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🚀 gnet is a high-performance, lightweight, non-blocking, event-driven networking framework written in pure Go.
Quick Overview
The panjf2000/ants
project is a high-performance, lightweight, and scalable Go concurrency library that provides a simple and efficient way to manage and coordinate goroutines (lightweight threads in Go). It is designed to help developers write concurrent and parallel programs in Go with ease.
Pros
- High Performance: The library is optimized for performance, allowing for efficient management of a large number of goroutines.
- Simplicity: The API is straightforward and easy to use, making it accessible for developers of all skill levels.
- Scalability: The library can handle a large number of goroutines, making it suitable for building scalable applications.
- Flexibility: The library provides a variety of features and options, allowing developers to customize the behavior of the goroutines to fit their specific needs.
Cons
- Limited Documentation: The project's documentation could be more comprehensive, which may make it challenging for new users to get started.
- Lack of Detailed Examples: While the project provides some examples, more detailed and diverse examples would be helpful for developers to understand the library's capabilities.
- Potential Learning Curve: Developers who are new to Go or concurrent programming may need to invest some time to fully understand the concepts and best practices involved in using the library.
- Potential Vendor Lock-in: By using this specific library, developers may become dependent on it, which could make it difficult to switch to alternative solutions in the future.
Code Examples
Here are a few code examples demonstrating the usage of the panjf2000/ants
library:
- Creating a Worker Pool:
package main
import (
"fmt"
"time"
"github.com/panjf2000/ants/v2"
)
func main() {
// Create a worker pool with a maximum of 10 goroutines
p, _ := ants.NewPoolWithFunc(10, func(i interface{}) {
// Simulate some work
time.Sleep(time.Second)
fmt.Println("Processed task:", i.(int))
})
defer p.Release()
// Submit tasks to the worker pool
for i := 0; i < 100; i++ {
_ = p.Invoke(i)
}
// Wait for all tasks to complete
time.Sleep(time.Second * 12)
}
- Using a Context to Cancel Tasks:
package main
import (
"context"
"fmt"
"time"
"github.com/panjf2000/ants/v2"
)
func main() {
// Create a worker pool with a maximum of 10 goroutines
p, _ := ants.NewPoolWithFunc(10, func(i interface{}) {
// Simulate some work
time.Sleep(time.Second * 3)
fmt.Println("Processed task:", i.(int))
})
defer p.Release()
// Create a context with a 5-second timeout
ctx, cancel := context.WithTimeout(context.Background(), time.Second*5)
defer cancel()
// Submit tasks to the worker pool with the context
for i := 0; i < 100; i++ {
_ = p.Submit(ctx, i)
}
// Wait for all tasks to complete or the context to be canceled
<-ctx.Done()
fmt.Println("All tasks completed or canceled.")
}
- Dynamically Adjusting the Pool Size:
package main
import (
"fmt"
"time"
"github.com/panjf2000/ants/v2"
)
func main() {
// Create a worker pool with an initial size of 5 goroutines
p, _ := ants.NewPoolWithFunc(5, func(i interface{}) {
// Simulate some work
time.Sleep(time.Second)
fmt.Println("Processed task:", i.(int))
})
defer p.Release()
// Submit tasks to the worker pool
for i := 0; i < 100; i++ {
_
Competitor Comparisons
🚀 gnet is a high-performance, lightweight, non-blocking, event-driven networking framework written in pure Go.
Pros of gnet
- gnet is a high-performance, non-blocking, event-driven networking framework for Go.
- gnet provides a simple and intuitive API for building network applications.
- gnet supports a wide range of network protocols, including TCP, UDP, and WebSocket.
Cons of gnet
- gnet may have a steeper learning curve compared to Ants, as it provides more advanced features and functionality.
- gnet may have a higher memory footprint than Ants, depending on the complexity of the application.
Code Comparison
Here's a brief comparison of the code for a simple TCP server in both Ants and gnet:
Ants:
func main() {
ant.Run(func(c *ant.Conn) {
c.Write([]byte("Hello, World!"))
})
}
gnet:
func main() {
_ = gnet.Serve(new(echoServer), "tcp://0.0.0.0:8080")
}
type echoServer struct{}
func (es *echoServer) React(frame []byte, c gnet.Conn) (out []byte, action gnet.Action) {
return frame, gnet.None
}
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English | ä¸æ
ð Introduction
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.
