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]  1.48643701  0.74245965 -0.02958559 -1.40699491  1.09164048
#> 
#> [[2]]
#> [1] -1.0385714 -1.3429057 -0.7959764  2.1244429 -0.5499333
#> 
#> [[3]]
#> [1]  1.99479777 -0.37637955  1.57523440 -0.02104012 -2.15554360
#> 
#> [[4]]
#> [1]  1.3795233 -0.1293130  2.2500494  0.8972059 -1.2189534
#> 
#> [[5]]
#> [1]  0.2176338  0.1120140 -0.9150514 -1.1933988  0.8365308
#> 
#> [[6]]
#> [1]  1.4909572 -1.7275138  0.3668783  0.1306008 -1.0811151
#> 
#> [[7]]
#> [1] -1.6264912  0.6093191 -0.3837559  0.2647067 -1.0759165
#> 
#> [[8]]
#> [1] -1.7049200 -0.0900827  0.2846788 -0.4430617 -0.2991162
#> 
#> [[9]]
#> [1] -0.7739517  0.2410810 -0.3375843  1.2491336  0.7086719
#> 
#> [[10]]
#> [1]  1.3185074  3.4585513 -0.1949492  0.4287486 -1.4925215
#> 
10 %>%
  rerun(x = rnorm(5), y = rnorm(5)) %>%
  map_dbl(~ cor(.x$x, .x$y))
#>  [1]  0.5839396 -0.3419190 -0.8133030 -0.6915704 -0.6448143  0.7800958
#>  [7] -0.3354932  0.4527590  0.6328682  0.8522864