go-concurrency

What problem does it solve?

Building concurrent applications can be complex and error-prone, leading to race conditions, deadlocks, and inefficient resource utilization. This Skill provides a comprehensive guide to Go's powerful concurrency model, enabling you to design and implement robust, scalable, and safe concurrent systems.

Core Features & Use Cases

• Goroutines & Channels: Learn the fundamental building blocks of Go concurrency for lightweight, efficient parallel execution and safe communication.
• Synchronization Primitives: Master sync.Mutex, sync.RWMutex, sync.WaitGroup, and sync.Once to manage shared resources and coordinate goroutines effectively.
• Concurrency Patterns: Explore common patterns like worker pools, fan-in/fan-out, context for cancellation, and error propagation in concurrent code.
• Use Case: You need to process a large number of tasks in parallel, such as fetching data from multiple APIs or performing heavy computations. This Skill guides you in setting up a worker pool using goroutines and channels to efficiently distribute and manage these tasks, ensuring optimal resource usage and responsiveness.

Quick Start

package main

import ( "fmt" "time" )

func worker(id int, jobs <-chan int, results chan<- int) { for j := range jobs { fmt.Printf("Worker %d started job %d ", id, j) time.Sleep(time.Second) // Simulate work fmt.Printf("Worker %d finished job %d ", id, j) results <- j * 2 } }

func main() { jobs := make(chan int, 100) results := make(chan int, 100)

// Start 3 workers
for w := 1; w <= 3; w++ {
    go worker(w, jobs, results)
}

// Send 5 jobs
for j := 1; j <= 5; j++ {
    jobs <- j
}
close(jobs)

// Collect results
for a := 1; a <= 5; a++ {
    <-results
}

}