ants/README.md

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# ants
<p align="center">
<img src="https://user-images.githubusercontent.com/7496278/51748488-8efd2600-20e7-11e9-91f5-1c5b466dcca1.jpg"/>
A goroutine pool for Go
<br/><br/>
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</p>
[中文](README_ZH.md) | [Project Blog](https://taohuawu.club/high-performance-implementation-of-goroutine-pool)
Library `ants` implements a goroutine pool with fixed capacity, managing and recycling a massive number of goroutines, allowing developers to limit the number of goroutines in your concurrent programs.
## Features:
- Automatically managing and recycling a massive number of goroutines.
- Periodically purging overdue goroutines.
- Friendly interfaces: submitting tasks, getting the number of running goroutines, tuning capacity of pool dynamically, closing pool.
- Handle panic gracefully to prevent programs from crash.
- Efficient in memory usage and it even achieves higher performance than unlimited goroutines in golang.
## Tested in the following Golang versions:
- 1.8.x
- 1.9.x
- 1.10.x
- 1.11.x
- 1.12.x
## How to install
``` sh
go get -u github.com/panjf2000/ants
```
## How to use
Just take a imagination that your program starts a massive number of goroutines, from which a vast amount of memory will be consumed. To mitigate that kind of situation, all you need to do is to import `ants` package and submit all your tasks to a default pool with fixed capacity, activated when package `ants` is 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
// Use the common pool.
var wg sync.WaitGroup
syncCalculateSum := func() {
demoFunc()
wg.Done()
}
for i := 0; i < runTimes; i++ {
wg.Add(1)
_ = ants.Submit(syncCalculateSum)
}
wg.Wait()
fmt.Printf("running goroutines: %d\n", ants.Running())
fmt.Printf("finish all tasks.\n")
// Use the pool with a function,
// set 10 to the capacity of goroutine pool and 1 second for expired duration.
p, _ := ants.NewPoolWithFunc(10, func(i interface{}) {
myFunc(i)
wg.Done()
})
defer p.Release()
// Submit tasks one by one.
for i := 0; i < runTimes; i++ {
wg.Add(1)
_ = p.Invoke(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(100000, 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)}
// Throttle the requests traffic with ants pool. This process is asynchronous and
// you can receive a result from the channel defined outside.
if err := pool.Invoke(request); err != nil {
http.Error(w, "throttle limit error", http.StatusInternalServerError)
}
w.Write(<-request.Result)
})
http.ListenAndServe(":8080", nil)
}
```
## Functional options for ants pool
```go
type Options struct {
// ExpiryDuration set the expired time (second) of every worker.
ExpiryDuration time.Duration
// PreAlloc indicate whether to make memory pre-allocation when initializing Pool.
PreAlloc bool
// Max number of goroutine blocking on pool.Submit.
// 0 (default value) means no such limit.
MaxBlockingTasks int
// When Nonblocking is true, Pool.Submit will never be blocked.
// ErrPoolOverload will be returned when Pool.Submit cannot be done at once.
// When Nonblocking is true, MaxBlockingTasks is inoperative.
Nonblocking bool
// PanicHandler is used to handle panics from each worker goroutine.
// if nil, panics will be thrown out again from worker goroutines.
PanicHandler func(interface{})
}
func WithOptions(options Options) Option {
return func(opts *Options) {
*opts = options
}
}
func WithExpiryDuration(expiryDuration time.Duration) Option {
return func(opts *Options) {
opts.ExpiryDuration = expiryDuration
}
}
func WithPreAlloc(preAlloc bool) Option {
return func(opts *Options) {
opts.PreAlloc = preAlloc
}
}
func WithMaxBlockingTasks(maxBlockingTasks int) Option {
return func(opts *Options) {
opts.MaxBlockingTasks = maxBlockingTasks
}
}
func WithNonblocking(nonblocking bool) Option {
return func(opts *Options) {
opts.Nonblocking = nonblocking
}
}
func WithPanicHandler(panicHandler func(interface{})) Option {
return func(opts *Options) {
opts.PanicHandler = panicHandler
}
}
```
`ants.Options`contains all optional configurations of ants pool, which allow you to customize the goroutine pool by invoking option functions to set up each configuration in `NewPool`/`NewPoolWithFunc`method.
## Customize limited pool
`ants` also supports customizing the capacity of pool. You can invoke the `NewPool` method to instantiate a pool with a given capacity, as following:
``` go
// Set 10000 the size of goroutine pool
p, _ := ants.NewPool(10000)
```
## Submit tasks
Tasks can be submitted by calling `ants.Submit(func())`
```go
ants.Submit(func(){})
```
## Tune pool capacity in runtime
You can tune the capacity of `ants` pool in runtime with `Tune(int)`:
``` go
pool.Tune(1000) // Tune its capacity to 1000
pool.Tune(100000) // Tune its capacity to 100000
```
Don't worry about the synchronous problems in this case, the method here is thread-safe (or should be called goroutine-safe).
## Pre-malloc goroutine queue in pool
`ants` allows you to pre-allocate memory of goroutine queue in pool, which may get a performance enhancement under some special certain circumstances such as the scenario that requires an pool with ultra-large capacity, meanwhile each task in goroutine lasts for a long time, in this case, pre-mallocing will reduce a lot of costs when re-slicing goroutine queue.
```go
// ants will pre-malloc the whole capacity of pool when you invoke this method
p, _ := ants.NewPool(100000, ants.WithPreAlloc(true))
```
## Release Pool
```go
pool.Release()
```
## About sequence
All tasks submitted to `ants` pool will not be guaranteed to be addressed in order, because those tasks scatter among a series of concurrent workers, thus those tasks would be executed concurrently.
## Benchmarks
```
OS: macOS High Sierra
Processor: 2.7 GHz Intel Core i5
Memory: 8 GB 1867 MHz DDR3
Go Version: 1.9
```
<div align="center"><img src="https://user-images.githubusercontent.com/7496278/51515466-c7ce9e00-1e4e-11e9-89c4-bd3785b3c667.png"/></div>
In that benchmark-picture, the first and second benchmarks performed test cases with 1M tasks and the rest of benchmarks performed test cases with 10M tasks, both in 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 more detailed benchmarks are about to be uploaded later.
### Benchmarks with Pool
![](https://user-images.githubusercontent.com/7496278/51515499-f187c500-1e4e-11e9-80e5-3df8f94fa70f.png)
In above benchmark picture, the first and second benchmarks performed test cases with 1M tasks and the rest of benchmarks performed test cases with 10M tasks, both in 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 the memory comparing with goroutines without pool. (both 1M and 10M tasks)**
### Benchmarks with PoolWithFunc
![](https://user-images.githubusercontent.com/7496278/51515565-1e3bdc80-1e4f-11e9-8a08-452ab91d117e.png)
### Throughput (it is suitable for scenarios where asynchronous tasks are submitted despite of the final results)
#### 100K tasks
![](https://user-images.githubusercontent.com/7496278/51515590-36abf700-1e4f-11e9-91e4-7bd3dcb5f4a5.png)
#### 1M tasks
![](https://user-images.githubusercontent.com/7496278/51515596-44617c80-1e4f-11e9-89e3-01e19d2979a1.png)
#### 10M tasks
![](https://user-images.githubusercontent.com/7496278/52987732-537c2000-3437-11e9-86a6-177f00d7a1d6.png)
### Performance Summary
![](https://user-images.githubusercontent.com/7496278/52989641-51b65a80-343f-11e9-86c0-e855d97343ea.gif)
**In conclusion, `ants` can up to 2x~6x faster than goroutines without a pool and the memory consumption is reduced by 10 to 20 times.**