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asyncio — Claude Code skill: async/await concurrency in Python

A Python asyncio skill covering coroutines, tasks, the event loop, aiohttp and async FastAPI endpoints. Useful when code waits on network or database.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add bobmatnyc/claude-mpm-skills --skill asyncio -a claude-code
Open on GitHub

What asyncio does

The skill hands your agent a reference for concurrent Python: how to declare async def, where await belongs, why asyncio.gather() beats sequential calls, how to spin up background work with asyncio.create_task(). Separate sections cover primitives such as locks, semaphores and queues, error handling with return_exceptions=True, and running blocking code without stalling the loop.

Examples target real libraries: an HTTP client on aiohttp, asyncpg, aiomysql and motor for PostgreSQL, MySQL and MongoDB, async FastAPI endpoints, and tests with pytest-asyncio. The quick start is five steps — define the coroutine, await the operation, run it with asyncio.run(), collect parallel tasks in gather(), wrap the risky part in try/except. asyncio itself ships with Python 3.7 and later, but aiohttp, the database drivers and pytest-asyncio are separate installs, so check they are already in your project dependencies.

The skill is marked user-invocable: false and disable-model-invocation: true, meaning it loads as reference material on the topic rather than a command you type. Its context budget is 700 tokens, so the agent gets a condensed version instead of the full document.

What it helps with

  • run parallel HTTP requests instead of one after another
  • start a background task without blocking the main loop
  • collect results from several coroutines with gather
  • catch a failure in one task without killing the rest
  • write an async FastAPI endpoint that queries a database

Example prompts for the agent

  • Show me how to fire parallel API calls with asyncio.gather()
  • Rewrite this blocking call as async with aiohttp
  • How do I cancel a background task in asyncio?

How to install asyncio

1Skills CLI (Vercel)

npx skills add bobmatnyc/claude-mpm-skills --skill asyncio -a claude-code

2Manually: put the files in place

~/.claude/skills/asyncio/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/asyncio/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about asyncio

How do I install asyncio in Claude?

Run npx skills add bobmatnyc/claude-mpm-skills --skill asyncio -a claude-code. The skill file then lives at ~/.claude/skills/asyncio/SKILL.md.

What does the asyncio skill do?

It gives the agent patterns and examples for async/await: coroutines, tasks, the event loop, synchronization primitives, aiohttp, async database drivers and FastAPI.

Do I need extra packages for the skill to work?

asyncio is built into Python 3.7 and later. The HTTP, database and testing examples need aiohttp, asyncpg, aiomysql, motor, fastapi with uvicorn, and pytest-asyncio.

Source text

SKILL.md · MIT
---
name: asyncio
description: Python asyncio - Modern concurrent programming with async/await, event loops, tasks, coroutines, primitives, aiohttp, and FastAPI async patterns
user-invocable: false
disable-model-invocation: true
version: 1.0.0
category: toolchain
author: Claude MPM Team
license: MIT
progressive_disclosure:
  entry_point:
    summary: "Async/await concurrency: coroutines, tasks, event loops, async HTTP (aiohttp), async DB, FastAPI async, locks, queues, error handling"
    when_to_use: "Concurrent I/O operations, HTTP clients/servers, database access, WebSocket handling, parallel API calls, background tasks, real-time systems"
    quick_start: "1. Define async def functions 2. Await async operations 3. Run with asyncio.run() 4. Use asyncio.gather() for parallel tasks 5. Handle errors with try/except"
context_limit: 700
tags:
  - asyncio
  - async
  - concurrency
  - coroutines
  - aiohttp
  - fastapi
  - async-database
  - event-loop
  - tasks
requires_tools: []
---

# Python asyncio - Async/Await Concurrency

## Overview

Python's asyncio library enables writing concurrent code using async/await syntax. It's ideal for I/O-bound operations like HTTP requests, database queries, file operations, and WebSocket connections. asyncio provides non-blocking execution without the complexity of threading or multiprocessing.

