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panjf2000 logoants

🐜🐜🐜 ants is the most powerful and reliable pooling solution for Go.

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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:

  1. 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)
}
  1. 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.")
}
  1. 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

9,481

🚀 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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README

A goroutine pool for Go


English | 中文

📖 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.

🚀 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

💡 How ants works

Flow Diagram

ants-flowchart-en

Activity Diagrams

🧰 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

🛠 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.Optionscontains 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/NewPoolWithFuncmethod.

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()

⚙️ 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.

👏 Contributors

Please read our Contributing Guidelines before opening a PR and thank you to all the developers who already made contributions to ants!

📄 License

The source code in ants is available under the MIT License.

📚 Relevant Articles

🖥 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 是 360 信息安全中心开发的一款针对域安全的日志分析与监控系统,它可以收集所有域控上的事件日志、网络流量,通过特征匹配、协议分析、历史行为、敏感操作和蜜罐账户等方式来检测各种已知与未知威胁,功能覆盖了大部分目前的常见内网域渗透手法。
  • 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.

🔋 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.

💰 Backers

Support us with a monthly donation and help us continue our activities.

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