ð Features:
- Managing and recycling a massive number of goroutines automatically
- Purging overdue goroutines periodically
- Abundant APIs: submitting tasks, getting the number of running goroutines, tuning the capacity of the pool dynamically, releasing the pool, rebooting the pool
- Handle panic gracefully to prevent programs from crash
- Efficient in memory usage and it even achieves higher performance than unlimited goroutines in Golang
- Nonblocking mechanism
ð¡ How ants
works
Flow Diagram
Activity Diagrams
𧰠How to install
For ants
v1
go get -u github.com/panjf2000/ants
For ants
v2 (with GO111MODULE=on)
go get -u github.com/panjf2000/ants/v2
ð How to use
Just imagine that your program starts a massive number of goroutines, resulting in a huge consumption of memory. 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:
package main
import (
"fmt"
"sync"
"sync/atomic"
"time"
"github.com/panjf2000/ants/v2"
)
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)
if sum != 499500 {
panic("the final result is wrong!!!")
}
// Use the MultiPool and set the capacity of the 10 goroutine pools to unlimited.
// If you use -1 as the pool size parameter, the size will be unlimited.
// There are two load-balancing algorithms for pools: ants.RoundRobin and ants.LeastTasks.
mp, _ := ants.NewMultiPool(10, -1, ants.RoundRobin)
defer mp.ReleaseTimeout(5 * time.Second)
for i := 0; i < runTimes; i++ {
wg.Add(1)
_ = mp.Submit(syncCalculateSum)
}
wg.Wait()
fmt.Printf("running goroutines: %d\n", mp.Running())
fmt.Printf("finish all tasks.\n")
// Use the MultiPoolFunc and set the capacity of 10 goroutine pools to (runTimes/10).
mpf, _ := ants.NewMultiPoolWithFunc(10, runTimes/10, func(i interface{}) {
myFunc(i)
wg.Done()
}, ants.LeastTasks)
defer mpf.ReleaseTimeout(5 * time.Second)
for i := 0; i < runTimes; i++ {
wg.Add(1)
_ = mpf.Invoke(int32(i))
}
wg.Wait()
fmt.Printf("running goroutines: %d\n", mpf.Running())
fmt.Printf("finish all tasks, result is %d\n", sum)
if sum != 499500*2 {
panic("the final result is wrong!!!")
}
}
Functional options for ants pool
// Option represents the optional function.
type Option func(opts *Options)
// Options contains all options which will be applied when instantiating a ants pool.
type Options struct {
// ExpiryDuration is a period for the scavenger goroutine to clean up those expired workers,
// the scavenger scans all workers every `ExpiryDuration` and clean up those workers that haven't been
// used for more than `ExpiryDuration`.
ExpiryDuration time.Duration
// PreAlloc indicates 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{})
// Logger is the customized logger for logging info, if it is not set,
// default standard logger from log package is used.
Logger Logger
}
// WithOptions accepts the whole options config.
func WithOptions(options Options) Option {
return func(opts *Options) {
*opts = options
}
}
// WithExpiryDuration sets up the interval time of cleaning up goroutines.
func WithExpiryDuration(expiryDuration time.Duration) Option {
return func(opts *Options) {
opts.ExpiryDuration = expiryDuration
}
}
// WithPreAlloc indicates whether it should malloc for workers.
func WithPreAlloc(preAlloc bool) Option {
return func(opts *Options) {
opts.PreAlloc = preAlloc
}
}
// WithMaxBlockingTasks sets up the maximum number of goroutines that are blocked when it reaches the capacity of pool.
func WithMaxBlockingTasks(maxBlockingTasks int) Option {
return func(opts *Options) {
opts.MaxBlockingTasks = maxBlockingTasks
}
}
// WithNonblocking indicates that pool will return nil when there is no available workers.
func WithNonblocking(nonblocking bool) Option {
return func(opts *Options) {
opts.Nonblocking = nonblocking
}
}
// WithPanicHandler sets up panic handler.
func WithPanicHandler(panicHandler func(interface{})) Option {
return func(opts *Options) {
opts.PanicHandler = panicHandler
}
}
// WithLogger sets up a customized logger.
func WithLogger(logger Logger) Option {
return func(opts *Options) {
opts.Logger = logger
}
}
ants.Options
contains all optional configurations of the ants pool, which allows 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 the pool. You can invoke the NewPool
method to instantiate a pool with a given capacity, as follows:
p, _ := ants.NewPool(10000)
Submit tasks
Tasks can be submitted by calling ants.Submit(func())
ants.Submit(func(){})
Tune pool capacity in runtime
You can tune the capacity of ants
pool in runtime with Tune(int)
:
pool.Tune(1000) // Tune its capacity to 1000
pool.Tune(100000) // Tune its capacity to 100000
Don't worry about the contention 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 the memory of the goroutine queue in the pool, which may get a performance enhancement under some special certain circumstances such as the scenario that requires a 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 memory allocation in goroutine queue.
