Python run_in_executor 却忘记了

Python中的`run_in_executor`是一个非常有用的函数，它可以帮助开发者在异步程序中运行阻塞的代码。这个函数可以让开发者使用线程池或者进程池来执行耗时的任务，从而避免阻塞主线程。不过，有时候我们可能会忘记如何正确地使用`run_in_executor`，所以本文将带领大家重新学习这个函数，并提供一些实际的案例代码来帮助理解。

python
asyncio.ensure_future(loop.run_in_executor(executor, func, *args, **kwargs))

python
import asyncio
import requests
async def download_file(url, file_path):
    response = requests.get(url, stream=True)
    with open(file_path, 'wb') as file:
        for chunk in response.iter_content(chunk_size=8192):
            if chunk:
                file.write(chunk)
async def main():
    url = 'http://example.com/large_file.bin'
    file_path = 'large_file.bin'
    
    loop = asyncio.get_event_loop()
    executor = loop.run_in_executor(None, download_file, url, file_path)
    
    await asyncio.wait([executor])
if __name__ == '__main__':
    asyncio.run(main())

python
import asyncio
import math
async def calculate_factorial(number):
    result = await loop.run_in_executor(None, math.factorial, number)
    print(f"The factorial of {number} is {result}")
async def main():
    numbers = [100, 500, 1000]
    
    tasks = [calculate_factorial(number) for number in numbers]
    await asyncio.wait(tasks)
if __name__ == '__main__':
    loop = asyncio.get_event_loop()
    asyncio.run(main())