I am opening a file which has 100,000 URL's. I need to send an HTTP request to each URL and print the status code. I am using Python 2.6, and so far looked at the many confusing ways Python implements threading/concurrency. I have even looked at the python concurrence library, but cannot figure out how to write this program correctly. Has anyone come across a similar problem? I guess generally I need to know how to perform thousands of tasks in Python as fast as possible - I suppose that means 'concurrently'.
当前回答
我知道这是一个老问题,但在Python 3.7中,您可以使用asyncio和aiohttp来做到这一点。
import asyncio
import aiohttp
from aiohttp import ClientSession, ClientConnectorError
async def fetch_html(url: str, session: ClientSession, **kwargs) -> tuple:
try:
resp = await session.request(method="GET", url=url, **kwargs)
except ClientConnectorError:
return (url, 404)
return (url, resp.status)
async def make_requests(urls: set, **kwargs) -> None:
async with ClientSession() as session:
tasks = []
for url in urls:
tasks.append(
fetch_html(url=url, session=session, **kwargs)
)
results = await asyncio.gather(*tasks)
for result in results:
print(f'{result[1]} - {str(result[0])}')
if __name__ == "__main__":
import pathlib
import sys
assert sys.version_info >= (3, 7), "Script requires Python 3.7+."
here = pathlib.Path(__file__).parent
with open(here.joinpath("urls.txt")) as infile:
urls = set(map(str.strip, infile))
asyncio.run(make_requests(urls=urls))
你可以阅读更多关于它的内容,并在这里看到一个例子。
其他回答
我知道这是一个老问题,但在Python 3.7中,您可以使用asyncio和aiohttp来做到这一点。
import asyncio
import aiohttp
from aiohttp import ClientSession, ClientConnectorError
async def fetch_html(url: str, session: ClientSession, **kwargs) -> tuple:
try:
resp = await session.request(method="GET", url=url, **kwargs)
except ClientConnectorError:
return (url, 404)
return (url, resp.status)
async def make_requests(urls: set, **kwargs) -> None:
async with ClientSession() as session:
tasks = []
for url in urls:
tasks.append(
fetch_html(url=url, session=session, **kwargs)
)
results = await asyncio.gather(*tasks)
for result in results:
print(f'{result[1]} - {str(result[0])}')
if __name__ == "__main__":
import pathlib
import sys
assert sys.version_info >= (3, 7), "Script requires Python 3.7+."
here = pathlib.Path(__file__).parent
with open(here.joinpath("urls.txt")) as infile:
urls = set(map(str.strip, infile))
asyncio.run(make_requests(urls=urls))
你可以阅读更多关于它的内容,并在这里看到一个例子。
线程绝对不是这里的答案。它们将提供进程和内核瓶颈,以及吞吐量限制,如果总体目标是“最快的方式”,这些限制是不可接受的。
稍微扭曲一点,它的异步HTTP客户端会给你更好的结果。
对于您的情况,线程可能会做的技巧,因为您可能会花费大部分时间等待响应。标准库中有一些有用的模块,如Queue,可能会有所帮助。
我以前做过类似的并行下载文件的事情,对我来说已经足够好了,但它不是你所说的那种规模。
如果您的任务对cpu的限制更大,您可能需要考虑multiprocessing模块,它将允许您利用更多的cpu /内核/线程(更多的进程不会相互阻塞,因为锁定是每个进程)
我发现使用tornado包是最快和最简单的方法来实现这一点:
from tornado import ioloop, httpclient, gen
def main(urls):
"""
Asynchronously download the HTML contents of a list of URLs.
:param urls: A list of URLs to download.
:return: List of response objects, one for each URL.
"""
@gen.coroutine
def fetch_and_handle():
httpclient.AsyncHTTPClient.configure(None, defaults=dict(user_agent='MyUserAgent'))
http_client = httpclient.AsyncHTTPClient()
waiter = gen.WaitIterator(*[http_client.fetch(url, raise_error=False, method='HEAD')
for url in urls])
results = []
# Wait for the jobs to complete
while not waiter.done():
try:
response = yield waiter.next()
except httpclient.HTTPError as e:
print(f'Non-200 HTTP response returned: {e}')
continue
except Exception as e:
print(f'An unexpected error occurred querying: {e}')
continue
else:
print(f'URL \'{response.request.url}\' has status code <{response.code}>')
results.append(response)
return results
loop = ioloop.IOLoop.current()
web_pages = loop.run_sync(fetch_and_handle)
return web_pages
my_urls = ['url1.com', 'url2.com', 'url100000.com']
responses = main(my_urls)
print(responses[0])
一个使用tornado的异步网络库解决方案
from tornado import ioloop, httpclient
i = 0
def handle_request(response):
print(response.code)
global i
i -= 1
if i == 0:
ioloop.IOLoop.instance().stop()
http_client = httpclient.AsyncHTTPClient()
for url in open('urls.txt'):
i += 1
http_client.fetch(url.strip(), handle_request, method='HEAD')
ioloop.IOLoop.instance().start()
这段代码使用非阻塞网络I/O,没有任何限制。它可以扩展到数万个打开的连接。它将在单个线程中运行,但比任何线程解决方案都要快。签出非阻塞I/O
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