**Key Features**:
- async/await syntax for readable concurrent code
- Event loop for managing concurrent operations
- Tasks for running multiple coroutines concurrently
- Primitives: locks, semaphores, events, queues
- HTTP client/server with aiohttp
- Database async support (asyncpg, aiomysql, motor)
- FastAPI async endpoints
- WebSocket support
- Background task management

**Installation**:
```bash
# asyncio is built-in (Python 3.7+)

# Async HTTP client
pip install aiohttp

# Async HTTP requests (alternative)
pip install httpx

# Async database drivers
pip install asyncpg aiomysql motor  # PostgreSQL, MySQL, MongoDB

# FastAPI with async support
pip install fastapi uvicorn[standard]

# Async testing
pip install pytest-asyncio
```

## Basic Async/Await Patterns

### 1. Simple Async Function

```python
import asyncio

async def hello():
    """Basic async function (coroutine)."""
    print("Hello")
    await asyncio.sleep(1)  # Async sleep (non-blocking)
    print("World")
    return "Done"

# Run async function
result = asyncio.run(hello())
print(result)  # "Done"
```

**Key Points**:
- `async def` defines a coroutine function
- `await` suspends execution until awaitable completes
- `asyncio.run()` is the entry point for async programs
- Coroutines must be awaited or scheduled

### 2. Multiple Concurrent Tasks

```python
import asyncio
import time

async def task(name, duration):
    """Simulate async task."""
    print(f"{name}: Starting (duration: {duration}s)")
    await asyncio.sleep(duration)
    print(f"{name}: Complete")
    return f"{name} result"

async def run_concurrent():
    """Run multiple tasks concurrently."""
    start = time.time()

    # Sequential (slow) - 6 seconds total
    # result1 = await task("Task 1", 3)
    # result2 = await task("Task 2", 2)
    # result3 = await task("Task 3", 1)

    # Concurrent (fast) - 3 seconds total
    results = await asyncio.gather(
        task("Task 1", 3),
        task("Task 2", 2),
        task("Task 3", 1)
    )

    elapsed = time.time() - start
    print(f"Total time: {elapsed:.2f}s")
    print(f"Results: {results}")

asyncio.run(run_concurrent())
# Output: Total time: 3.00s (tasks ran concurrently)
```

### 3. Task Creation and Management

```python
import asyncio

async def background_task(name):
    """Long-running background task."""
    for i in range(5):
        print(f"{name}: iteration {i}")
        await asyncio.sleep(1)
    return f"{name} complete"

async def main():
    # Create task (starts immediately)
    task1 = asyncio.create_task(background_task("Task-1"))
    task2 = asyncio.create_task(background_task("Task-2"))

    # Do other work while tasks run
    print("Main: doing other work")
    await asyncio.sleep(2)

    # Wait for tasks to complete
    result1 = await task1
    result2 = await task2

    print(f"Results: {result1}, {result2}")

asyncio.run(main())
```

### 4. Error Handling in Async Code

```python
import asyncio

async def risky_operation(fail=False):
    """Operation that might fail."""
    await asyncio.sleep(1)
    if fail:
        raise ValueError("Operation failed")
    return "Success"

async def handle_errors():
    # Individual try/except
    try:
        result = await risky_operation(fail=True)
    except ValueError as e:
        print(f"Caught error: {e}")
        result = "Fallback value"

    # Gather with error handling
    results = await asyncio.gather(
        risky_operation(fail=False),
        risky_operation(fail=True),
        risky_operation(fail=False),
        return_exceptions=True  # Return exceptions instead of raising
    )

    for i, result in enumerate(results):
        if isinstance(result, Exception):
            print(f"Task {i} failed: {result}")
        else:
            print(f"Task {i} succeeded: {result}")

asyncio.run(handle_errors())
```

