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https://github.com/gammazero/workerpool

Concurrency limiting goroutine pool
https://github.com/gammazero/workerpool

concurrency worker-pool

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Concurrency limiting goroutine pool

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# workerpool



[![GoDoc](https://pkg.go.dev/badge/github.com/gammazero/workerpool)](https://pkg.go.dev/github.com/gammazero/workerpool)

[![Build Status](https://github.com/gammazero/workerpool/actions/workflows/go.yml/badge.svg)](https://github.com/gammazero/workerpool/actions/workflows/go.yml)

[![Go Report Card](https://goreportcard.com/badge/github.com/gammazero/workerpool)](https://goreportcard.com/report/github.com/gammazero/workerpool)

[![codecov](https://codecov.io/gh/gammazero/workerpool/branch/master/graph/badge.svg)](https://codecov.io/gh/gammazero/workerpool)

[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/gammazero/workerpool/blob/master/LICENSE)



Concurrency limiting goroutine pool. Limits the concurrency of task execution, not the number of tasks queued. Never blocks submitting tasks, no matter how many tasks are queued.



This implementation builds on ideas from the following:



- http://marcio.io/2015/07/handling-1-million-requests-per-minute-with-golang

- http://nesv.github.io/golang/2014/02/25/worker-queues-in-go.html



## Installation



To install this package, you need to setup your Go workspace. The simplest way to install the library is to run:

```

$ go get github.com/gammazero/workerpool

```



## Example



```go

package main



import (

	"fmt"

	"github.com/gammazero/workerpool"

)



func main() {

	wp := workerpool.New(2)

	requests := []string{"alpha", "beta", "gamma", "delta", "epsilon"}



	for _, r := range requests {

		r := r

		wp.Submit(func() {

			fmt.Println("Handling request:", r)

		})

	}



	wp.StopWait()

}

```



[Example wrapper function](https://go.dev/play/p/BWnRhJYarZ1) to show start and finish time of submitted function.



## Usage Note



There is no upper limit on the number of tasks queued, other than the limits of system resources. If the number of inbound tasks is too many to even queue for pending processing, then the solution is outside the scope of workerpool. It should be solved by distributing workload over multiple systems, and/or storing input for pending processing in intermediate storage such as a file system, distributed message queue, etc.