python-async-patterns
Python asyncio patterns for concurrent programming. Triggers on: asyncio, async, await, coroutine, gather, semaphore, TaskGroup, event loop, aiohttp, concurrent.
Best use case
python-async-patterns is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Python asyncio patterns for concurrent programming. Triggers on: asyncio, async, await, coroutine, gather, semaphore, TaskGroup, event loop, aiohttp, concurrent.
Teams using python-async-patterns should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/python-async-patterns/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How python-async-patterns Compares
| Feature / Agent | python-async-patterns | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Python asyncio patterns for concurrent programming. Triggers on: asyncio, async, await, coroutine, gather, semaphore, TaskGroup, event loop, aiohttp, concurrent.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Python Async Patterns
Asyncio patterns for concurrent Python programming.
## Core Concepts
```python
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
```python
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
```python
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+)
```python
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
```python
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
```python
# 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)
```
```python
# 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
```python
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
---
## See Also
**Prerequisites:**
- `python-typing-patterns` - Type hints for async functions
**Related Skills:**
- `python-fastapi-patterns` - Async web APIs
- `python-observability-patterns` - Async logging and tracing
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