// ants will pre-malloc the whole capacity of pool when you invoke this method
p, _ := ants.NewPool(100000, ants.WithPreAlloc(true))
Release Pool
pool.Release()
Reboot Pool
// A pool that has been released can be still used once you invoke the Reboot().
pool.Reboot()
âï¸ 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.
ð Contributors
Please read our Contributing Guidelines before opening a PR and thank you to all the developers who already made contributions to ants
!
ð License
The source code in ants
is available under the MIT License.
ð Relevant Articles
- Goroutine 并åè°åº¦æ¨¡å深度解æä¹ææ¸ä¸ä¸ªé«æ§è½ goroutine æ±
- Visually Understanding Worker Pool
- The Case For A Go Worker Pool
- Go Concurrency - GoRoutines, Worker Pools and Throttling Made Simple
ð¥ Use cases
business corporations
Trusted by the following corporations/organizations.
If you're also using ants
in production, please help us enrich this list by opening a pull request.
open-source software
The open-source projects below do concurrent programming with the help of ants
.
- gnet: A high-performance, lightweight, non-blocking, event-driven networking framework written in pure Go.
- milvus: An open-source vector database for scalable similarity search and AI applications.
- nps: A lightweight, high-performance, powerful intranet penetration proxy server, with a powerful web management terminal.
- siyuan: SiYuan is a local-first personal knowledge management system that supports complete offline use, as well as end-to-end encrypted synchronization.
- osmedeus: A Workflow Engine for Offensive Security.
- jitsu: An open-source Segment alternative. Fully-scriptable data ingestion engine for modern data teams. Set-up a real-time data pipeline in minutes, not days.
- triangula: Generate high-quality triangulated and polygonal art from images.
- teler: Real-time HTTP Intrusion Detection.
- bsc: A Binance Smart Chain client based on the go-ethereum fork.
- jaeles: The Swiss Army knife for automated Web Application Testing.
- devlake: The open-source dev data platform & dashboard for your DevOps tools.
- matrixone: MatrixOne is a future-oriented hyper-converged cloud and edge native DBMS that supports transactional, analytical, and streaming workloads with a simplified and distributed database engine, across multiple data centers, clouds, edges and other heterogeneous infrastructures.
- bk-bcs: BlueKing Container Service (BCS, same below) is a container management and orchestration platform for the micro-services under the BlueKing ecosystem.
- trueblocks-core: TrueBlocks improves access to blockchain data for any EVM-compatible chain (particularly Ethereum mainnet) while remaining entirely local.
- openGemini: openGemini is an open-source,cloud-native time-series database(TSDB) that can be widely used in IoT, Internet of Vehicles(IoV), O&M monitoring, and industrial Internet scenarios.
- AdGuardDNS: AdGuard DNS is an alternative solution for tracker blocking, privacy protection, and parental control.
- WatchAD2.0: WatchAD2.0 æ¯ 360 ä¿¡æ¯å®å ¨ä¸å¿å¼åçä¸æ¬¾é对åå®å ¨çæ¥å¿åæä¸çæ§ç³»ç»ï¼å®å¯ä»¥æ¶éææåæ§ä¸çäºä»¶æ¥å¿ãç½ç»æµéï¼éè¿ç¹å¾å¹é ãåè®®åæãåå²è¡ä¸ºãæææä½åèç½è´¦æ·çæ¹å¼æ¥æ£æµåç§å·²ç¥ä¸æªç¥å¨èï¼åè½è¦çäºå¤§é¨åç®åç常è§å ç½åæ¸éææ³ã
- vanus: Vanus is a Serverless, event streaming system with processing capabilities. It easily connects SaaS, Cloud Services, and Databases to help users build next-gen Event-driven Applications.
- trpc-go: A pluggable, high-performance RPC framework written in Golang.
- motan-go: a remote procedure call (RPC) framework for the rapid development of high-performance distributed services.
All use cases:
If you have ants
integrated into projects, feel free to open a pull request refreshing this list of use cases.
ð JetBrains OS licenses
ants
had been being developed with GoLand under the free JetBrains Open Source license(s) granted by JetBrains s.r.o., hence I would like to express my thanks here.
ð° Backers
Support us with a monthly donation and help us continue our activities.
ð Sponsors
Become a bronze sponsor with a monthly donation of $10 and get your logo on our README on GitHub.
âï¸ Buy me a coffee
Please be sure to leave your name, GitHub account, or other social media accounts when you donate by the following means so that I can add it to the list of donors as a token of my appreciation.
ð Sponsorship
Top Related Projects
🚀 gnet is a high-performance, lightweight, non-blocking, event-driven networking framework written in pure Go.
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