How to Avoid Deadlock When Using Goroutines to Process Values and Gather Results into a Slice?

Using Goroutines to Efficiently Process Values and Gather Results into a Slice

The utilization of goroutines can be a transformative element in Go programming, enabling concurrent task execution and efficient processing. However, proper implementation is crucial to avoid potential pitfalls.

Problem:

When attempting to employ goroutines in a codebase, a "fatal error: all goroutines are asleep - deadlock!" arises. The aim is to process values in a list concurrently, subsequently accumulating the processed results into a new list. Difficulty, however, emerges in the accumulation phase.

Code Decomposition:

The provided code snippet includes several essential elements:

// Process each item with a goroutine and send output to sampleChan
go newSample(line, *replicatePtr, *timePtr, sampleChan, &wg)

• This goroutine concurrently processes the data and sends the outcome to a channel named sampleChan.

// Read from sampleChan and put into a slice
for s := range sampleChan {
    sampleList = append(sampleList, s)
}
close(sampleChan)

• The code attempts to gather results from the channel and incorporate them into a slice.

Solution:

The errors are caused by two issues: premature waiting for worker completion and improper channel closure timing. The following modifications resolve these issues:

go func() {
    wg.Wait()
    close(sampleChan)
}()

• Postpone channel closure until after workers have finished by initiating a separate goroutine.

Additionally, for stylistic cohesion, consider restructuring newSample as a synchronous function for result production, resulting in the following code:

for i, line := range contents {
    wg.Add(1)
    go func(line string) {
        defer wg.Done()
        sampleChan <p>This revised approach improves code readability, eases testing, and simplifies concurrency management, enabling clear identification of critical operations like wg.Done().</p>

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