Junior — Middle

How did you implement managing multiple tasks in your projects?

sobes.tech AI

Answer from AI

To manage multiple tasks in Python, I often use several approaches depending on the project requirements:

Threads (threading) — for I/O-bound tasks where concurrency is important but multi-processing is not required. For example, loading multiple files simultaneously.
Multiprocessing — when you need to parallelize compute-intensive tasks to utilize multiple CPU cores.
Asynchronous programming (asyncio) — for a large number of I/O operations with high concurrency, such as working with network requests.

Example using asyncio:

import asyncio

async def task(name, delay):
    print(f"Task {name} started")
    await asyncio.sleep(delay)
    print(f"Task {name} finished")

async def main():
    await asyncio.gather(
        task('A', 2),
        task('B', 1),
        task('C', 3)
    )

asyncio.run(main())

This approach allows running multiple tasks simultaneously without blocking the main thread.

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