Concurrency Patterns
Table of Contents
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