Python 3.x 如何提高此python请求会话的速度？

我正在使用Anaconda-Python 3.5.2

我有一个280000网址的列表。 我正在抓取数据并试图跟踪数据的url

我已经提出了大约3万个请求。我平均每秒1个请求

response_df = pd.DataFrame()
# create the session
with requests.Session() as s:
    # loop through the list of urls
    for url in url_list:
        # call the resource
        resp = s.get(url)
        # check the response
        if resp.status_code == requests.codes.ok:
            # create a new dataframe with the response            
            ftest = json_normalize(resp.json())
            ftest['url'] = url
            response_df = response_df.append(ftest, ignore_index=True)
        else:
            print("Something went wrong! Hide your wife! Hide the kids!")

response_df.to_csv(results_csv) 

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我最终放弃了请求，而是使用了异步和aiohttp。我的请求速度大约是每秒1次。新方法平均每秒5次左右，仅使用我系统资源的20%左右。我最终使用了与此非常相似的东西：

此外，这也很有帮助：

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请将代码缩进，也可以考虑对代码进行解析。此外，考虑预先分配输出DF。URL是静态的还是其值取决于诸如最后一个请求之类的东西？谢谢，我将阅读有关代码的预配置和预分配输出DF。关于url，基本url是静态的，但每个url都是唯一的。

import aiohttp
import asyncio
import async_timeout
import os

async def download_coroutine(session, url):
    with async_timeout.timeout(10):
        async with session.get(url) as response:
            filename = os.path.basename(url)
            with open(filename, 'wb') as f_handle:
                while True:
                    chunk = await response.content.read(1024)
                    if not chunk:
                        break
                    f_handle.write(chunk)
            return await response.release()

async def main(loop):
    urls = ["http://www.irs.gov/pub/irs-pdf/f1040.pdf",
        "http://www.irs.gov/pub/irs-pdf/f1040a.pdf",
        "http://www.irs.gov/pub/irs-pdf/f1040ez.pdf",
        "http://www.irs.gov/pub/irs-pdf/f1040es.pdf",
        "http://www.irs.gov/pub/irs-pdf/f1040sb.pdf"]

async with aiohttp.ClientSession(loop=loop) as session:
    for url in urls:
        await download_coroutine(session, url)


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