API上的For循环

Question

我在一个名为“y”的列表中有一个大约28K个数字的列表，我正在API上运行for循环来发送消息，但这需要很多时间（确切地说，每次调用1.2797秒）

代码：

import timeit

start = timeit.default_timer()

for i in y:
    data = {'From': 'XXXX', 'To': str(i),
            'Body': "ABC ABC" }
    requests.post('https://xxxx:[e-mail]/v1/Accounts/xxx/Sms/send',data=data)

stop = timeit.default_timer()
print('Time: ', stop - start)   

我怎样才能减少做这件事的时间？

Answer 1

Asyncio或多线程是优化代码的两种可能的解决方案，它们基本上都是这样做的：

import timeit
import threading
import time

y = list(range(50))


def post_data(server, data, sleep_time=1.5):
    time.sleep(sleep_time)
    # request.post(server, data=data)


start = timeit.default_timer()

server = 'https://xxxx:[e-mail]/v1/Accounts/xxx/Sms/send'

threads = []
for i in y:
    # if you don't need to wait for your threads don't hold them in memory after they are done and instead do
    # threading.Thread(target, args).start()
    # instead. Especially important if you want to send a large number of messages
    threads.append(threading.Thread(target=post_data,
                            args=(server, {'From': 'XXXX', 'To': str(i), 'Body': "ABC ABC"}))
    threads[-1].start()

for thread in threads:
    # optional if you want to wait for completion of the concurrent posts
    thread.join()

stop = timeit.default_timer()
print('Time: ', stop - start)

关于这个答案。

import timeit
import asyncio
from concurrent.futures import ThreadPoolExecutor

y =  list(range(50)
_executor = ThreadPoolExecutor(len(y))

loop = asyncio.get_event_loop()

def post_data(server, data, sleep_time=1.5):
    time.sleep(sleep_time)
    # request.post(server, data=data)

async def post_data_async(server, data):
    return await loop.run_in_executor(_executor, lambda: post_data(server, data))


async def run(y, server):
    return await asyncio.gather(*[post_data_async(server, {'From': 'XXXX', 'To': str(i), 'Body': "ABC ABC"})
                                  for i in y])


start = timeit.default_timer()

server = 'https://xxxx:[e-mail]/v1/Accounts/xxx/Sms/send'

loop.run_until_complete(run(y, server))

stop = timeit.default_timer()
print('Time: ', stop - start)

当使用不支持异步但会从并发中获益的API时，就像您的用例一样，我倾向于使用线程，因为它更容易阅读IMHO。如果你的API/库确实支持asyncio，那就去吧！这是伟大的！

在我的机器上，当执行50个time.sleep（1.5）实例时，异步解决方案的运行时间为1.515秒，而线程解决方案需要大约1.509秒。