mirror of
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464 lines
14 KiB
Markdown
464 lines
14 KiB
Markdown
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# `conc`: better structured concurrency for go
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[](https://pkg.go.dev/github.com/sourcegraph/conc)
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[](https://sourcegraph.com/github.com/sourcegraph/conc)
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[](https://goreportcard.com/report/github.com/sourcegraph/conc)
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[](https://codecov.io/gh/sourcegraph/conc)
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[](https://discord.gg/bvXQXmtRjN)
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`conc` is your toolbelt for structured concurrency in go, making common tasks
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easier and safer.
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```sh
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go get github.com/sourcegraph/conc
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```
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# At a glance
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- Use [`conc.WaitGroup`](https://pkg.go.dev/github.com/sourcegraph/conc#WaitGroup) if you just want a safer version of `sync.WaitGroup`
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- Use [`pool.Pool`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#Pool) if you want a concurrency-limited task runner
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- Use [`pool.ResultPool`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#ResultPool) if you want a concurrent task runner that collects task results
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- Use [`pool.(Result)?ErrorPool`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#ErrorPool) if your tasks are fallible
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- Use [`pool.(Result)?ContextPool`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#ContextPool) if your tasks should be canceled on failure
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- Use [`stream.Stream`](https://pkg.go.dev/github.com/sourcegraph/conc/stream#Stream) if you want to process an ordered stream of tasks in parallel with serial callbacks
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- Use [`iter.Map`](https://pkg.go.dev/github.com/sourcegraph/conc/iter#Map) if you want to concurrently map a slice
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- Use [`iter.ForEach`](https://pkg.go.dev/github.com/sourcegraph/conc/iter#ForEach) if you want to concurrently iterate over a slice
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- Use [`panics.Catcher`](https://pkg.go.dev/github.com/sourcegraph/conc/panics#Catcher) if you want to catch panics in your own goroutines
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All pools are created with
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[`pool.New()`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#New)
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or
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[`pool.NewWithResults[T]()`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#NewWithResults),
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then configured with methods:
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- [`p.WithMaxGoroutines()`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#Pool.MaxGoroutines) configures the maximum number of goroutines in the pool
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- [`p.WithErrors()`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#Pool.WithErrors) configures the pool to run tasks that return errors
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- [`p.WithContext(ctx)`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#Pool.WithContext) configures the pool to run tasks that should be canceled on first error
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- [`p.WithFirstError()`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#ErrorPool.WithFirstError) configures error pools to only keep the first returned error rather than an aggregated error
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- [`p.WithCollectErrored()`](https://pkg.go.dev/github.com/sourcegraph/conc/pool#ResultContextPool.WithCollectErrored) configures result pools to collect results even when the task errored
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# Goals
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The main goals of the package are:
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1) Make it harder to leak goroutines
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2) Handle panics gracefully
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3) Make concurrent code easier to read
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## Goal #1: Make it harder to leak goroutines
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A common pain point when working with goroutines is cleaning them up. It's
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really easy to fire off a `go` statement and fail to properly wait for it to
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complete.
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`conc` takes the opinionated stance that all concurrency should be scoped.
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That is, goroutines should have an owner and that owner should always
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ensure that its owned goroutines exit properly.
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In `conc`, the owner of a goroutine is always a `conc.WaitGroup`. Goroutines
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are spawned in a `WaitGroup` with `(*WaitGroup).Go()`, and
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`(*WaitGroup).Wait()` should always be called before the `WaitGroup` goes out
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of scope.
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In some cases, you might want a spawned goroutine to outlast the scope of the
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caller. In that case, you could pass a `WaitGroup` into the spawning function.
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```go
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func main() {
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var wg conc.WaitGroup
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defer wg.Wait()
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startTheThing(&wg)
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}
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func startTheThing(wg *conc.WaitGroup) {
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wg.Go(func() { ... })
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}
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```
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For some more discussion on why scoped concurrency is nice, check out [this
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blog
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post](https://vorpus.org/blog/notes-on-structured-concurrency-or-go-statement-considered-harmful/).
