Concurrency Patterns

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

Overview

Implement safe concurrent code using proper synchronization primitives and patterns for parallel execution.

When to Use

• Multi-threaded applications
• Parallel data processing
• Race condition prevention
• Resource pooling
• Task coordination
• High-performance systems
• Async operations
• Worker pools

Quick Start

Minimal working example:

class PromisePool {
  private queue: Array<() => Promise<any>> = [];
  private active = 0;

  constructor(private concurrency: number) {}

  async add<T>(fn: () => Promise<T>): Promise<T> {
    while (this.active >= this.concurrency) {
      await this.waitForSlot();
    }

    this.active++;

    try {
      return await fn();
    } finally {
      this.active--;
    }
  }

  private async waitForSlot(): Promise<void> {
    return new Promise((resolve) => {
      const checkSlot = () => {
        if (this.active < this.concurrency) {
          resolve();
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide	Contents
Promise Pool (TypeScript)	Promise Pool (TypeScript)
Mutex and Semaphore (TypeScript)	Mutex and Semaphore (TypeScript)
Worker Pool (Node.js)	Worker Pool (Node.js)
Python Threading Patterns	Python Threading Patterns
Async Patterns (Python asyncio)	Async Patterns (Python asyncio)
Go-Style Channels (Simulation)	Go-Style Channels (Simulation)

Best Practices

✅ DO

• Use proper synchronization primitives
• Limit concurrency to avoid resource exhaustion
• Handle errors in concurrent operations
• Use immutable data when possible
• Test concurrent code thoroughly
• Profile concurrent performance
• Document thread-safety guarantees

❌ DON'T

• Share mutable state without synchronization
• Use sleep/polling for coordination
• Create unlimited threads/workers
• Ignore race conditions
• Block event loops in async code
• Forget to clean up resources