python 异步线程池 python异步调用

最近遇到个问题， NLP相关的代码，尤其是DL相关的代码，处理千万级数据显得会慢一些，有可能要好几个小时，那前端的等待是不可行的，这个时候就需要采用python的异步函数了。

同步代码

import time

def hello():
    time.sleep(1)

def run():
    for i in range(5):
        hello()
        print('Hello World:%s' % time.time())  
if __name__ == '__main__':
    run()

Hello World:1536842494.2786784
Hello World:1536842495.2796268
Hello World:1536842496.2802596
Hello World:1536842497.2804587
Hello World:1536842498.2812462

异步代码

import time
import asyncio

# 定义异步函数
async def hello():
    print('Hello World:%s' % time.time())
    #必须使用await，不能使用yield from；如果是使用yield from ，需要采用@asyncio.coroutine相对应
    await asyncio.sleep(1)   
    print('Hello wow World:%s' % time.time())

def run():
    tasks = []
    for i in range(5):
        tasks.append(hello())
    loop.run_until_complete(asyncio.wait(tasks))

loop = asyncio.get_event_loop()
if __name__ =='__main__':
    run()

Hello World:1536855050.1950748
Hello World:1536855050.1950748
Hello World:1536855050.1950748
Hello World:1536855050.1960726
Hello World:1536855050.1960726
(暂停约1秒)
Hello wow World:1536855051.1993241
Hello wow World:1536855051.1993241
Hello wow World:1536855051.1993241
Hello wow World:1536855051.1993241
Hello wow World:1536855051.1993241