在API上进行循环

拉胡尔·沙玛（Rahul Sharma）

我在名为“ y ”的列表中有大约28000个数字的列表，并且正在API上运行for循环以发送消息，但这需要花费大量时间（准确地说是每次调用1.2797秒）

码：

import timeit

start = timeit.default_timer()

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

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

我该如何减少时间？

贾克

Asyncio或Multithreading是优化代码的两种可能的解决方案，并且两者基本上都在后台执行相同的操作：

螺纹的

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:[email protected]/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)

异步

参考这个答案。

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:[email protected]/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可以从并发中获利的API时（如您的用例），我倾向于使用线程，因为它更易于理解IMHO。如果您的API /库确实支持asyncio，那就去吧！这很棒！

在我的包含50个元素的列表的机器上，asyncio解决方案在运行时运行1.515秒，而线程解决方案在执行50个实例时需要大约1.509秒time.sleep(1.5)。

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