# ants

<div align="center"><img src="ants_logo.png"/></div>

<p align="center">A goroutine pool for Go</p>


[![Build Status][1]][2]
[![codecov][3]][4]
[![goreportcard for panjf2000/ants][5]][6]
[![godoc for panjf2000/ants][7]][8]
[![MIT Licence][9]][10]

[中文项目说明](README_ZH.md) | [Project Tutorial](http://blog.taohuawu.club/article/goroutine-pool)

Package `ants` implements a fixed goroutine pool for managing and recycling a massive number of goroutines, allowing developers to limit the number of goroutines that created in your concurrent programs.

## Features:

- Automatically managing and recycling a massive number of goroutines.
- Periodically clearing overdue goroutines.
- Friendly interfaces: submitting tasks, getting the number of running goroutines, readjusting capacity of pool dynamically, closing pool.
- Efficient in memory usage and it even achieves higher performance than unlimited goroutines in golang.


## How to install

``` sh
go get -u github.com/panjf2000/ants
```

Or, using glide:

``` sh
glide get github.com/panjf2000/ants
```

## How to use
If your program will generate a massive number of goroutines and you don't want them to consume a vast amount of memory, with `ants`, all you need to do is to import `ants` package and submit all your tasks to the default limited pool created when `ants` was imported:

``` go
package main

import (
	"fmt"
	"sync"
	"sync/atomic"
	"time"

	"github.com/panjf2000/ants"
)

var sum int32

func myFunc(i interface{}) {
	n := i.(int32)
	atomic.AddInt32(&sum, n)
	fmt.Printf("run with %d\n", n)
}

func demoFunc() {
	time.Sleep(10 * time.Millisecond)
	fmt.Println("Hello World!")
}

func main() {
	defer ants.Release()

	runTimes := 1000

	// Uses the common pool
	var wg sync.WaitGroup
	for i := 0; i < runTimes; i++ {
		wg.Add(1)
		ants.Submit(func() {
			demoFunc()
			wg.Done()
		})
	}
	wg.Wait()
	fmt.Printf("running goroutines: %d\n", ants.Running())
	fmt.Printf("finish all tasks.\n")

	// Uses the pool with a function,
	// sets 10 to the size of goroutine pool and 1 second for expired duration
	p, _ := ants.NewPoolWithFunc(10, func(i interface{}) {
		myFunc(i)
		wg.Done()
	})
	defer p.Release()
	// Submits tasks
	for i := 0; i < runTimes; i++ {
		wg.Add(1)
		p.Serve(int32(i))
	}
	wg.Wait()
	fmt.Printf("running goroutines: %d\n", p.Running())
	fmt.Printf("finish all tasks, result is %d\n", sum)
}
```

## Integrate with http server
```go
package main

import (
	"io/ioutil"
	"net/http"

	"github.com/panjf2000/ants"
)

type Request struct {
	Param  []byte
	Result chan []byte
}

func main() {
	pool, _ := ants.NewPoolWithFunc(100, func(payload interface{}) {
		request, ok := payload.(*Request)
		if !ok {
			return
		}
		reverseParam := func(s []byte) []byte {
			for i, j := 0, len(s)-1; i < j; i, j = i+1, j-1 {
				s[i], s[j] = s[j], s[i]
			}
			return s
		}(request.Param)

		request.Result <- reverseParam
	})
	defer pool.Release()

	http.HandleFunc("/reverse", func(w http.ResponseWriter, r *http.Request) {
		param, err := ioutil.ReadAll(r.Body)
		if err != nil {
			http.Error(w, "request error", http.StatusInternalServerError)
		}
		defer r.Body.Close()

		request := &Request{Param: param, Result: make(chan []byte)}

		// Throttles the requests with ants pool. This process is asynchronous and
		// you can receive a result from the channel defined outside.
		if err := pool.Serve(request); err != nil {
			http.Error(w, "throttle limit error", http.StatusInternalServerError)
		}

		w.Write(<-request.Result)
	})

	http.ListenAndServe(":8080", nil)
}
```

## Submits tasks
Tasks can be submitted by calling `ants.Submit(func())`
```go
ants.Submit(func(){})
```

## Customizes limited pool
`ants` also supports customizing limited pool. You can use the `NewPool` method to create a pool with the given capacity, as following:

``` go
// Sets 10000 the size of goroutine pool
p, _ := ants.NewPool(10000)
// Submits a task
p.Submit(func(){})
```

## Tuning pool capacity
You can change `ants` pool capacity at any time with `ReSize(int)`:

``` go
pool.ReSize(1000) // Tunes its capacity to 1000
pool.ReSize(100000) // Tunes its capacity to 100000
```

Don't worry about the synchronous problems in this case, this method is thread-safe.

## About sequence
All the tasks submitted to `ants` pool will not be guaranteed to be processed in order, because those tasks distribute among a series of concurrent workers, thus those tasks are processed concurrently.

## Benchmarks

```
OS : macOS High Sierra
Processor : 2.7 GHz Intel Core i5
Memory : 8 GB 1867 MHz DDR3

Go1.9
```

<div align="center"><img src="ants_benchmarks.png"/></div>

 In that benchmark-picture, the first and second benchmarks performed test with 1M tasks and the rest of benchmarks performed test with 10M tasks, both unlimited goroutines and `ants` pool, and the capacity of this `ants` goroutine-pool was limited to 50K.

- BenchmarkGoroutine-4 represents the benchmarks with unlimited goroutines in golang.

- BenchmarkPoolGroutine-4 represents the benchmarks with a `ants` pool.

The test data above is a basic benchmark and the more detailed benchmarks will be uploaded later.

### Benchmarks with Pool 

![](benchmark_pool.png)

In that benchmark-picture, the first and second benchmarks performed test with 1M tasks and the rest of benchmarks performed test with 10M tasks, both unlimited goroutines and `ants` pool, and the capacity of this `ants` goroutine-pool was limited to 50K.

**As you can see, `ants` can up to 2x faster than goroutines without pool (10M tasks) and it only consumes half memory comparing with goroutines without pool. (both 1M and 10M tasks)**

### Benchmarks with PoolWithFunc

![](ants_bench_poolwithfunc.png)

### Throughput (it is suitable for scenarios where asynchronous tasks are submitted without concern for results) 

#### 100K tasks

![](ants_bench_10w.png)

#### 1M tasks

![](ants_bench_100w.png)

#### 10M tasks

![](ants_bench_1000w.png)

There was only the test of `ants` Pool because my computer was crash when it reached 10M goroutines without pool. 

**In conclusion, `ants` can up to 2x~6x faster than goroutines without pool and the memory consumption is reduced by 10 to 20 times.**

[1]: https://travis-ci.com/panjf2000/ants.svg?branch=develop
[2]: https://travis-ci.com/panjf2000/ants
[3]: https://codecov.io/gh/panjf2000/ants/branch/develop/graph/badge.svg
[4]: https://codecov.io/gh/panjf2000/ants
[5]: https://goreportcard.com/badge/github.com/panjf2000/ants
[6]: https://goreportcard.com/report/github.com/panjf2000/ants
[7]: https://godoc.org/github.com/panjf2000/ants?status.svg
[8]: https://godoc.org/github.com/panjf2000/ants
[9]: https://badges.frapsoft.com/os/mit/mit.svg?v=103
[10]: https://opensource.org/licenses/mit-license.php