简单来说就是一般IO密集型任务采用多线程、CPU密集型任务采用多进程。官网范例如下:
import asyncio
import concurrent.futures
def blocking_io():
# File operations (such as logging) can block the
# event loop: run them in a thread pool.
with open('/dev/urandom', 'rb') as f:
return f.read(100)
def cpu_bound():
# CPU-bound operations will block the event loop:
# in general it is preferable to run them in a
# process pool.
return sum(i * i for i in range(10 ** 7))
async def main():
loop = asyncio.get_running_loop()
## Options:
# 1. Run in the default loop's executor:
result = await loop.run_in_executor(
None, blocking_io)
print('default thread pool', result)
# 2. Run in a custom thread pool:
with concurrent.futures.ThreadPoolExecutor() as pool:
result = await loop.run_in_executor(
pool, blocking_io)
print('custom thread pool', result)
# 3. Run in a custom process pool:
with concurrent.futures.ProcessPoolExecutor() as pool:
result = await loop.run_in_executor(
pool, cpu_bound)
print('custom process pool', result)
asyncio.run(main())
Ref:Event Loop — Python 3.9.7 documentation
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