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
}
}
