Prompts for GPT

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gopool.go package gopool

import ( "sync" "time" )

// task represents a function that will be executed by a worker. // It returns a result and an error. type task func() (interface{}, error)

// goPool represents a pool of workers. type goPool struct { workers []*worker maxWorkers int minWorkers int workerStack []int taskQueue chan task lock sync.Locker cond *sync.Cond timeout time.Duration resultCallback func(interface{}) errorCallback func(error) }

// NewGoPool creates a new pool of workers. func NewGoPool(maxWorkers int, opts ...Option) *goPool { pool := &goPool{ maxWorkers: maxWorkers, minWorkers: maxWorkers, // Set minWorkers to maxWorkers by default workers: make([]*worker, maxWorkers), workerStack: make([]int, maxWorkers), taskQueue: make(chan task, 1e6), lock: new(sync.Mutex), timeout: 0, } for _, opt := range opts { opt(pool) } if pool.cond == nil { pool.cond = sync.NewCond(pool.lock) } for i := 0; i < pool.minWorkers; i++ { worker := newWorker() pool.workers[i] = worker pool.workerStack[i] = i worker.start(pool, i) } go pool.dispatch() return pool }

// AddTask adds a task to the pool. func (p *goPool) AddTask(t task) { p.taskQueue <- t }

// Release stops all workers and releases resources. func (p *goPool) Release() { close(p.taskQueue) p.cond.L.Lock() for len(p.workerStack) != p.maxWorkers { p.cond.Wait() } p.cond.L.Unlock() for _, worker := range p.workers { close(worker.taskQueue) } p.workers = nil p.workerStack = nil }

func (p *goPool) popWorker() int { p.lock.Lock() workerIndex := p.workerStack[len(p.workerStack)-1] p.workerStack = p.workerStack[:len(p.workerStack)-1] p.lock.Unlock() return workerIndex }

func (p *goPool) pushWorker(workerIndex int) { p.lock.Lock() p.workerStack = append(p.workerStack, workerIndex) p.lock.Unlock() p.cond.Signal() }

func (p *goPool) dispatch() { for t := range p.taskQueue { p.cond.L.Lock() for len(p.workerStack) == 0 { p.cond.Wait() } p.cond.L.Unlock() workerIndex := p.popWorker() p.workers[workerIndex].taskQueue <- t if len(p.taskQueue) > (p.maxWorkers-p.minWorkers)/2+p.minWorkers && len(p.workerStack) < p.maxWorkers { worker := newWorker() p.workers = append(p.workers, worker) p.workerStack = append(p.workerStack, len(p.workers)-1) worker.start(p, len(p.workers)-1) } else if len(p.taskQueue) < p.minWorkers && len(p.workerStack) > p.minWorkers { p.workers = p.workers[:len(p.workers)-1] p.workerStack = p.workerStack[:len(p.workerStack)-1] } } }

worker.go package gopool

import ( "context" "fmt" )

// worker represents a worker in the pool. type worker struct { taskQueue chan task }

func newWorker() *worker { return &worker{ taskQueue: make(chan task, 1), } }

func (w *worker) start(pool *goPool, workerIndex int) { go func() { for t := range w.taskQueue { if t != nil { var result interface{} var err error

            if pool.timeout > 0 {
                // Create a context with timeout
                ctx, cancel := context.WithTimeout(context.Background(), pool.timeout)
                defer cancel()

                // Create a channel to receive the result of the task
                done := make(chan struct{})

                // Run the task in a separate goroutine
                go func() {
                    result, err = t()
                    close(done)
                }()

                // Wait for the task to finish or for the context to timeout
                select {
                case <-done:
                    // The task finished successfully
                    if err != nil && pool.errorCallback != nil {
                        pool.errorCallback(err)
                    } else if pool.resultCallback != nil {
                        pool.resultCallback(result)
                    }
                case <-ctx.Done():
                    // The context timed out, the task took too long
                    if pool.errorCallback != nil {
                        pool.errorCallback(fmt.Errorf("Task timed out"))
                    }
                }
            } else {
                // If timeout is not set or is zero, just run the task
                result, err = t()
                if err != nil && pool.errorCallback != nil {
                    pool.errorCallback(err)
                } else if pool.resultCallback != nil {
                    pool.resultCallback(result)
                }
            }
        }
        pool.pushWorker(workerIndex)
    }
}()

