Re-run expressions multiple times.

This is a convenient way of generating sample data. It works similarly to replicate(..., simplify = FALSE).

rerun(.n, ...)

Arguments

.n	Number of times to run expressions
...	Expressions to re-run.

Value

A list of length .n. Each element of ... will be re-run once for each .n.

There is one special case: if there's a single unnamed input, the second level list will be dropped. In this case, rerun(n, x) behaves like replicate(n, x, simplify = FALSE).

Lifecycle

rerun() is in the questioning lifecycle stage because we are no longer convinced NSE functions are a good fit for purrr. Also, rerun(n, x) can just as easily be expressed as map(1:n, ~ x) (with the added benefit of being passed the current index as argument to the lambda).

Examples

10 %>% rerun(rnorm(5))
#> [[1]]
#> [1] -0.1165475 -0.2394815 -1.0777479 -1.6147655  2.2264153
#> 
#> [[2]]
#> [1] -1.0951697  1.3531404 -1.3668377 -0.3109369  1.0309340
#> 
#> [[3]]
#> [1]  2.1270070  2.2671748 -0.7295284 -0.3285439 -1.0982613
#> 
#> [[4]]
#> [1]  0.1943798  0.4002536 -0.4490203  1.5965016 -0.2169430
#> 
#> [[5]]
#> [1] 1.0666471 1.4070856 0.2900719 0.8935104 0.7180041
#> 
#> [[6]]
#> [1]  0.3371559 -1.6741345  0.4867500 -1.0234974  0.2061258
#> 
#> [[7]]
#> [1] -0.2367365  1.7270080  0.8006205 -1.8889077 -0.5625300
#> 
#> [[8]]
#> [1] -0.1346985  0.4111025 -0.6739550 -0.8711032  0.4065985
#> 
#> [[9]]
#> [1]  0.7491272  0.4080580 -0.1398280 -0.7211374  0.2844147
#> 
#> [[10]]
#> [1]  1.36780134 -0.09473477 -1.71740570  0.15306192  1.01317917
#> 
10 %>%
  rerun(x = rnorm(5), y = rnorm(5)) %>%
  map_dbl(~ cor(.x$x, .x$y))
#>  [1] -0.89673073  0.76702858 -0.86471325 -0.16389576  0.06149510 -0.34729814
#>  [7] -0.88311137 -0.01305969  0.75752511  0.03675323