## Event Loop Fundamentals

### 1. Event Loop Lifecycle

```python
import asyncio

# Modern approach (Python 3.7+)
async def main():
    print("Main coroutine")
    await asyncio.sleep(1)

asyncio.run(main())  # Creates loop, runs main, closes loop

# Manual loop management (advanced use cases)
async def manual_example():
    loop = asyncio.get_event_loop()

    # Schedule coroutine
    task = loop.create_task(some_coroutine())

    # Schedule callback
    loop.call_later(5, callback_function)

    # Run until complete
    result = await task

    return result

# Get current event loop
async def get_current_loop():
    loop = asyncio.get_running_loop()
    print(f"Loop: {loop}")

    # Schedule callback in event loop
    loop.call_soon(lambda: print("Callback executed"))

    await asyncio.sleep(0)  # Let callback execute
```

### 2. Loop Scheduling and Callbacks

```python
import asyncio
from datetime import datetime

def callback(name, loop):
    """Callback function (not async)."""
    print(f"{datetime.now()}: {name} callback executed")

    # Stop loop after callback
    # loop.stop()

async def schedule_callbacks():
    loop = asyncio.get_running_loop()

    # Schedule immediate callback
    loop.call_soon(callback, "Immediate", loop)

    # Schedule callback after delay
    loop.call_later(2, callback, "Delayed 2s", loop)

    # Schedule callback at specific time
    loop.call_at(loop.time() + 3, callback, "Delayed 3s", loop)

    # Wait for callbacks to execute
    await asyncio.sleep(5)

asyncio.run(schedule_callbacks())
```

### 3. Running Blocking Code

```python
import asyncio
import time

def blocking_io():
    """CPU-intensive or blocking I/O operation."""
    print("Blocking operation started")
    time.sleep(2)  # Blocks thread
    print("Blocking operation complete")
    return "Blocking result"

async def run_in_executor():
    """Run blocking code in thread pool."""
    loop = asyncio.get_running_loop()

    # Run in default executor (thread pool)
    result = await loop.run_in_executor(
        None,  # Use default executor
        blocking_io
    )

    print(f"Result: {result}")

# Run blocking operations concurrently
async def concurrent_blocking():
    loop = asyncio.get_running_loop()

    # These run in thread pool, don't block event loop
    results = await asyncio.gather(
        loop.run_in_executor(None, blocking_io),
        loop.run_in_executor(None, blocking_io),
        loop.run_in_executor(None, blocking_io)
    )

    print(f"All results: {results}")

asyncio.run(concurrent_blocking())
```

## Asyncio Primitives

### 1. Locks for Mutual Exclusion

```python
import asyncio

# Shared resource
counter = 0
lock = asyncio.Lock()

async def increment_with_lock(name):
    """Increment counter with lock protection."""
    global counter

    async with lock:
        # Critical section - only one task at a time
        print(f"{name}: acquired lock")
        current = counter
        await asyncio.sleep(0.1)  # Simulate processing
        counter = current + 1
        print(f"{name}: released lock, counter={counter}")

async def increment_without_lock(name):
    """Increment without lock - race condition!"""
    global counter

    current = counter
    await asyncio.sleep(0.1)  # Race condition window
    counter = current + 1
    print(f"{name}: counter={counter}")

async def test_locks():
    global counter

    # Without lock (race condition)
    counter = 0
    await asyncio.gather(
        increment_without_lock("Task-1"),
        increment_without_lock("Task-2"),
        increment_without_lock("Task-3")
    )
    print(f"Without lock: {counter}")  # Often wrong (< 3)

    # With lock (correct)
    counter = 0
    await asyncio.gather(
        increment_with_lock("Task-1"),
        increment_with_lock("Task-2"),
        increment_with_lock("Task-3")
    )
    print(f"With lock: {counter}")  # Always 3

asyncio.run(test_locks())
```

