Whats the difference between asyncio and multithreading in python?

Multi-threading

import threading

def heavy_computation():
    # A CPU-bound task
    result = sum(x * x for x in range(10**6))

threads = []
for _ in range(4):
    t = threading.Thread(target=heavy_computation)
    threads.append(t)
    t.start()

for t in threads:
    t.join()

Asynchronous python

import asyncio

# Define an asynchronous function (coroutine)
async def async_task(name, duration):
    print(f"Task {name} started, will take {duration} seconds.")
    await asyncio.sleep(duration)  # Simulate a long-running I/O-bound task
    print(f"Task {name} finished.")

# Define the main coroutine
async def main():
    # Create multiple tasks using asyncio.create_task()
    task1 = asyncio.create_task(async_task("A", 2))
    task2 = asyncio.create_task(async_task("B", 3))
    task3 = asyncio.create_task(async_task("C", 1))

    # Wait for all tasks to complete
    await task1
    await task2
    await task3

# Run the main coroutine
asyncio.run(main())

What are the differences between using multi-threading in Python and Asynchronous Python since the global interpreter lock prevents parallelism of threads, only a single thread can execute at one time. Asynchronous Python is also also single threaded. I suppose, it could the resource management of multi-threads which could make asynchronous python more efficient. Which is preferred for backend applications like Django?

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