Menene ginina karancin concurrency da ake sani a Go?

Question

Accepted Answer

Goroutines da channels na Go suna ba da damar jerin **concurrency patterns** da aka tabbata - rarraba aiki, fanning out/in, pipelines, da rate limiting. Sanin waɗannan ginina na al'ada yana ba da damar gina tsarin concurrent da daidai, mai girma.

## Worker pool — bounded concurrency

```go
func workerPool(jobs <-chan int, results chan<- int, numWorkers int) {
    var wg sync.WaitGroup
    for w := 0; w < numWorkers; w++ {     // a FIXED number of workers
        wg.Add(1)
        go func() {
            defer wg.Done()
            for job := range jobs {        // each worker pulls jobs until the channel closes
                results <- process(job)
            }
        }()
    }
    wg.Wait()
    close(results)
}
```

A **worker pool** yana gudna ƙayyade adadin goroutines da ke ci gida daga shared jobs channel — bounded concurrency (misali don kada buɗe 10,000 DB connections; yi amfani da 10 workers). Wannan shine mafi mahimmancin pattern don sarrafa amfani da resources.

## Fan-out / fan-in

```text
Fan-out: distribute work across MULTIPLE goroutines (parallelize)
Fan-in:  MERGE results from multiple goroutines back into one channel
```

```go
// fan-in: merge several channels into one
func merge(channels ...<-chan int) <-chan int {
    out := make(chan int)
    var wg sync.WaitGroup
    for _, ch := range channels {
        wg.Add(1)
        go func(c <-chan int) {
            defer wg.Done()
            for v := range c { out <- v }   // forward each channel's values to out
        }(ch)
    }
    go func() { wg.Wait(); close(out) }()    // close out when all sources are drained
    return out
}
```

## Pipeline — stages connected by channels

```go
// each stage is a goroutine: receives from an input channel, sends to an output channel
func generate(nums ...int) <-chan int {
    out := make(chan int)
    go func() { for _, n := range nums { out <- n }; close(out) }()
    return out
}
func square(in <-chan int) <-chan int {
    out := make(chan int)
    go func() { for n := range in { out <- n * n }; close(out) }()
    return out
}
// compose: square(generate(1,2,3)) → a streaming pipeline
for result := range square(generate(1, 2, 3)) { fmt.Println(result) }
```

A **pipeline** yana haɗa ayyukan stages ta channels — data yana wuce ta, kowane stage yana canza shi ta taɓana.

## Rate limiting

```go
limiter := time.Tick(200 * time.Millisecond)   // a tick every 200ms
for req := range requests {
    <-limiter                                    // wait for the next tick before proceeding
    go handle(req)                                // → at most 5 requests/second
}
```

## Cancellation with context (cross-cutting)

```go
select {
case result := <-work:
case <-ctx.Done():    return   // stop on cancellation — prevents leaks
}
```

## Me yasa ya mahalaci

Waɗannan concurrency patterns shine abubuwan kayan aiki na yau-yau don gina tsarin concurrent na Go na gida, canza raw goroutines da channels zuwa tsarin, daidai mafita zuwa matsaloli maimaitawa.

The **worker pool** ya fi mahimmanci — yana ɗaure concurrency don kariye limited resources (database connections, API rate limits, memory), sanid makali na aiki mara iyaka na goroutines da ke kashe tsarin. **Fan-out/fan-in** yana kammala aiki da haɗi sakamakon; **pipelines** yana cewa streaming data transformations sosai; **rate limiting** yana sarrafa throughput.

Tare da **context-based cancellation** (don guji goroutine leaks), waɗannan patterns shine yadda ayyukan Go na production suke jira concurrency cikin tsaro da girma.

Tuntuni su — kuma musamman sanin ɗaure concurrency tare da worker pools maimakon bayarwa da unlimited goroutines — shine alamar ɗar-da-mahimmaci na Go da matakin ajiya wazifa na gida, tun da naive concurrency (unbounded goroutines, leaks, races) shine tushen marubucin production.