### 2. Semaphores for Resource Limiting

```python
import asyncio

# Limit concurrent operations
semaphore = asyncio.Semaphore(2)  # Max 2 concurrent

async def limited_operation(name):
    """Operation limited by semaphore."""
    print(f"{name}: waiting for semaphore")

    async with semaphore:
        print(f"{name}: acquired semaphore")
        await asyncio.sleep(2)  # Simulate work
        print(f"{name}: releasing semaphore")

async def test_semaphore():
    # Create 5 tasks, but only 2 run concurrently
    await asyncio.gather(
        limited_operation("Task-1"),
        limited_operation("Task-2"),
        limited_operation("Task-3"),
        limited_operation("Task-4"),
        limited_operation("Task-5")
    )

asyncio.run(test_semaphore())
# Only 2 tasks hold semaphore at any time
```

### 3. Events for Signaling

```python
import asyncio

event = asyncio.Event()

async def waiter(name):
    """Wait for event to be set."""
    print(f"{name}: waiting for event")
    await event.wait()  # Block until event is set
    print(f"{name}: event received!")

async def setter():
    """Set event after delay."""
    await asyncio.sleep(2)
    print("Setter: setting event")
    event.set()  # Wake up all waiters

async def test_event():
    # Create waiters
    await asyncio.gather(
        waiter("Waiter-1"),
        waiter("Waiter-2"),
        waiter("Waiter-3"),
        setter()
    )

asyncio.run(test_event())
```

### 4. Queues for Task Distribution

```python
import asyncio
import random

async def producer(queue, name):
    """Produce items and add to queue."""
    for i in range(5):
        item = f"{name}-item-{i}"
        await queue.put(item)
        print(f"{name}: produced {item}")
        await asyncio.sleep(random.uniform(0.1, 0.5))

    # Signal completion
    await queue.put(None)

async def consumer(queue, name):
    """Consume items from queue."""
    while True:
        item = await queue.get()  # Block until item available

        if item is None:  # Shutdown signal
            queue.task_done()
            break

        print(f"{name}: consumed {item}")
        await asyncio.sleep(random.uniform(0.2, 0.8))
        queue.task_done()

async def test_queue():
    queue = asyncio.Queue(maxsize=10)

    # Create producers and consumers
    await asyncio.gather(
        producer(queue, "Producer-1"),
        producer(queue, "Producer-2"),
        consumer(queue, "Consumer-1"),
        consumer(queue, "Consumer-2"),
        consumer(queue, "Consumer-3")
    )

    # Wait for all items to be processed
    await queue.join()
    print("All tasks complete")

asyncio.run(test_queue())
```

### 5. Condition Variables

```python
import asyncio

condition = asyncio.Condition()
items = []

async def consumer(name):
    """Wait for items to be available."""
    async with condition:
        # Wait until items are available
        await condition.wait_for(lambda: len(items) > 0)

        item = items.pop(0)
        print(f"{name}: consumed {item}")

async def producer(name):
    """Add items and notify consumers."""
    async with condition:
        item = f"{name}-item"
        items.append(item)
        print(f"{name}: produced {item}")

        # Notify one waiting consumer
        condition.notify(n=1)
        # Or notify all: condition.notify_all()

async def test_condition():
    await asyncio.gather(
        consumer("Consumer-1"),
        consumer("Consumer-2"),
        producer("Producer-1"),
        producer("Producer-2")
    )

asyncio.run(test_condition())
```

## Async HTTP with aiohttp

### 1. Basic HTTP Client

```python
import asyncio
import aiohttp

async def fetch_url(session, url):
    """Fetch single URL."""
    async with session.get(url) as response:
        status = response.status
        text = await response.text()
        return {"url": url, "status": status, "length": len(text)}

async def fetch_multiple_urls():
    """Fetch multiple URLs concurrently."""
    urls = [
        "https://httpbin.org/delay/1",
        "https://httpbin.org/delay/2",
        "https://httpbin.org/json",
    ]

    async with aiohttp.ClientSession() as session:
        # Concurrent requests
        tasks = [fetch_url(session, url) for url in urls]
        results = await asyncio.gather(*tasks)

        for result in results:
            print(f"{result['url']}: {result['status']} ({result['length']} bytes)")

asyncio.run(fetch_multiple_urls())
```

