python-async-ops

Python Async Patterns

Asyncio patterns for concurrent Python programming.

When to Use Async vs Sync

Use Async When	Use Sync When
I/O-bound operations (HTTP, DB, files)	CPU-bound computations
High concurrency (100s+ connections)	Simple scripts, one-off tasks
WebSocket/streaming connections	Small data processing
Microservices with network calls	Single sequential operations

Decision tree:

1. Is it CPU-bound? → Sync (or multiprocessing)
2. Is it I/O-bound with high concurrency? → Async
3. Is it simple I/O with few connections? → Sync is fine

Core Concepts

import asyncio

# Coroutine (must be awaited)
async def fetch(url: str) -> str:
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as response:
            return await response.text()

# Entry point
async def main():
    result = await fetch("https://example.com")
    return result

asyncio.run(main())

Pattern 1: Concurrent with gather

async def fetch_all(urls: list[str]) -> list[str]:
    """Fetch multiple URLs concurrently."""
    async with aiohttp.ClientSession() as session:
        tasks = [fetch_one(session, url) for url in urls]
        return await asyncio.gather(*tasks, return_exceptions=True)

Pattern 2: Bounded Concurrency

async def fetch_with_limit(urls: list[str], limit: int = 10):
    """Limit concurrent requests."""
    semaphore = asyncio.Semaphore(limit)

    async def bounded_fetch(url):
        async with semaphore:
            return await fetch_one(url)

    return await asyncio.gather(*[bounded_fetch(url) for url in urls])

Pattern 3: TaskGroup (Python 3.11+)

async def process_items(items):
    """Structured concurrency with automatic cleanup."""
    async with asyncio.TaskGroup() as tg:
        for item in items:
            tg.create_task(process_one(item))
    # All tasks complete here, or exception raised

Pattern 4: Timeout

async def with_timeout():
    try:
        async with asyncio.timeout(5.0):  # Python 3.11+
            result = await slow_operation()
    except asyncio.TimeoutError:
        result = None
    return result

Critical Warnings

# WRONG - blocks event loop
async def bad():
    time.sleep(5)         # Never use time.sleep!
    requests.get(url)     # Blocking I/O!

# CORRECT
async def good():
    await asyncio.sleep(5)
    async with aiohttp.ClientSession() as s:
        await s.get(url)

# WRONG - orphaned task
async def bad():
    asyncio.create_task(work())  # May be garbage collected!

# CORRECT - keep reference
async def good():
    task = asyncio.create_task(work())
    await task

Quick Reference

Pattern	Use Case
gather(*tasks)	Multiple independent operations
Semaphore(n)	Rate limiting, resource constraints
TaskGroup()	Structured concurrency (3.11+)
Queue()	Producer-consumer
timeout(s)	Timeout wrapper (3.11+)
Lock()	Shared mutable state

Async Context Manager

from contextlib import asynccontextmanager

@asynccontextmanager
async def managed_connection():
    conn = await create_connection()
    try:
        yield conn
    finally:
        await conn.close()

Additional Resources

For detailed patterns, load:

• ./references/concurrency-patterns.md - Queue, Lock, producer-consumer
• ./references/aiohttp-patterns.md - HTTP client/server patterns
• ./references/mixing-sync-async.md - run_in_executor, thread pools
• ./references/debugging-async.md - Debug mode, profiling, finding issues
• ./references/production-patterns.md - Graceful shutdown, health checks, signal handling
• ./references/error-handling.md - Retry with backoff, circuit breakers, partial failures
• ./references/performance.md - uvloop, connection pooling, buffer sizing

Scripts

• ./scripts/find-blocking-calls.sh - Scan code for blocking calls in async functions

Assets

• ./assets/async-project-template.py - Production-ready async app skeleton

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See Also

Prerequisites:

• python-typing-ops - Type hints for async functions

Related Skills:

• python-fastapi-ops - Async web APIs
• python-observability-ops - Async logging and tracing
• python-database-ops - Async database access