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## Goal #2: Handle panics gracefully
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A frequent problem with goroutines in long-running applications is handling
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panics. A goroutine spawned without a panic handler will crash the whole process
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on panic. This is usually undesirable.
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However, if you do add a panic handler to a goroutine, what do you do with the
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panic once you catch it? Some options:
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1) Ignore it
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2) Log it
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3) Turn it into an error and return that to the goroutine spawner
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4) Propagate the panic to the goroutine spawner
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Ignoring panics is a bad idea since panics usually mean there is actually
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something wrong and someone should fix it.
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Just logging panics isn't great either because then there is no indication to the spawner
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that something bad happened, and it might just continue on as normal even though your
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program is in a really bad state.
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Both (3) and (4) are reasonable options, but both require the goroutine to have
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an owner that can actually receive the message that something went wrong. This
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is generally not true with a goroutine spawned with `go`, but in the `conc`
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package, all goroutines have an owner that must collect the spawned goroutine.
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In the conc package, any call to `Wait()` will panic if any of the spawned goroutines
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panicked. Additionally, it decorates the panic value with a stacktrace from the child
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goroutine so that you don't lose information about what caused the panic.
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Doing this all correctly every time you spawn something with `go` is not
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trivial and it requires a lot of boilerplate that makes the important parts of
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the code more difficult to read, so `conc` does this for you.
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<table>
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<tr>
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<th><code>stdlib</code></th>
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<th><code>conc</code></th>
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</tr>
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<tr>
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<td>
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```go
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type caughtPanicError struct {
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val any
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stack []byte
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}
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func (e *caughtPanicError) Error() string {
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return fmt.Sprintf(
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"panic: %q\n%s",
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e.val,
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string(e.stack)
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)
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}
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func main() {
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done := make(chan error)
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go func() {
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defer func() {
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if v := recover(); v != nil {
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done <- &caughtPanicError{
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val: v,
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stack: debug.Stack()
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}
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} else {
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done <- nil
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}
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}()
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doSomethingThatMightPanic()
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}()
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err := <-done
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if err != nil {
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panic(err)
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}
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}
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```
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</td>
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<td>
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```go
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func main() {
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var wg conc.WaitGroup
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wg.Go(doSomethingThatMightPanic)
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// panics with a nice stacktrace
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wg.Wait()
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}
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```
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</td>
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</tr>
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</table>
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## Goal #3: Make concurrent code easier to read
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Doing concurrency correctly is difficult. Doing it in a way that doesn't
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obfuscate what the code is actually doing is more difficult. The `conc` package
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attempts to make common operations easier by abstracting as much boilerplate
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complexity as possible.
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Want to run a set of concurrent tasks with a bounded set of goroutines? Use
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`pool.New()`. Want to process an ordered stream of results concurrently, but
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still maintain order? Try `stream.New()`. What about a concurrent map over
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a slice? Take a peek at `iter.Map()`.
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Browse some examples below for some comparisons with doing these by hand.
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# Examples
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Each of these examples forgoes propagating panics for simplicity. To see
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what kind of complexity that would add, check out the "Goal #2" header above.
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Spawn a set of goroutines and waiting for them to finish:
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<table>
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<tr>
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<th><code>stdlib</code></th>
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<th><code>conc</code></th>
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</tr>
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<tr>
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<td>
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```go
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func main() {
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var wg sync.WaitGroup
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for i := 0; i < 10; i++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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// crashes on panic!