### 2. HTTP Client with Error Handling

```python
import asyncio
import aiohttp
from typing import Dict, Any

async def fetch_with_retry(
    session: aiohttp.ClientSession,
    url: str,
    max_retries: int = 3
) -> Dict[str, Any]:
    """Fetch URL with retry logic."""
    for attempt in range(max_retries):
        try:
            async with session.get(url, timeout=aiohttp.ClientTimeout(total=10)) as response:
                response.raise_for_status()  # Raise for 4xx/5xx
                data = await response.json()
                return {"success": True, "data": data}

        except aiohttp.ClientError as e:
            print(f"Attempt {attempt + 1} failed: {e}")
            if attempt == max_retries - 1:
                return {"success": False, "error": str(e)}

            # Exponential backoff
            await asyncio.sleep(2 ** attempt)

        except asyncio.TimeoutError:
            print(f"Attempt {attempt + 1} timed out")
            if attempt == max_retries - 1:
                return {"success": False, "error": "Timeout"}

            await asyncio.sleep(2 ** attempt)

async def parallel_api_calls():
    """Make parallel API calls with error handling."""
    urls = [
        "https://httpbin.org/json",
        "https://httpbin.org/status/500",  # Will fail
        "https://httpbin.org/delay/1",
    ]

    async with aiohttp.ClientSession() as session:
        results = await asyncio.gather(
            *[fetch_with_retry(session, url) for url in urls],
            return_exceptions=True  # Don't stop on errors
        )

        for url, result in zip(urls, results):
            if isinstance(result, Exception):
                print(f"{url}: Exception - {result}")
            elif result["success"]:
                print(f"{url}: Success")
            else:
                print(f"{url}: Failed - {result['error']}")

asyncio.run(parallel_api_calls())
```

### 3. HTTP Server with aiohttp

```python
from aiohttp import web
import asyncio

async def handle_hello(request):
    """Simple GET handler."""
    name = request.query.get("name", "World")
    return web.json_response({"message": f"Hello, {name}!"})

async def handle_post(request):
    """POST handler with JSON body."""
    data = await request.json()

    # Simulate async processing
    await asyncio.sleep(1)

    return web.json_response({
        "received": data,
        "status": "processed"
    })

async def handle_stream(request):
    """Streaming response."""
    response = web.StreamResponse()
    await response.prepare(request)

    for i in range(10):
        await response.write(f"Chunk {i}\n".encode())
        await asyncio.sleep(0.5)

    await response.write_eof()
    return response

# Create application
app = web.Application()
app.router.add_get("/hello", handle_hello)
app.router.add_post("/process", handle_post)
app.router.add_get("/stream", handle_stream)

# Run server
if __name__ == "__main__":
    web.run_app(app, host="0.0.0.0", port=8080)
```

### 4. WebSocket Client

```python
import asyncio
import aiohttp

async def websocket_client():
    """Connect to WebSocket server."""
    url = "wss://echo.websocket.org"

    async with aiohttp.ClientSession() as session:
        async with session.ws_connect(url) as ws:
            # Send messages
            await ws.send_str("Hello WebSocket")
            await ws.send_json({"type": "greeting", "data": "test"})

            # Receive messages
            async for msg in ws:
                if msg.type == aiohttp.WSMsgType.TEXT:
                    print(f"Received: {msg.data}")

                    if msg.data == "close":
                        await ws.close()
                        break

                elif msg.type == aiohttp.WSMsgType.ERROR:
                    print(f"Error: {ws.exception()}")
                    break

asyncio.run(websocket_client())
```

