Introduction

Have you ever been troubled by Python program performance issues? Especially when handling large amounts of I/O operations, such as network requests and file operations, programs always seem so sluggish. This is exactly where asynchronous programming shines. Let me share with you my exploration and insights in the field of asynchronous programming.

Understanding

When it comes to asynchronous programming, many people's first reaction is "it's too difficult." Indeed, when I first encountered asyncio, I was also confused by various concepts: coroutines, event loops, Futures, Tasks... But as I learned more deeply, I discovered that asynchronous programming isn't as scary as imagined.

The core idea of asynchronous programming is actually quite simple: while waiting for one operation to complete, we can go do something else. It's just like in our daily life when we scroll through our phones or handle other tasks while waiting for food delivery.

Let's understand this concept through a simple example:

import asyncio
import time

async def make_coffee():
    print('Starting to brew coffee...')
    await asyncio.sleep(3)  # Simulating coffee brewing time
    print('Coffee is ready!')
    return 'A cup of rich coffee'

async def make_toast():
    print('Starting to toast bread...')
    await asyncio.sleep(2)  # Simulating toasting time
    print('Toast is ready!')
    return 'A slice of golden toast'

async def main():
    coffee, toast = await asyncio.gather(make_coffee(), make_toast())
    print(f'Breakfast is ready: {coffee} and {toast}')

asyncio.run(main())