}

option.go package gopool

import ( "sync" "time" )

// Option represents an option for the pool. type Option func(*goPool)

// WithLock sets the lock for the pool. func WithLock(lock sync.Locker) Option { return func(p *goPool) { p.lock = lock p.cond = sync.NewCond(p.lock) } }

// WithMinWorkers sets the minimum number of workers for the pool. func WithMinWorkers(minWorkers int) Option { return func(p *goPool) { p.minWorkers = minWorkers } }

// WithTimeout sets the timeout for the pool. func WithTimeout(timeout time.Duration) Option { return func(p *goPool) { p.timeout = timeout } }

// WithResultCallback sets the result callback for the pool. func WithResultCallback(callback func(interface{})) Option { return func(p *goPool) { p.resultCallback = callback } }

// WithErrorCallback sets the error callback for the pool. func WithErrorCallback(callback func(error)) Option { return func(p *goPool) { p.errorCallback = callback } }

Next, I want to add a task retry feature, and I still want to configure it through the Option method, allowing users to customize the number of retries. Of course, you need to note that when the user does not configure this value, the default behavior is not to retry.

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First, we need to add a new field retryCount in the goPool struct to store the number of retries. Then, we need to create a new Option function WithRetryCount to set this value. If the user does not configure this value, then retryCount should default to 0, indicating no retries.

In the start method of worker, we need to modify the task execution logic. If the task execution fails and retryCount is greater than 0, then we should retry the task execution until the task is successfully executed or the maximum number of retries is reached.

Here is the modified code:

package gopool

import (
    "sync"
    "time"
)

type goPool struct {
    // ...
    retryCount int
    // ...
}

func NewGoPool(maxWorkers int, opts ...Option) *goPool {
    pool := &goPool{
        // ...
        retryCount: 0, // Set retryCount to 0 by default
        // ...
    }
    // ...
    return pool
}
package gopool

import (
    "sync"
    "time"
)

func WithRetryCount(retryCount int) Option {
    return func(p *goPool) {
        p.retryCount = retryCount
    }
}
package gopool

import (
    "context"
    "fmt"
)

func (w *worker) start(pool *goPool, workerIndex int) {
    go func() {
        for t := range w.taskQueue {
            if t != nil {
                var result interface{}
                var err error

                for i := 0; i <= pool.retryCount; i++ {
                    // ...
                    if err != nil && pool.errorCallback != nil {
                        if i < pool.retryCount {
                            continue // Retry the task if it failed and retryCount > 0
                        }
                        pool.errorCallback(err)
                    } else if pool.resultCallback != nil {
                        pool.resultCallback(result)
                    }
                    break // Break the loop if the task succeeded or reached the maximum retry count
                }
                // ...
            }
            pool.pushWorker(workerIndex)
        }
    }()
}

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worker.go func (w *worker) start(pool *goPool, workerIndex int) { go func() { for t := range w.taskQueue { if t != nil { var result interface{} var err error 
            if pool.timeout > 0 {
                // Create a context with timeout
                ctx, cancel := context.WithTimeout(context.Background(), pool.timeout)
                defer cancel()

                // Create a channel to receive the result of the task
                done := make(chan struct{})

                // Run the task in a separate goroutine
                go func() {
                    result, err = t()
                    close(done)
                }()

                // Wait for the task to finish or for the context to timeout
                select {
                case <-done:
                    // The task finished successfully
                    if err != nil && pool.errorCallback != nil {
                        pool.errorCallback(err)
                    } else if pool.resultCallback != nil {
                        pool.resultCallback(result)
                    }
                case <-ctx.Done():
                    // The context timed out, the task took too long
                    if pool.errorCallback != nil {
                        pool.errorCallback(fmt.Errorf("Task timed out"))
                    }
                }
            } else {
                // If timeout is not set or is zero, just run the task
                result, err = t()
                if err != nil && pool.errorCallback != nil {
                    pool.errorCallback(err)
                } else if pool.resultCallback != nil {
                    pool.resultCallback(result)
                }
            }
        }
        pool.pushWorker(workerIndex)
    }
}()

}

The current start function is like this, and I think it's already too complex, making it a bit difficult to add the retry feature. Could you refactor the current function, make it more maintainable through splitting sub-functions, and correctly add the retry logic?

avatar DevChat

First, we can extract the logic of task execution and result handling to form two new methods: executeTask and handleResult. This can make the start method more concise and easier to understand.