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doSomething()
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}()
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}
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wg.Wait()
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}
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```
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</td>
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<td>
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```go
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func main() {
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var wg conc.WaitGroup
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for i := 0; i < 10; i++ {
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wg.Go(doSomething)
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}
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wg.Wait()
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}
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```
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</td>
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</tr>
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</table>
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Process each element of a stream in a static pool of goroutines:
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<table>
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<tr>
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<th><code>stdlib</code></th>
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<th><code>conc</code></th>
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</tr>
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<tr>
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<td>
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```go
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func process(stream chan int) {
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var wg sync.WaitGroup
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for i := 0; i < 10; i++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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for elem := range stream {
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handle(elem)
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}
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}()
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}
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wg.Wait()
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}
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```
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</td>
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<td>
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```go
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func process(stream chan int) {
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p := pool.New().WithMaxGoroutines(10)
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for elem := range stream {
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elem := elem
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p.Go(func() {
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handle(elem)
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})
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}
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p.Wait()
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}
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```
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</td>
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</tr>
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</table>
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Process each element of a slice in a static pool of goroutines:
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<table>
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<tr>
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<th><code>stdlib</code></th>
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<th><code>conc</code></th>
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</tr>
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<tr>
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<td>
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```go
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func process(values []int) {
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feeder := make(chan int, 8)
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var wg sync.WaitGroup
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for i := 0; i < 10; i++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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for elem := range feeder {
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handle(elem)
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}
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}()
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}
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for _, value := range values {
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feeder <- value
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}
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close(feeder)
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wg.Wait()
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}
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```
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</td>
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<td>
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```go
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func process(values []int) {
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iter.ForEach(values, handle)
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}
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```
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</td>
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</tr>
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</table>
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Concurrently map a slice:
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<table>
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<tr>
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<th><code>stdlib</code></th>
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<th><code>conc</code></th>
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</tr>
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<tr>
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<td>
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```go
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func concMap(
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input []int,
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f func(int) int,
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) []int {
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res := make([]int, len(input))
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var idx atomic.Int64
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var wg sync.WaitGroup
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for i := 0; i < 10; i++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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for {
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i := int(idx.Add(1) - 1)
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if i >= len(input) {
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return
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}
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res[i] = f(input[i])
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}
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}()
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}
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wg.Wait()
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return res
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}
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```
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</td>
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<td>
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```go
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func concMap(
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input []int,
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f func(*int) int,
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) []int {
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return iter.Map(input, f)
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}
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```
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</td>
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</tr>
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</table>
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Process an ordered stream concurrently:
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<table>
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<tr>
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<th><code>stdlib</code></th>
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<th><code>conc</code></th>
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</tr>
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<tr>
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<td>
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```go
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func mapStream(
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in chan int,
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out chan int,
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f func(int) int,
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) {
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tasks := make(chan func())
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taskResults := make(chan chan int)
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// Worker goroutines
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var workerWg sync.WaitGroup
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for i := 0; i < 10; i++ {
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workerWg.Add(1)
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go func() {
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defer workerWg.Done()
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for task := range tasks {
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task()
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}
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}()
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}
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// Ordered reader goroutines
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var readerWg sync.WaitGroup
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readerWg.Add(1)
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go func() {
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defer readerWg.Done()
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for result := range taskResults {
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item := <-result
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out <- item
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}
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}()
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// Feed the workers with tasks
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for elem := range in {
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resultCh := make(chan int, 1)
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taskResults <- resultCh
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tasks <- func() {
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resultCh <- f(elem)
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}
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}
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// We've exhausted input.
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// Wait for everything to finish
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close(tasks)
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workerWg.Wait()
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close(taskResults)
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readerWg.Wait()
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}
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```
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</td>
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<td>
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```go
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func mapStream(
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in chan int,
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out chan int,
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f func(int) int,
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) {
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s := stream.New().WithMaxGoroutines(10)
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for elem := range in {
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elem := elem
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s.Go(func() stream.Callback {
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res := f(elem)
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return func() { out <- res }
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})
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}
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s.Wait()
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}
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```
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</td>
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</tr>
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</table>
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# Status
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This package is currently pre-1.0. There are likely to be minor breaking
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changes before a 1.0 release as we stabilize the APIs and tweak defaults.
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Please open an issue if you have questions, concerns, or requests that you'd
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like addressed before the 1.0 release. Currently, a 1.0 is targeted for
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March 2023.
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