)
#> 
#> Coefficients:
#> (Intercept)          cyl  
#>      -156.6         62.6  
#>