sync

Go Concurrency Patterns Series: ← Worker Pool | Series Overview | WaitGroup Pattern → What are Mutex Patterns? Mutex (mutual exclusion) patterns are essential for protecting shared resources in concurrent programs. Go provides sync.Mutex and sync.RWMutex for controlling access to critical sections, ensuring data consistency and preventing race conditions. Key Types: Mutex: Exclusive access (one goroutine at a time) RWMutex: Reader-writer locks (multiple readers OR one writer) Lock-free: Atomic operations without explicit locks Real-World Use Cases Shared Counters: Statistics, metrics, rate limiting Cache Systems: Thread-safe caching with read/write operations Configuration Management: Safe updates to application config Connection Pools: Managing database/HTTP connection pools Resource Allocation: Tracking and managing limited resources State Machines: Protecting state transitions Basic Mutex Usage package main import ( "fmt" "sync" "time" ) // Counter demonstrates basic mutex usage type Counter struct { mu sync....

Go Concurrency Patterns Series: ← WaitGroup Pattern | Series Overview | Context Pattern → What is the Once Pattern? The Once pattern uses sync.Once to ensure that a piece of code executes exactly once, regardless of how many goroutines call it. This is essential for thread-safe initialization, singleton patterns, and one-time setup operations in concurrent programs. Key Characteristics: Thread-safe: Multiple goroutines can call it safely Exactly once: Code executes only on the first call Blocking: Subsequent calls wait for the first execution to complete No return values: The function passed to Do() cannot return values Real-World Use Cases Singleton Initialization: Create single instances of objects Configuration Loading: Load config files once at startup Database Connections: Initialize connection pools Logger Setup: Configure logging systems Resource Initialization: Set up expensive resources Feature Flags: Initialize feature flag systems Basic Once Usage package main import ( "fmt" "sync" "time" ) var ( instance *Database once sync....

Go Concurrency Patterns Series: ← Pub/Sub Pattern | Series Overview | Worker Pool → What is the Request/Response Pattern? The Request/Response pattern enables synchronous communication between goroutines, where a sender waits for a response from a receiver. This pattern is essential for RPC-style communication, database queries, API calls, and any scenario where you need to get a result back from an operation. Key Components: Request: Contains data and a response channel Response: Contains result data and/or error information Requester: Sends request and waits for response Responder: Processes request and sends response Real-World Use Cases Database Operations: Query execution with results API Gateways: Forwarding requests to microservices Cache Systems: Get/Set operations with confirmation File Operations: Read/Write with status feedback Validation Services: Input validation with results Authentication: Login requests with tokens Basic Request/Response Implementation package main import ( "fmt" "math/rand" "time" ) // Request represents a request with a response channel type Request struct { ID string Data interface{} Response chan Response } // Response represents the response to a request type Response struct { ID string Result interface{} Error error } // Server processes requests type Server struct { requests chan Request quit chan bool } // NewServer creates a new server func NewServer() *Server { return &Server{ requests: make(chan Request), quit: make(chan bool), } } // Start begins processing requests func (s *Server) Start() { go func() { for { select { case req := <-s....

Go Concurrency Patterns Series: ← Mutex Patterns | Series Overview | Once Pattern → What is the WaitGroup Pattern? The WaitGroup pattern uses sync.WaitGroup to coordinate the completion of multiple goroutines. It acts as a counter that blocks until all registered goroutines have finished executing, making it perfect for implementing barriers and waiting for parallel tasks to complete. Key Operations: Add(n): Increment the counter by n Done(): Decrement the counter by 1 (usually called with defer) Wait(): Block until counter reaches zero Real-World Use Cases Parallel Processing: Wait for all workers to complete Batch Operations: Process multiple items concurrently Service Initialization: Wait for all services to start Data Collection: Gather results from multiple sources Cleanup Operations: Ensure all cleanup tasks finish Testing: Coordinate test goroutines Basic WaitGroup Usage package main import ( "fmt" "math/rand" "sync" "time" ) // Task represents work to be done type Task struct { ID int Name string } // processTask simulates processing a task func processTask(task Task, wg *sync....