## Async Database Operations

### 1. PostgreSQL with asyncpg

```python
import asyncio
import asyncpg

async def database_operations():
    """Async PostgreSQL operations."""
    # Create connection pool
    pool = await asyncpg.create_pool(
        host="localhost",
        database="mydb",
        user="user",
        password="password",
        min_size=5,
        max_size=20
    )

    try:
        # Acquire connection from pool
        async with pool.acquire() as conn:
            # Execute query
            rows = await conn.fetch(
                "SELECT id, name, email FROM users WHERE active = $1",
                True
            )

            for row in rows:
                print(f"User: {row['name']} ({row['email']})")

            # Insert data
            await conn.execute(
                "INSERT INTO users (name, email) VALUES ($1, $2)",
                "Alice", "[email protected]"
            )

            # Transaction
            async with conn.transaction():
                await conn.execute("UPDATE users SET active = $1 WHERE id = $2", False, 1)
                await conn.execute("INSERT INTO audit_log (action) VALUES ($1)", "deactivate")

    finally:
        await pool.close()

asyncio.run(database_operations())
```

### 2. MongoDB with motor

```python
import asyncio
from motor.motor_asyncio import AsyncIOMotorClient

async def mongodb_operations():
    """Async MongoDB operations."""
    # Create client
    client = AsyncIOMotorClient("mongodb://localhost:27017")
    db = client.mydb
    collection = db.users

    try:
        # Insert document
        result = await collection.insert_one({
            "name": "Alice",
            "email": "[email protected]",
            "age": 30
        })
        print(f"Inserted ID: {result.inserted_id}")

        # Find documents
        cursor = collection.find({"age": {"$gte": 25}})
        async for document in cursor:
            print(f"User: {document['name']}")

        # Update document
        await collection.update_one(
            {"name": "Alice"},
            {"$set": {"age": 31}}
        )

        # Aggregation pipeline
        pipeline = [
            {"$match": {"age": {"$gte": 25}}},
            {"$group": {"_id": None, "avg_age": {"$avg": "$age"}}}
        ]
        async for result in collection.aggregate(pipeline):
            print(f"Average age: {result['avg_age']}")

    finally:
        client.close()

asyncio.run(mongodb_operations())
```

### 3. Connection Pool Pattern

```python
import asyncio
import asyncpg
from typing import Optional

class DatabasePool:
    """Async database connection pool manager."""

    def __init__(self, dsn: str):
        self.dsn = dsn
        self.pool: Optional[asyncpg.Pool] = None

    async def connect(self):
        """Create connection pool."""
        self.pool = await asyncpg.create_pool(self.dsn, min_size=5, max_size=20)

    async def close(self):
        """Close connection pool."""
        if self.pool:
            await self.pool.close()

    async def execute(self, query: str, *args):
        """Execute query."""
        async with self.pool.acquire() as conn:
            return await conn.execute(query, *args)

    async def fetch(self, query: str, *args):
        """Fetch multiple rows."""
        async with self.pool.acquire() as conn:
            return await conn.fetch(query, *args)

    async def fetchrow(self, query: str, *args):
        """Fetch single row."""
        async with self.pool.acquire() as conn:
            return await conn.fetchrow(query, *args)

# Usage
async def use_pool():
    db = DatabasePool("postgresql://user:pass@localhost/mydb")
    await db.connect()

    try:
        # Execute operations
        rows = await db.fetch("SELECT * FROM users")
        for row in rows:
            print(row)
    finally:
        await db.close()

asyncio.run(use_pool())
```

