goroutines

Go Concurrency Patterns Series: Series Overview | Channel Fundamentals → What are Goroutines? Goroutines are lightweight threads managed by the Go runtime. They’re one of Go’s most powerful features, allowing you to write concurrent programs that can handle thousands of simultaneous operations with minimal overhead. Think of goroutines as extremely efficient workers that can run independently while sharing the same memory space. Unlike traditional threads that typically consume 1-2MB of memory each, goroutines start with just 2KB of stack space and grow as needed....

Go Concurrency Patterns Series: ← Pipeline Pattern | Series Overview | Pub/Sub Pattern → What is the Fan-Out/Fan-In Pattern? The Fan-Out/Fan-In pattern is a powerful concurrency pattern that distributes work across multiple goroutines (fan-out) and then collects the results back into a single channel (fan-in). This pattern is perfect for parallelizing CPU-intensive tasks or I/O operations that can be processed independently. Fan-Out: Distribute work from one source to multiple workers Fan-In: Collect results from multiple workers into a single destination...

Go Concurrency Patterns Series: ← Fan-Out/Fan-In | Series Overview | Request/Response → What is the Pub/Sub Pattern? The Publisher/Subscriber (Pub/Sub) pattern is a messaging pattern where publishers send messages without knowing who will receive them, and subscribers receive messages without knowing who sent them. This creates a loosely coupled system where components can communicate through events without direct dependencies. Key Components: Publisher: Sends messages/events Subscriber: Receives and processes messages/events Message Broker: Routes messages from publishers to subscribers Topics/Channels: Categories for organizing messages Real-World Use Cases Event-Driven Architecture: Microservices communication Real-Time Notifications: User activity feeds, alerts Data Streaming: Log aggregation, metrics collection UI Updates: React to state changes across components Workflow Orchestration: Trigger actions based on events Cache Invalidation: Notify when data changes Basic Pub/Sub Implementation package main import ( "fmt" "sync" "time" ) // Message represents a pub/sub message type Message struct { Topic string Payload interface{} } // Subscriber represents a message handler type Subscriber func(Message) // PubSub is a simple in-memory pub/sub system type PubSub struct { mu sync....

Go Concurrency Patterns Series: ← Request/Response | Series Overview | Mutex Patterns → What is the Worker Pool Pattern? The Worker Pool pattern manages a fixed number of worker goroutines that process jobs from a shared queue. This pattern is essential for controlling resource usage, preventing system overload, and ensuring predictable performance under varying loads. Key Components: Job Queue: Channel containing work to be processed Worker Pool: Fixed number of worker goroutines Result Channel: Optional channel for collecting results Dispatcher: Coordinates job distribution to workers Real-World Use Cases Image Processing: Resize/compress images with limited CPU cores Database Operations: Limit concurrent database connections API Rate Limiting: Control outbound API call rates File Processing: Process files with bounded I/O operations Web Scraping: Limit concurrent HTTP requests Background Jobs: Process queued tasks with resource limits Basic Worker Pool Implementation package main import ( "fmt" "math/rand" "sync" "time" ) // Job represents work to be processed type Job struct { ID int Data interface{} } // Result represents the outcome of processing a job type Result struct { JobID int Output interface{} Error error } // WorkerPool manages a pool of workers type WorkerPool struct { workerCount int jobQueue chan Job resultQueue chan Result quit chan bool wg sync....