name: async-patterns description: Asynchronous programming patterns for Python, JavaScript/TypeScript, and other languages. Auto-triggers when implementing concurrent code, handling promises, or optimizing I/O operations.

Async Programming Patterns

Core Concepts

Event Loop

• Single-threaded execution model
• Non-blocking I/O operations
• Cooperative multitasking via yield points

When to Use Async

• I/O-bound operations (network, disk, database)
• High concurrency requirements
• Real-time applications (WebSockets)

When NOT to Use Async

• CPU-bound computation (use multiprocessing)
• Simple sequential scripts
• When overhead outweighs benefit

Python Async Patterns

Basic Pattern

import asyncio

async def fetch_data(url: str) -> dict:
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as response:
            return await response.json()

# Run concurrent requests
async def main():
    urls = ["url1", "url2", "url3"]
    results = await asyncio.gather(*[fetch_data(u) for u in urls])

Producer-Consumer Queue

async def producer(queue: asyncio.Queue):
    for item in items:
        await queue.put(item)
    await queue.put(None)  # Sentinel

async def consumer(queue: asyncio.Queue):
    while True:
        item = await queue.get()
        if item is None:
            break
        await process(item)
        queue.task_done()

Rate Limiting with Semaphore

semaphore = asyncio.Semaphore(10)  # Max 10 concurrent

async def rate_limited_request(url):
    async with semaphore:
        return await fetch(url)

Timeout Handling

try:
    result = await asyncio.wait_for(slow_operation(), timeout=5.0)
except asyncio.TimeoutError:
    handle_timeout()

JavaScript/TypeScript Patterns

Promise Patterns

// Parallel execution
const results = await Promise.all([fetch1(), fetch2(), fetch3()]);

// First to complete
const fastest = await Promise.race([fetch1(), fetch2()]);

// All settled (includes failures)
const outcomes = await Promise.allSettled([fetch1(), fetch2()]);

Async Iterator

async function* paginate(url: string) {
  let cursor: string | null = null;
  do {
    const { data, nextCursor } = await fetchPage(url, cursor);
    yield* data;
    cursor = nextCursor;
  } while (cursor);
}

for await (const item of paginate('/api/items')) {
  process(item);
}

Error Handling

// Good: Specific error handling
try {
  const data = await fetchData();
} catch (error) {
  if (error instanceof NetworkError) {
    await retry();
  } else if (error instanceof ValidationError) {
    logValidationError(error);
  } else {
    throw error;  // Re-throw unknown errors
  }
}

Cancellation

const controller = new AbortController();
const { signal } = controller;

// Cancel after 5 seconds
setTimeout(() => controller.abort(), 5000);

try {
  const response = await fetch(url, { signal });
} catch (error) {
  if (error.name === 'AbortError') {
    console.log('Request cancelled');
  }
}

Common Anti-Patterns

Sequential Awaits (Bad)

// BAD: Sequential execution
const a = await fetchA();
const b = await fetchB();
const c = await fetchC();

// GOOD: Parallel execution
const [a, b, c] = await Promise.all([fetchA(), fetchB(), fetchC()]);

Unhandled Promise Rejection

// BAD: Silent failure
fetchData().then(process);

// GOOD: Handle errors
fetchData().then(process).catch(handleError);
// OR
try {
  const data = await fetchData();
  process(data);
} catch (error) {
  handleError(error);
}

Blocking Event Loop

# BAD: Blocks event loop
def sync_heavy_computation():
    # CPU-bound work
    pass

# GOOD: Run in executor
result = await asyncio.get_event_loop().run_in_executor(
    None, sync_heavy_computation
)

Performance Tips

1. Connection pooling: Reuse connections
2. Batch operations: Group small requests
3. Backpressure: Limit queue sizes
4. Graceful shutdown: Cancel pending tasks on exit