These functions work exactly the same as purrr::modify() functions, but allow you to modify in parallel.

future_modify(
  .x,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_modify_at(
  .x,
  .at,
  .f,
  ...,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

future_modify_if(
  .x,
  .p,
  .f,
  ...,
  .else = NULL,
  .options = furrr_options(),
  .env_globals = parent.frame(),
  .progress = FALSE
)

Arguments

.x

A list or atomic vector.

.f

A function, formula, or vector (not necessarily atomic).

If a function, it is used as is.

If a formula, e.g. ~ .x + 2, it is converted to a function. There are three ways to refer to the arguments:

  • For a single argument function, use .

  • For a two argument function, use .x and .y

  • For more arguments, use ..1, ..2, ..3 etc

This syntax allows you to create very compact anonymous functions.

If character vector, numeric vector, or list, it is converted to an extractor function. Character vectors index by name and numeric vectors index by position; use a list to index by position and name at different levels. If a component is not present, the value of .default will be returned.

...

Additional arguments passed on to the mapped function.

.options

The future specific options to use with the workers. This must be the result from a call to furrr_options().

.env_globals

The environment to look for globals required by .x and .... Globals required by .f are looked up in the function environment of .f.

.progress

A single logical. Should a progress bar be displayed? Only works with multisession, multicore, and multiprocess futures. Note that if a multicore/multisession future falls back to sequential, then a progress bar will not be displayed.

Warning: The .progress argument will be deprecated and removed in a future version of furrr in favor of using the more robust progressr package.

.at

A character vector of names, positive numeric vector of positions to include, or a negative numeric vector of positions to exlude. Only those elements corresponding to .at will be modified. If the tidyselect package is installed, you can use vars() and the tidyselect helpers to select elements.

.p

A single predicate function, a formula describing such a predicate function, or a logical vector of the same length as .x. Alternatively, if the elements of .x are themselves lists of objects, a string indicating the name of a logical element in the inner lists. Only those elements where .p evaluates to TRUE will be modified.

.else

A function applied to elements of .x for which .p returns FALSE.

Value

An object the same class as .x

Details

From purrr:

Since the transformation can alter the structure of the input; it's your responsibility to ensure that the transformation produces a valid output. For example, if you're modifying a data frame, .f must preserve the length of the input.

Examples

library(magrittr) plan(multisession, workers = 2) # Convert each col to character, in parallel future_modify(mtcars, as.character)
#> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21 6 160 110 3.9 2.62 16.46 0 1 4 4 #> Mazda RX4 Wag 21 6 160 110 3.9 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108 93 3.85 2.32 18.61 1 1 4 1 #> Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 18.7 8 360 175 3.15 3.44 17.02 0 0 3 2 #> Valiant 18.1 6 225 105 2.76 3.46 20.22 1 0 3 1 #> Duster 360 14.3 8 360 245 3.21 3.57 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.19 20 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.15 22.9 1 0 4 2 #> Merc 280 19.2 6 167.6 123 3.92 3.44 18.3 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.44 18.9 1 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.07 17.4 0 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.73 17.6 0 0 3 3 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.78 18 0 0 3 3 #> Cadillac Fleetwood 10.4 8 472 205 2.93 5.25 17.98 0 0 3 4 #> Lincoln Continental 10.4 8 460 215 3 5.424 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 32.4 4 78.7 66 4.08 2.2 19.47 1 1 4 1 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.9 1 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.7 2.465 20.01 1 0 3 1 #> Dodge Challenger 15.5 8 318 150 2.76 3.52 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304 150 3.15 3.435 17.3 0 0 3 2 #> Camaro Z28 13.3 8 350 245 3.73 3.84 15.41 0 0 3 4 #> Pontiac Firebird 19.2 8 400 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 27.3 4 79 66 4.08 1.935 18.9 1 1 4 1 #> Porsche 914-2 26 4 120.3 91 4.43 2.14 16.7 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.9 1 1 5 2 #> Ford Pantera L 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4 #> Ferrari Dino 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6 #> Maserati Bora 15 8 301 335 3.54 3.57 14.6 0 1 5 8 #> Volvo 142E 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2
iris %>% future_modify_if(is.factor, as.character) %>% str()
#> 'data.frame': 150 obs. of 5 variables: #> $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ... #> $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ... #> $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ... #> $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ... #> $ Species : chr "setosa" "setosa" "setosa" "setosa" ...
mtcars %>% future_modify_at(c(1, 4, 5), as.character) %>% str()
#> 'data.frame': 32 obs. of 11 variables: #> $ mpg : chr "21" "21" "22.8" "21.4" ... #> $ cyl : num 6 6 4 6 8 6 8 4 4 6 ... #> $ disp: num 160 160 108 258 360 ... #> $ hp : chr "110" "110" "93" "110" ... #> $ drat: chr "3.9" "3.9" "3.85" "3.08" ... #> $ wt : num 2.62 2.88 2.32 3.21 3.44 ... #> $ qsec: num 16.5 17 18.6 19.4 17 ... #> $ vs : num 0 0 1 1 0 1 0 1 1 1 ... #> $ am : num 1 1 1 0 0 0 0 0 0 0 ... #> $ gear: num 4 4 4 3 3 3 3 4 4 4 ... #> $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
# \dontshow{ # Close open connections for R CMD Check if (!inherits(plan(), "sequential")) plan(sequential) # }