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

Usage

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)
# }