Using Python asynchronously

The video tutorial explains asynchronous programming in Python, highlighting its ability to handle multiple tasks concurrently, especially in IO-bound operations like network requests. It contrasts synchronous and asynchronous scripts, demonstrating the efficiency of async operations using Python's asyncio library. Key concepts include async syntax, event loops, task objects, and the asyncio gather function, which allows for efficient result collection from multiple tasks.

What is the primary advantage of asynchronous programming?

• It simplifies the code structure.

• It makes CPU-intensive tasks run faster.

• It enables tasks to run concurrently, reducing wait times.

• It allows tasks to run without any waiting time.

Why is the synchronous script slower in fetching data from URLs?

• It uses more CPU resources.

• It requires more memory to run.

• It waits for each task to complete before starting the next.

• It processes multiple URLs at the same time.

Which Python library is essential for running async functions?

• threading

• requests

• asyncio

• concurrent

What is the role of the event loop in asynchronous programming?

• It executes tasks sequentially.

• It increases the CPU usage.

• It blocks tasks until they are completed.

• It manages and runs async functions.

How does the asyncio gather command function?

• It cancels all running tasks.

• It runs tasks one after another.

• It prioritizes tasks based on their complexity.

• It waits for all tasks to finish and collects their results.