DEV Community

Vladimir Ignatev
Vladimir Ignatev

Posted on

🤔 Python Quiz 8/64: Introduction to `asyncio` in Python

Follow me to learn 🐍 Python in 5-minute a day fun quizzes!

For this quiz, I'll choose a topic related to the use of the asyncio module in Python, which is a more advanced concept but extremely useful in modern Python programming. This topic is covered by PEP 492 - Coroutines with async and await syntax, which is a fundamental part of asynchronous programming in Python.

In Python, the difference between asynchronous (async) and blocking code is central to how you write programs that perform tasks that can take a long time to complete, such as I/O operations.

Blocking Code:

  • Blocking code is the default mode of operation for Python; when the program encounters an operation, it must wait for the operation to complete before moving on to the next line of code.
  • If a blocking call is made (like input(), time.sleep(), or a network request), the entire program is stalled until that call returns.
  • In a single-threaded application, blocking I/O can make the program inefficient and unresponsive, especially in network programming or when dealing with files.

Asynchronous Code:

  • Asynchronous code allows the program to handle multiple operations without waiting for any single one to complete; while one operation is waiting, other operations can continue.
  • The asyncio library in Python provides the infrastructure for writing single-threaded concurrent code using coroutines, multiplexing I/O access over sockets and other resources, running network clients and servers, and other related primitives.
  • An async function is defined with the async def keyword, and it allows you to use await to pause the coroutine until an operation completes, while letting the event loop run other coroutines that are not paused.

Why It Matters:

  • Performance: Asynchronous code can provide a significant performance improvement for I/O-bound and high-level structured network code.
  • Efficiency: Async allows for more efficient use of system resources as you can handle more tasks with fewer threads.
  • Responsiveness: In user-facing applications, such as web applications, async programming can prevent the application from becoming unresponsive.
  • Scalability: Asynchronous applications can scale better, as they can handle many simultaneous connections.

Quiz

Which code sample correctly uses the asyncio module in Python for asynchronous programming?

Sample 1

import asyncio

async def main():
    print("Hello")
    await asyncio.sleep(1)
    print("World")

asyncio.run(main())
Enter fullscreen mode Exit fullscreen mode

Sample 2

import asyncio

def main():
    print("Hello")
    asyncio.sleep(1)
    print("World")

asyncio.run(main())
Enter fullscreen mode Exit fullscreen mode

Post your answer in the comments – is it 0 for the first sample or 1 for the second! As usual, the correct answer will be explained in the comments.

Top comments (0)