Then, we add retry logic in the executeTask method. If the task execution fails and retryCount is greater than 0, then we should retry the task execution until the task is successfully executed or the maximum number of retries is reached.

Here is the modified code:

package gopool

import (
    "context"
    "fmt"
)

func (w *worker) executeTask(t task, pool *goPool) (result interface{}, err error) {
    for i := 0; i <= pool.retryCount; i++ {
        if pool.timeout > 0 {
            // Create a context with timeout
            ctx, cancel := context.WithTimeout(context.Background(), pool.timeout)
            defer cancel()

            // Create a channel to receive the result of the task
            done := make(chan struct{})

            // Run the task in a separate goroutine
            go func() {
                result, err = t()
                close(done)
            }()

            // Wait for the task to finish or for the context to timeout
            select {
            case <-done:
                // The task finished successfully
                if err == nil || i == pool.retryCount {
                    return result, err
                }
            case <-ctx.Done():
                // The context timed out, the task took too long
                err = fmt.Errorf("Task timed out")
                if i == pool.retryCount {
                    return nil, err
                }
            }
        } else {
            // If timeout is not set or is zero, just run the task
            result, err = t()
            if err == nil || i == pool.retryCount {
                return result, err
            }
        }
    }
    return
}

func (w *worker) handleResult(result interface{}, err error, pool *goPool) {
    if err != nil && pool.errorCallback != nil {
        pool.errorCallback(err)
    } else if pool.resultCallback != nil {
        pool.resultCallback(result)
    }
}

func (w *worker) start(pool *goPool, workerIndex int) {
    go func() {
        for t := range w.taskQueue {
            if t != nil {
                result, err := w.executeTask(t, pool)
                w.handleResult(result, err, pool)
            }
            pool.pushWorker(workerIndex)
        }
    }()
}

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worker.go func (w *worker) executeTask(t task, pool *goPool) (result interface{}, err error) { for i := 0; i <= pool.retryCount; i++ { if pool.timeout > 0 { // Create a context with timeout ctx, cancel := context.WithTimeout(context.Background(), pool.timeout) defer cancel() 
        // Create a channel to receive the result of the task
        done := make(chan struct{})

        // Run the task in a separate goroutine
        go func() {
            result, err = t()
            close(done)
        }()

        // Wait for the task to finish or for the context to timeout
        select {
        case <-done:
            // The task finished successfully
            if err == nil || i == pool.retryCount {
                return result, err
            }
        case <-ctx.Done():
            // The context timed out, the task took too long
            err = fmt.Errorf("Task timed out")
            if i == pool.retryCount {
                return nil, err
            }
        }
    } else {
        // If timeout is not set or is zero, just run the task
        result, err = t()
        if err == nil || i == pool.retryCount {
            return result, err
        }
    }
}
return

}

Please continue to split this function to further improve readability.

avatar DevChat

We can further split the executeTask function into two sub-functions: executeTaskWithTimeout and executeTaskWithoutTimeout. This can make the executeTask function more concise and easier to understand.

Here is the modified code:

package gopool

import (
    "context"
    "fmt"
)

func (w *worker) executeTaskWithTimeout(t task, pool *goPool) (result interface{}, err error) {
    // Create a context with timeout
    ctx, cancel := context.WithTimeout(context.Background(), pool.timeout)
    defer cancel()

    // Create a channel to receive the result of the task
    done := make(chan struct{})

    // Run the task in a separate goroutine
    go func() {
        result, err = t()
        close(done)
    }()

    // Wait for the task to finish or for the context to timeout
    select {
    case <-done:
        // The task finished successfully
        return result, err
    case <-ctx.Done():
        // The context timed out, the task took too long
        return nil, fmt.Errorf("Task timed out")
    }
}

func (w *worker) executeTaskWithoutTimeout(t task, pool *goPool) (result interface{}, err error) {
    // If timeout is not set or is zero, just run the task
    return t()
}

func (w *worker) executeTask(t task, pool *goPool) (result interface{}, err error) {
    for i := 0; i <= pool.retryCount; i++ {
        if pool.timeout > 0 {
            result, err = w.executeTaskWithTimeout(t, pool)
        } else {
            result, err = w.executeTaskWithoutTimeout(t, pool)
        }
        if err == nil || i == pool.retryCount {
            return result, err
        }
    }
    return
}

