async-python-patterns
本技能提供全面的指南,用于实现高性能的异步 Python 应用程序,利用 `asyncio`、并发编程和 `async/await` 模式。它对于希望构建异步 Web API、实时应用或优化 I/O 密集型工作负载的开发者至关重要,能够显著提升应用程序的响应速度和资源利用率。
npx skills add https://github.com/wshobson/agents --skill async-python-patternsBefore / After 效果对比
1 组在传统同步模式下,处理大量并发I/O密集型任务(如数据库查询或外部API调用)时,请求会阻塞执行,导致总处理时间线性增长,系统响应缓慢,资源利用率低下。
通过应用异步Python模式,系统能够高效地并发处理数千个I/O请求,显著减少总等待时间,提升吞吐量和响应速度,从而实现资源的最大化利用。
Async Python Patterns
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
When to Use This Skill
- Building async web APIs (FastAPI, aiohttp, Sanic)
- Implementing concurrent I/O operations (database, file, network)
- Creating web scrapers with concurrent requests
- Developing real-time applications (WebSocket servers, chat systems)
- Processing multiple independent tasks simultaneously
- Building microservices with async communication
- Optimizing I/O-bound workloads
- Implementing async background tasks and queues
Sync vs Async Decision Guide
Before adopting async, consider whether it's the right choice for your use case.
| Use Case | Recommended Approach |
|---|---|
| Many concurrent network/DB calls | asyncio |
| CPU-bound computation | multiprocessing or thread pool |
| Mixed I/O + CPU | Offload CPU work with asyncio.to_thread() |
| Simple scripts, few connections | Sync (simpler, easier to debug) |
| Web APIs with high concurrency | Async frameworks (FastAPI, aiohttp) |
Key Rule: Stay fully sync or fully async within a call path. Mixing creates hidden blocking and complexity.
Core Concepts
1. Event Loop
The event loop is the heart of asyncio, managing and scheduling asynchronous tasks.
Key characteristics:
- Single-threaded cooperative multitasking
- Schedules coroutines for execution
- Handles I/O operations without blocking
- Manages callbacks and futures
2. Coroutines
Functions defined with async def that can be paused and resumed.
Syntax:
async def my_coroutine():
result = await some_async_operation()
return result
3. Tasks
Scheduled coroutines that run concurrently on the event loop.
4. Futures
Low-level objects representing eventual results of async operations.
5. Async Context Managers
Resources that support async with for proper cleanup.
6. Async Iterators
Objects that support async for for iterating over async data sources.
Quick Start
import asyncio
async def main():
print("Hello")
await asyncio.sleep(1)
print("World")
# Python 3.7+
asyncio.run(main())
Fundamental Patterns
Pattern 1: Basic Async/Await
import asyncio
async def fetch_data(url: str) -> dict:
"""Fetch data from URL asynchronously."""
await asyncio.sleep(1) # Simulate I/O
return {"url": url, "data": "result"}
async def main():
result = await fetch_data("https://api.example.com")
print(result)
asyncio.run(main())
Pattern 2: Concurrent Execution with gather()
import asyncio
from typing import List
async def fetch_user(user_id: int) -> dict:
"""Fetch user data."""
await asyncio.sleep(0.5)
return {"id": user_id, "name": f"User {user_id}"}
async def fetch_all_users(user_ids: List[int]) -> List[dict]:
"""Fetch multiple users concurrently."""
tasks = [fetch_user(uid) for uid in user_ids]
results = await asyncio.gather(*tasks)
return results
async def main():
user_ids = [1, 2, 3, 4, 5]
users = await fetch_all_users(user_ids)
print(f"Fetched {len(users)} users")
asyncio.run(main())
Pattern 3: Task Creation and Management
import asyncio
async def background_task(name: str, delay: int):
"""Long-running background task."""
print(f"{name} started")
await asyncio.sleep(delay)
print(f"{name} completed")
return f"Result from {name}"
async def main():
# Create tasks
task1 = asyncio.create_task(background_task("Task 1", 2))
task2 = asyncio.create_task(background_task("Task 2", 1))
# Do other work
print("Main: doing other work")
await asyncio.sleep(0.5)
# Wait for tasks
result1 = await task1
result2 = await task2
print(f"Results: {result1}, {result2}")
asyncio.run(main())
Pattern 4: Error Handling in Async Code
import asyncio
from typing import List, Optional
async def risky_operation(item_id: int) -> dict:
"""Operation that might fail."""
await asyncio.sleep(0.1)
if item_id % 3 == 0:
raise ValueError(f"Item {item_id} failed")
return {"id": item_id, "status": "success"}
async def safe_operation(item_id: int) -> Optional[dict]:
"""Wrapper with error handling."""
try:
return await risky_operation(item_id)
except ValueError as e:
print(f"Error: {e}")
return None
async def process_items(item_ids: List[int]):
"""Process multiple items with error handling."""
tasks = [safe_operation(iid) for iid in item_ids]
results = await asyncio.gather(*tasks, return_exceptions=True)
# Filter out failures
successful = [r for r in results if r is not None and not isinstance(r, Exception)]
failed = [r for r in results if isinstance(r, Exception)]
print(f"Success: {len(successful)}, Failed: {len(failed)}")
return successful
asyncio.run(process_items([1, 2, 3, 4, 5, 6]))
Pattern 5: Timeout Handling
import asyncio
async def slow_operation(delay: int) -> str:
"""Operation that takes time."""
await asyncio.sleep(delay)
return f"Completed after {delay}s"
async def with_timeout():
"""Execute operation with timeout."""
try:
result = await asyncio.wait_for(slow_operation(5), timeout=2.0)
print(result)
except asyncio.TimeoutError:
print("Operation timed out")
asyncio.run(with_timeout())
Detailed worked examples and patterns
Detailed sections (starting with ## Advanced Patterns) live in references/details.md. Read that file when the navigation summary above is insufficient.
Common Pitfalls
1. Forgetting await
# Wrong - returns coroutine object, doesn't execute
result = async_function()
# Correct
result = await async_function()
2. Blocking the Event Loop
# Wrong - blocks event loop
import time
async def bad():
time.sleep(1) # Blocks!
# Correct
async def good():
await asyncio.sleep(1) # Non-blocking
3. Not Handling Cancellation
async def cancelable_task():
"""Task that handles cancellation."""
try:
while True:
await asyncio.sleep(1)
print("Working...")
except asyncio.CancelledError:
print("Task cancelled, cleaning up...")
# Perform cleanup
raise # Re-raise to propagate cancellation
4. Mixing Sync and Async Code
# Wrong - can't call async from sync directly
def sync_function():
result = await async_function() # SyntaxError!
# Correct
def sync_function():
result = asyncio.run(async_function())
Testing Async Code
import asyncio
import pytest
# Using pytest-asyncio
@pytest.mark.asyncio
async def test_async_function():
"""Test async function."""
result = await fetch_data("https://api.example.com")
assert result is not None
@pytest.mark.asyncio
async def test_with_timeout():
"""Test with timeout."""
with pytest.raises(asyncio.TimeoutError):
await asyncio.wait_for(slow_operation(5), timeout=1.0)
用户评价 (0)
发表评价
暂无评价
统计数据
用户评分
为此 Skill 评分