Tell about an interesting/complex technical problem you solved.

One of the interesting tasks in Go was related to optimizing the parallel processing of a large volume of data from multiple sources. It was necessary to implement a goroutine pool that would efficiently distribute tasks, taking into account priorities and dependencies between them, as well as correctly handle errors and cancellation through contexts.

For this, I used channels for passing tasks and results, contexts for cancellation and timeouts, and sync.WaitGroup to wait for all goroutines to finish. As a result, it was possible to achieve a significant improvement in system performance and stability.

Example of simplified code:

func worker(ctx context.Context, tasks <-chan Task, results chan<- Result) {
    for {
        select {
        case <-ctx.Done():
            return
        case task, ok := <-tasks:
            if !ok {
                return
            }
            res := process(task)
            results <- res
        }
    }
}