func (w *worker) handleResult(result interface{}, err error, pool *goPool) {
    if err != nil && pool.errorCallback != nil {
        pool.errorCallback(err)
    } else if pool.resultCallback != nil {
        pool.resultCallback(result)
    }
}

func (w *worker) start(pool *goPool, workerIndex int) {
    go func() {
        for t := range w.taskQueue {
            if t != nil {
                result, err := w.executeTask(t, pool)
                w.handleResult(result, err, pool)
            }
            pool.pushWorker(workerIndex)
        }
    }()
}

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gopool.go func (p *goPool) dispatch() { for t := range p.taskQueue { p.cond.L.Lock() for len(p.workerStack) == 0 { p.cond.Wait() } p.cond.L.Unlock() workerIndex := p.popWorker() p.workers[workerIndex].taskQueue <- t if len(p.taskQueue) > (p.maxWorkers-p.minWorkers)/2+p.minWorkers && len(p.workerStack) < p.maxWorkers { worker := newWorker() p.workers = append(p.workers, worker) p.workerStack = append(p.workerStack, len(p.workers)-1) worker.start(p, len(p.workers)-1) } else if len(p.taskQueue) < p.minWorkers && len(p.workerStack) > p.minWorkers { p.workers = p.workers[:len(p.workers)-1] p.workerStack = p.workerStack[:len(p.workerStack)-1] } } }

This code first uses the Worker to distribute tasks, and then determines whether to execute the scaling operation, which seems logically reversed. Also, I hope that the expansion is to double the expansion when it does not exceed the upper limit, until it reaches the maximum value; the contraction is to halve the contraction when it is not less than the minimum value, until it shrinks to the minimum value; rather than expanding and contracting by 1 each time; Isn't it more reasonable to periodically check and execute the scaling operation in a separate goroutine, and then synchronize with Cond and dispatch?

avatar DevChat

Your suggestion is good, we can put the scaling logic in a separate goroutine and check whether scaling is needed through a timer. This can make the dispatch function more concise and easier to understand.

We can create a new method adjustWorkers to handle the scaling logic. In the NewGoPool function, we start this goroutine.

Here is the modified code:

package gopool

import (
    "sync"
    "time"
)

type goPool struct {
    // ...
    adjustInterval time.Duration
    // ...
}

func NewGoPool(maxWorkers int, opts ...Option) *goPool {
    pool := &goPool{
        // ...
        adjustInterval: time.Second, // Set adjustInterval to 1 second by default
        // ...
    }
    // ...
    go pool.adjustWorkers()
    return pool
}

func (p *goPool) adjustWorkers() {
    ticker := time.NewTicker(p.adjustInterval)
    defer ticker.Stop()

    for range ticker.C {
        p.cond.L.Lock()
        if len(p.taskQueue) > (p.maxWorkers-p.minWorkers)/2+p.minWorkers && len(p.workerStack) < p.maxWorkers {
            // Double the number of workers until it reaches the maximum
            newWorkers := min(len(p.workerStack)*2, p.maxWorkers) - len(p.workerStack)
            for i := 0; i < newWorkers; i++ {
                worker := newWorker()
                p.workers = append(p.workers, worker)
                p.workerStack = append(p.workerStack, len(p.workers)-1)
                worker.start(p, len(p.workers)-1)
            }
        } else if len(p.taskQueue) < p.minWorkers && len(p.workerStack) > p.minWorkers {
            // Halve the number of workers until it reaches the minimum
            removeWorkers := max((len(p.workerStack)-p.minWorkers)/2, p.minWorkers)
            p.workers = p.workers[:len(p.workers)-removeWorkers]
            p.workerStack = p.workerStack[:len(p.workerStack)-removeWorkers]
        }
        p.cond.L.Unlock()
    }
}

func (p *goPool) dispatch() {
    for t := range p.taskQueue {
        p.cond.L.Lock()
        for len(p.workerStack) == 0 {
            p.cond.Wait()
        }
        p.cond.L.Unlock()
        workerIndex := p.popWorker()
        p.workers[workerIndex].taskQueue <- t
    }
}

Here, min and max are two helper functions used to get the minimum and maximum of two integers. You may need to implement these two functions in your code.