These functions provide useful helpers for performaning common operations. `cluster_assign()` assigns the same value on each worker; `cluster_assign_each()` assigns different values on each worker; `cluster_assign_partition()` partitions vectors so that each worker gets (approximately) the same number of pieces.

## Usage

```
cluster_assign(.cluster, ...)
cluster_assign_each(.cluster, ...)
cluster_assign_partition(.cluster, ...)
cluster_copy(cluster, names, env = caller_env())
cluster_rm(cluster, names)
cluster_library(cluster, packages)
```

## Arguments

- ...
Name-value pairs

- cluster, .cluster
Cluster to work on

- names
Name of variables to copy.

- env
Environment in which to look for varibles to copy.

- packages
Character vector of packages to load

## Value

Functions that modify the worker environment invisibly return `cluster` so calls can be piped together. The other functions return lists with one element for each worker.

## Examples

```
cl <- default_cluster()
cluster_assign(cl, a = runif(1))
cluster_call(cl, a)
#> [[1]]
#> [1] 0.0586191
#>
#> [[2]]
#> [1] 0.0586191
#>
# Assign different values on each cluster
cluster_assign_each(cl, b = c(1, 10))
cluster_call(cl, b)
#> [[1]]
#> [1] 1
#>
#> [[2]]
#> [1] 10
#>
# Partition a vector so that each worker gets approximately the
# same amount of it
cluster_assign_partition(cl, c = 1:11)
cluster_call(cl, c)
#> [[1]]
#> [1] 1 2 3 4 5 6
#>
#> [[2]]
#> [1] 7 8 9 10 11
#>
# If you want different to compute different values on each
# worker, use `cluster_call()` directly:
cluster_call(cl, d <- runif(1))
#> [[1]]
#> [1] 0.5574918
#>
#> [[2]]
#> [1] 0.9418105
#>
cluster_call(cl, d)
#> [[1]]
#> [1] 0.5574918
#>
#> [[2]]
#> [1] 0.9418105
#>
# cluster_copy() is a useful shortcut
e <- 10
cluster_copy(cl, "e")
cluster_call(cl, ls())
#> [[1]]
#> [1] "a" "b" "c" "d" "e" "x"
#>
#> [[2]]
#> [1] "a" "b" "c" "d" "e" "x"
#>
cluster_rm(cl, letters[1:5])
cluster_call(cl, ls())
#> [[1]]
#> [1] "x"
#>
#> [[2]]
#> [1] "x"
#>
# Use cluster_library() to load packages
cluster_call(cl, search())
#> [[1]]
#> [1] ".GlobalEnv" "package:stats" "package:graphics"
#> [4] "package:grDevices" "package:utils" "package:datasets"
#> [7] "package:methods" "Autoloads" "tools:callr"
#> [10] "package:base"
#>
#> [[2]]
#> [1] ".GlobalEnv" "package:stats" "package:graphics"
#> [4] "package:grDevices" "package:utils" "package:datasets"
#> [7] "package:methods" "Autoloads" "tools:callr"
#> [10] "package:base"
#>
cluster_library(cl, "magrittr")
cluster_call(cl, search())
#> [[1]]
#> [1] ".GlobalEnv" "package:magrittr" "package:stats"
#> [4] "package:graphics" "package:grDevices" "package:utils"
#> [7] "package:datasets" "package:methods" "Autoloads"
#> [10] "tools:callr" "package:base"
#>
#> [[2]]
#> [1] ".GlobalEnv" "package:magrittr" "package:stats"
#> [4] "package:graphics" "package:grDevices" "package:utils"
#> [7] "package:datasets" "package:methods" "Autoloads"
#> [10] "tools:callr" "package:base"
#>
```