Day 38: Blocking I/O in async programs

 

🐍 Python Mistakes Everyone Makes ❌

Day 38: Blocking I/O in Async Programs

Async programming in Python is powerful—but only if you follow the rules.
One of the most common mistakes is using blocking I/O inside async code, which silently kills performance.

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❌ The Mistake

Using a blocking function like time.sleep() inside an async function.

import time
import asyncio 

async def task():
   time.sleep(2) # ❌ blocks the event loop
   print("Done")

asyncio.run(task())

At first glance, this looks fine.
But under the hood, it breaks how async works.

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❌ Why This Fails

• time.sleep() blocks the event loop

• While sleeping, no other async tasks can run

• Async code becomes slow and sequential

• No error is raised — just poor performance

This makes the bug easy to miss and hard to debug.

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🚨 What’s Really Happening

Async programs rely on an event loop to switch between tasks efficiently.
Blocking calls stop the event loop entirely.

Result:

• No concurrency

• Wasted async benefits

• Performance similar to synchronous code

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✅ The Correct Way

Use non-blocking async alternatives like asyncio.sleep().

import asyncio

async def task():
    await asyncio.sleep(2)
    print("Done")

asyncio.run(task())

Why this works:

• await pauses only the current task

• The event loop stays responsive

• Other async tasks can run in the meantime

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🧠 Common Blocking Functions to Avoid in Async Code

time.sleep()

• Blocking file I/O

• Blocking network calls

• CPU-heavy computations

Use:

asyncio.sleep()

• Async libraries (aiohttp, aiofiles)

• Executors for CPU-heavy work

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🧠 Simple Rule to Remember

🐍 Blocking calls freeze the event loop
🐍 Use await, not blocking functions
🐍 Never block the event loop in async code

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🚀 Final Takeaway

Async code only works when everything cooperates.
One blocking call can ruin your entire async design.

Write async code the async way —
Fast, non-blocking, and scalable.