## FastAPI Async Patterns

### 1. Async Endpoints

```python
from fastapi import FastAPI, HTTPException
import asyncio
import httpx

app = FastAPI()

@app.get("/")
async def root():
    """Simple async endpoint."""
    return {"message": "Hello World"}

@app.get("/delay/{seconds}")
async def delayed_response(seconds: int):
    """Endpoint with async delay."""
    await asyncio.sleep(seconds)
    return {"message": f"Waited {seconds} seconds"}

@app.get("/fetch")
async def fetch_external():
    """Fetch data from external API."""
    async with httpx.AsyncClient() as client:
        response = await client.get("https://httpbin.org/json")
        return response.json()

@app.get("/parallel")
async def parallel_requests():
    """Make parallel API calls."""
    async with httpx.AsyncClient() as client:
        responses = await asyncio.gather(
            client.get("https://httpbin.org/delay/1"),
            client.get("https://httpbin.org/delay/2"),
            client.get("https://httpbin.org/json")
        )

        return {
            "results": [r.json() for r in responses]
        }
```

### 2. Background Tasks

```python
from fastapi import FastAPI, BackgroundTasks
import asyncio

app = FastAPI()

async def send_email(email: str, message: str):
    """Simulate sending email."""
    print(f"Sending email to {email}")
    await asyncio.sleep(5)  # Simulate slow email service
    print(f"Email sent to {email}: {message}")

@app.post("/send-notification")
async def send_notification(
    email: str,
    message: str,
    background_tasks: BackgroundTasks
):
    """Send notification in background."""
    # Add task to background
    background_tasks.add_task(send_email, email, message)

    # Return immediately
    return {"status": "notification queued"}

# Alternative: manual task creation
@app.post("/send-notification-manual")
async def send_notification_manual(email: str, message: str):
    """Create background task manually."""
    asyncio.create_task(send_email(email, message))
    return {"status": "notification queued"}
```

### 3. Async Dependencies

```python
from fastapi import FastAPI, Depends
import asyncpg

app = FastAPI()

# Database pool (global)
db_pool = None

async def get_db():
    """Dependency: database connection."""
    async with db_pool.acquire() as conn:
        yield conn

@app.on_event("startup")
async def startup():
    """Initialize database pool on startup."""
    global db_pool
    db_pool = await asyncpg.create_pool(
        "postgresql://user:pass@localhost/mydb"
    )

@app.on_event("shutdown")
async def shutdown():
    """Close database pool on shutdown."""
    await db_pool.close()

@app.get("/users/{user_id}")
async def get_user(user_id: int, conn=Depends(get_db)):
    """Get user with async database dependency."""
    user = await conn.fetchrow(
        "SELECT * FROM users WHERE id = $1",
        user_id
    )

    if not user:
        raise HTTPException(status_code=404, detail="User not found")

    return dict(user)
```

### 4. WebSocket Endpoints

```python
from fastapi import FastAPI, WebSocket, WebSocketDisconnect
from typing import List
import asyncio

app = FastAPI()

# Active connections
active_connections: List[WebSocket] = []

@app.websocket("/ws")
async def websocket_endpoint(websocket: WebSocket):
    """WebSocket endpoint."""
    await websocket.accept()
    active_connections.append(websocket)

    try:
        while True:
            # Receive message
            data = await websocket.receive_text()

            # Broadcast to all connections
            for connection in active_connections:
                await connection.send_text(f"Broadcast: {data}")

    except WebSocketDisconnect:
        active_connections.remove(websocket)
        print("Client disconnected")

# Background task to send periodic updates
async def broadcast_updates():
    """Send periodic updates to all clients."""
    while True:
        await asyncio.sleep(5)

        for connection in active_connections:
            try:
                await connection.send_text("Periodic update")
            except:
                active_connections.remove(connection)

@app.on_event("startup")
async def startup():
    """Start background update task."""
    asyncio.create_task(broadcast_updates())
```

## Common Patterns and Best Practices

### 1. Timeout Handling

```python
import asyncio

async def slow_operation():
    """Slow operation."""
    await asyncio.sleep(10)
    return "Result"

async def with_timeout():
    """Run operation with timeout."""
    try:
        result = await asyncio.wait_for(slow_operation(), timeout=5.0)
        print(f"Result: {result}")

    except asyncio.TimeoutError:
        print("Operation timed out")

asyncio.run(with_timeout())
```

