从Python 3.5开始，可以对异步函数使用增强的生成器。

import asyncio
import datetime

增强的生成器语法:

@asyncio.coroutine
def display_date(loop):
    end_time = loop.time() + 5.0
    while True:
        print(datetime.datetime.now())
        if (loop.time() + 1.0) >= end_time:
            break
        yield from asyncio.sleep(1)


loop = asyncio.get_event_loop()
# Blocking call which returns when the display_date() coroutine is done
loop.run_until_complete(display_date(loop))
loop.close()

新的async/await语法:

async def display_date(loop):
    end_time = loop.time() + 5.0
    while True:
        print(datetime.datetime.now())
        if (loop.time() + 1.0) >= end_time:
            break
        await asyncio.sleep(1)


loop = asyncio.get_event_loop()
# Blocking call which returns when the display_date() coroutine is done
loop.run_until_complete(display_date(loop))
loop.close()

你可以使用过程。如果你想永远运行它，在你的函数中使用while(比如networking):

from multiprocessing import Process
def foo():
    while 1:
        # Do something

p = Process(target = foo)
p.start()

如果你只想运行一次，可以这样做:

from multiprocessing import Process
def foo():
    # Do something

p = Process(target = foo)
p.start()
p.join()

2021年的原生Python异步调用方式，Python 3.9也适用于Jupyter / Ipython内核

Camabeh的答案是从Python 3.3开始的。

异步def display_date(循环): End_time = loop.time() + 5.0 而真正的: print (datetime.datetime.now ()) If (loop.time() + 1.0) >= end_time: 打破 等待asyncio.sleep (1) Loop = asyncio.get_event_loop() #阻塞调用，当display_date()协程完成时返回 loop.run_until_complete (display_date(循环) loop.close ()

这将在Jupyter笔记本/ Jupyter实验室工作，但抛出一个错误:

RuntimeError: This event loop is already running

由于Ipython使用事件循环，我们需要一些嵌套异步循环，这在Python中还没有实现。幸运的是，有nest_asyncio来处理这个问题。你所需要做的就是:

!pip install nest_asyncio # use ! within Jupyter Notebook, else pip install in shell
import nest_asyncio
nest_asyncio.apply()

(基于此线程)

只有在调用loop.close()时，它才会抛出另一个错误，因为它可能指向Ipython的主循环。

RuntimeError: Cannot close a running event loop

一旦有人回答了这个github问题，我就会更新这个答案。

喜欢的东西:

import threading

thr = threading.Thread(target=foo, args=(), kwargs={})
thr.start() # Will run "foo"
....
thr.is_alive() # Will return whether foo is running currently
....
thr.join() # Will wait till "foo" is done

有关详细信息，请参阅https://docs.python.org/library/threading.html上的文档。

从Python 3.5开始，可以对异步函数使用增强的生成器。

import asyncio
import datetime

增强的生成器语法:

@asyncio.coroutine
def display_date(loop):
    end_time = loop.time() + 5.0
    while True:
        print(datetime.datetime.now())
        if (loop.time() + 1.0) >= end_time:
            break
        yield from asyncio.sleep(1)


loop = asyncio.get_event_loop()
# Blocking call which returns when the display_date() coroutine is done
loop.run_until_complete(display_date(loop))
loop.close()

新的async/await语法:

async def display_date(loop):
    end_time = loop.time() + 5.0
    while True:
        print(datetime.datetime.now())
        if (loop.time() + 1.0) >= end_time:
            break
        await asyncio.sleep(1)


loop = asyncio.get_event_loop()
# Blocking call which returns when the display_date() coroutine is done
loop.run_until_complete(display_date(loop))
loop.close()

你可以使用并发。期货(在Python 3.2中添加)。

import time
from concurrent.futures import ThreadPoolExecutor


def long_computation(duration):
    for x in range(0, duration):
        print(x)
        time.sleep(1)
    return duration * 2


print('Use polling')
with ThreadPoolExecutor(max_workers=1) as executor:
    future = executor.submit(long_computation, 5)
    while not future.done():
        print('waiting...')
        time.sleep(0.5)

    print(future.result())

print('Use callback')
executor = ThreadPoolExecutor(max_workers=1)
future = executor.submit(long_computation, 5)
future.add_done_callback(lambda f: print(f.result()))

print('waiting for callback')

executor.shutdown(False)  # non-blocking

print('shutdown invoked')