asyncio

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:

# 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

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

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)