Introduction

A Go lib for easier concurrency control. Inspired by ReactiveX and javascript Promise.

The v3 library dramatically improve performance than v2 and v1 library by reducing the heap memory allocation.

Benchmark result

Benchmark test on an AMD 2700X Ubuntu 20.04.3 LTS machine Go 1.16.8

v1

BenchmarkExecuteSerial_Immediate-16      	 1259301	       926.5 ns/op	     304 B/op	      14 allocs/op
BenchmarkExecuteSerial_Async-16          	  317821	      4144 ns/op	     616 B/op	      20 allocs/op
BenchmarkExecuteSerial_Pool-16           	  312390	      3894 ns/op	     616 B/op	      20 allocs/op
BenchmarkExecuteParallel_Immediate-16    	  897908	      1252 ns/op	     416 B/op	      17 allocs/op
BenchmarkExecuteParallel_Async-16        	  252895	      5007 ns/op	     728 B/op	      23 allocs/op
BenchmarkExecuteParallel_Pool-16         	  254157	      4411 ns/op	     728 B/op	      23 allocs/op

original v2

BenchmarkExecuteSerial_Immediate-16      	 1388926	       831.9 ns/op	     288 B/op	      11 allocs/op
BenchmarkExecuteSerial_Async-16          	  305587	      3940 ns/op	     600 B/op	      17 allocs/op
BenchmarkExecuteSerial_Pool-16           	  309193	      3626 ns/op	     600 B/op	      17 allocs/op
BenchmarkExecuteParallel_Immediate-16    	  923436	      1159 ns/op	     400 B/op	      14 allocs/op
BenchmarkExecuteParallel_Async-16        	  287938	      4582 ns/op	     712 B/op	      20 allocs/op
BenchmarkExecuteParallel_Pool-16         	  290116	      4016 ns/op	     712 B/op	      20 allocs/op

v3

BenchmarkExecuteSerial_Immediate-16              4078363               286.0 ns/op           168 B/op          3 allocs/op
BenchmarkExecuteSerial_Async-16                   432781              2540 ns/op             168 B/op          3 allocs/op
BenchmarkExecuteSerial_Pool-16                    452028              2473 ns/op             168 B/op          3 allocs/op
BenchmarkExecuteParallel_Immediate-16            1586167               762.7 ns/op           248 B/op          4 allocs/op
BenchmarkExecuteParallel_Async-16                 384945              3181 ns/op             248 B/op          4 allocs/op
BenchmarkExecuteParallel_Pool-16                  425948              2701 ns/op             248 B/op          4 allocs/op

Usage

Simple execution example

    var time1, time2 time.Time
    var t1 koncurrent.TaskFunc = func(ctx context.Context) error {
        time.Sleep(100 * time.Millisecond)
        time1 = time.Now()
        return nil
    }
    var t2 koncurrent.TaskFunc = func(ctx context.Context) error {
        time.Sleep(100 * time.Millisecond)
        time2 = time.Now()
        return nil
    }
    errIter, err := koncurrent.ExecuteParallel(t1.Async(), t2.Immediate()).Await(context.Background())
    fmt.Println(errIter)
    fmt.Println(err)

Cascaded execution example

    var time1, time2, time3, time4 time.Time
    var t1 koncurrent.TaskFunc = func(ctx context.Context) error {
        time.Sleep(100 * time.Millisecond)
        time1 = time.Now()
        return nil
    }
    var t2 koncurrent.TaskFunc = func(ctx context.Context) error {
        time.Sleep(100 * time.Millisecond)
        time2 = time.Now()
        return nil
    }
    var t3 koncurrent.TaskFunc = func(ctx context.Context) error {
        time.Sleep(100 * time.Millisecond)
        tim3 = time.Now()
        return nil
    }
    var t4 koncurrent.TaskFunc = func(ctx context.Context) error {
        time.Sleep(100 * time.Millisecond)
        time4 = time.Now()
        return errors.New("task 4 error occur")
    }
    pe := koncurrent.NewPoolExecutor(20, 20)
    for i := range executors {
        errIter, err := koncurrent.ExecuteSerial(t1.Pool(pe), t2.Async()).
            ExecuteParallel(t3.Pool(pe), t4.Pool(pe)).
            Await(context.Background())
        fmt.Println(errIter)
        fmt.Println(err)
    }

Check more example in execution_test.go