### 2. Cancellation Handling

```python
import asyncio

async def cancellable_task():
    """Task that can be cancelled."""
    try:
        for i in range(10):
            print(f"Working: {i}")
            await asyncio.sleep(1)

        return "Complete"

    except asyncio.CancelledError:
        print("Task was cancelled")
        # Cleanup
        raise  # Re-raise to propagate cancellation

async def cancel_example():
    """Example of task cancellation."""
    task = asyncio.create_task(cancellable_task())

    # Let it run for a bit
    await asyncio.sleep(3)

    # Cancel the task
    task.cancel()

    try:
        await task
    except asyncio.CancelledError:
        print("Confirmed: task was cancelled")

asyncio.run(cancel_example())
```

### 3. Resource Cleanup with Context Managers

```python
import asyncio

class AsyncResource:
    """Async context manager for resource management."""

    async def __aenter__(self):
        """Async setup."""
        print("Acquiring resource")
        await asyncio.sleep(1)  # Simulate async setup
        self.connection = "connected"
        return self

    async def __aexit__(self, exc_type, exc_val, exc_tb):
        """Async cleanup."""
        print("Releasing resource")
        await asyncio.sleep(1)  # Simulate async cleanup
        self.connection = None

async def use_resource():
    """Use async resource."""
    async with AsyncResource() as resource:
        print(f"Using resource: {resource.connection}")
        await asyncio.sleep(1)
    # Resource automatically cleaned up

asyncio.run(use_resource())
```

### 4. Debouncing and Throttling

```python
import asyncio
from datetime import datetime

class Debouncer:
    """Debounce async function calls."""

    def __init__(self, delay: float):
        self.delay = delay
        self.task = None

    async def call(self, func, *args, **kwargs):
        """Debounced function call."""
        # Cancel previous task
        if self.task:
            self.task.cancel()

        # Create new task
        async def delayed_call():
            await asyncio.sleep(self.delay)
            await func(*args, **kwargs)

        self.task = asyncio.create_task(delayed_call())

async def api_call(query: str):
    """Simulated API call."""
    print(f"{datetime.now()}: API call with query: {query}")

async def debounce_example():
    """Example of debouncing."""
    debouncer = Debouncer(delay=1.0)

    # Rapid calls - only last one executes
    await debouncer.call(api_call, "query1")
    await asyncio.sleep(0.1)
    await debouncer.call(api_call, "query2")
    await asyncio.sleep(0.1)
    await debouncer.call(api_call, "query3")

    # Wait for debounced call
    await asyncio.sleep(2)

asyncio.run(debounce_example())
# Output: Only "query3" API call executes
```

### 5. Rate Limiting

```python
import asyncio
from datetime import datetime

class RateLimiter:
    """Limit rate of async operations."""

    def __init__(self, max_calls: int, period: float):
        self.max_calls = max_calls
        self.period = period
        self.semaphore = asyncio.Semaphore(max_calls)
        self.calls = []

    async def __aenter__(self):
        """Acquire rate limit slot."""
        await self.semaphore.acquire()

        now = asyncio.get_event_loop().time()

        # Remove old calls outside period
        self.calls = [t for t in self.calls if now - t < self.period]

        if len(self.calls) >= self.max_calls:
            # Wait until oldest call expires
            sleep_time = self.period - (now - self.calls[0])
            if sleep_time > 0:
                await asyncio.sleep(sleep_time)

        self.calls.append(now)
        return self

    async def __aexit__(self, *args):
        """Release semaphore."""
        self.semaphore.release()

async def rate_limited_operation(limiter, name):...

© Claude MPM Team · MIT · bobmatnyc/claude-mpm-skills

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