Blorp by Example

Parallel Collection Work

List.parallel splits pure collection transformations across worker threads.

Pure Callbacks

The callback is pure, which prevents shared mutable state and I/O inside the parallel work.

parallel-callback.brp

items.parallel(
    pure func(chunk): chunk.map(pure func(x): x * 2)
)

List.parallel()

parallel hands the callback a ParallelList view with parallel-safe map, filter, and filter_map.

parallel.brp

items.parallel(
    pure func(chunk): chunk.map(pure func(x): x * x)
)

When It Helps

Use it for expensive per-element work, not tiny transforms where scheduling costs dominate.

expensive.brp

pure func expensive(n: Int) -> Int:
    n * n + n

Collecting Results

parallel returns an ordinary List after the scoped work completes.

collected.brp

results: List[Int] = transform(items)

Example

parallel-chunks.brp

pure func expensive(n: Int) -> Int:
	n * n + n


pure func transform(items: List[Int]) -> List[Int]:
	items.parallel(pure func(chunk: ParallelList[Int]):
		chunk.map(pure func(n): expensive(n))
	)


pure func sum(items: List[Int]) -> Int:
	var total: Int = 0
	for item in items:
		total += item
	total


func main(args: List[String]) -> Void:
	print(sum(transform([1, 2, 3, 4])).to_string())

Try It

terminal

blorp run parallel-chunks.brp