Tell me about Async, Multithreading, Multiprocessing: what are they, when is it better to use each?

Async, Multithreading, and Multiprocessing in Python — these are three approaches to executing tasks concurrently or asynchronously, each suitable for different scenarios.

• Async (asynchronous programming) — based on an event loop and coroutines. It allows efficient handling of a large number of I/O operations (e.g., network requests, file reading) without blocking the main thread. Used when tasks mainly wait for external resources.

  import asyncio
  
  async def fetch_data():
      await asyncio.sleep(1)  # simulate I/O
      return 'data'
  
  async def main():
      result = await fetch_data()
      print(result)
  
  asyncio.run(main())
  

• Multithreading — multiple threads within a single process. In Python, due to the GIL (Global Interpreter Lock), threads cannot execute Python code simultaneously, but are suitable for I/O-bound tasks (e.g., network operations, file handling).

• Multiprocessing — running multiple processes, each with its own memory and Python interpreter. It bypasses GIL and efficiently utilizes multiple CPU cores for compute-intensive tasks.

When to use what:

• For I/O-intensive tasks — async or multithreading.
• For CPU-intensive tasks — multiprocessing.
• Async is convenient for a large number of lightweight tasks, multithreading is easier to integrate with existing code, multiprocessing is for heavy computations.

The choice depends on the nature of the task and performance requirements.