Mastering Python Asyncio: Non-Blocking, Fast Code

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Mastering Python Asyncio: Non-Blocking, Fast Code

Mastering Python Asyncio: Non-Blocking, Fast Code

Asyncio is Python’s toolkit for asynchronous programming. With async and await, you can run tasks in parallel without threads—perfect for APIs, scraping, and networking apps.

🆚 Synchronous vs Asynchronous

# Synchronous version

import time

def fetch_data():

    time.sleep(2)

    return "Data received"

print(fetch_data())


# Asynchronous version

import asyncio

async def fetch_data():

    await asyncio.sleep(2)

    return "Data received"

async def main():

    result = await fetch_data()

    print(result)

asyncio.run(main())

Note: await pauses without blocking, letting the CPU run other tasks!

⚙️ The Event Loop

Asyncio uses an event loop to schedule and resume tasks. Think of it as a task manager that lets functions pause and resume without losing context.

🔄 Running Multiple Tasks

import asyncio

async def say_hello():

    await asyncio.sleep(1)

    print("Hello")

async def say_world():

    await asyncio.sleep(1)

    print("World")

async def main():

    task1 = asyncio.create_task(say_hello())

    task2 = asyncio.create_task(say_world())

    await task1

    await task2

asyncio.run(main())

✅ Output: Both tasks finish in 1 second instead of 2!

🌍 Real-Life Example: Fetch Multiple URLs

import asyncio

import aiohttp

async def fetch(url):

    async with aiohttp.ClientSession() as session:

        async with session.get(url) as response:

            return await response.text()

async def main():

    urls = [

        "https://httpbin.org/get",

        "https://api.github.com",

        "https://example.com"

    ]

    tasks = [fetch(url) for url in urls]

    results = await asyncio.gather(*tasks)

    for r in results:

        print(r[:100])  # Print preview

asyncio.run(main())
⚡ This is faster than using requests in a loop—everything runs concurrently!

🚫 Common Mistakes

  • ❌ Forgetting await — nothing will run!
  • ❌ Using time.sleep() inside async functions. Use asyncio.sleep() instead.
  • ❌ Nesting asyncio.run() inside Jupyter or another event loop.

📌 When Should You Use Asyncio?

  • Multiple I/O-bound tasks (API calls, file access, DB queries)
  • Thousands of concurrent tasks
  • Building fast bots, web scrapers, or microservices

🧠 Summary

  • async defines a coroutine.
  • await pauses and resumes the function.
  • asyncio.run() launches the event loop.
  • asyncio.gather() runs multiple coroutines concurrently.

📚 Learn More

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