Python async/await 正在下载 url 列表

Question

我正在尝试从 FTP 服务器下载 30,000 多个文件，经过谷歌搜索后，使用异步 IO 似乎是个好主意。但是，下面的代码无法下载任何文件并且 returns 超时错误。我真的很感激任何帮助！谢谢！

class pdb:
    def __init__(self):
        self.ids = []
        self.dl_id = []
        self.err_id = []


    async def download_file(self, session, url):
        try:
            with async_timeout.timeout(10):
                async with session.get(url) as remotefile:
                    if remotefile.status == 200:
                        data = await remotefile.read()
                        return {"error": "", "data": data}
                    else:
                        return {"error": remotefile.status, "data": ""}
        except Exception as e:
            return {"error": e, "data": ""}

    async def unzip(self, session, work_queue):
        while not work_queue.empty():
            queue_url = await work_queue.get()
            print(queue_url)
            data = await self.download_file(session, queue_url)
            id = queue_url[-11:-7]
            ID = id.upper()
            if not data["error"]:
                saved_pdb = os.path.join("./pdb", ID, f'{ID}.pdb')
                if ID not in self.dl_id:
                    self.dl_id.append(ID)
                with open(f"{id}.ent.gz", 'wb') as f:
                    f.write(data["data"].read())
                with gzip.open(f"{id}.ent.gz", "rb") as inFile, open(saved_pdb, "wb") as outFile:
                    shutil.copyfileobj(inFile, outFile)
                os.remove(f"{id}.ent.gz")
            else:
                self.err_id.append(ID)

    def download_queue(self, urls):
        loop = asyncio.get_event_loop()
        q = asyncio.Queue(loop=loop)
        [q.put_nowait(url) for url in urls]
        con = aiohttp.TCPConnector(limit=10)
        with aiohttp.ClientSession(loop=loop, connector=con) as session:
            tasks = [asyncio.ensure_future(self.unzip(session, q)) for _ in range(len(urls))]
            loop.run_until_complete(asyncio.gather(*tasks))
        loop.close()

删除 try 部分时的错误消息：

Traceback (most recent call last):
File "test.py", line 111, in
x.download_queue(urls)
File "test.py", line 99, in download_queue
loop.run_until_complete(asyncio.gather(*tasks))
File "/home/yz/miniconda3/lib/python3.6/asyncio/base_events.py", line 467, in run_until_complete
return future.result()
File "test.py", line 73, in unzip
data = await self.download_file(session, queue_url)
File "test.py", line 65, in download_file
return {"error": remotefile.status, "data": ""}
File "/home/yz/miniconda3/lib/python3.6/site- packages/async_timeout/init.py", line 46, in exit
raise asyncio.TimeoutError from None
concurrent.futures._base.TimeoutError

Answer 1

tasks = [asyncio.ensure_future(self.unzip(session, q)) for _ in range(len(urls))]
loop.run_until_complete(asyncio.gather(*tasks))

在这里，您开始同时下载所有网址。这意味着您也开始为所有这些计算超时。一旦它是一个很大的数字，例如 30,000，由于 networks/ram/cpu 容量，它无法在 10 秒内完成。

为避免这种情况，您应该保证限制同时启动的协程。通常可以使用像 asyncio.Semaphore 这样的同步原语来实现这一点。

看起来像这样：

sem = asyncio.Semaphore(10)

# ...

async def download_file(self, session, url):
    try:
        async with sem:  # Don't start next download until 10 other currently running
            with async_timeout.timeout(10):

Answer 2

作为@MikhailGerasimov 信号量方法的替代方法，您可以考虑使用 aiostream.stream.map 运算符：

from aiostream import stream, pipe

async def main(urls):
    async with aiohttp.ClientSession() as session:
        ws = stream.repeat(session)
        xs = stream.zip(ws, stream.iterate(urls))
        ys = stream.starmap(xs, fetch, ordered=False, task_limit=10)
        zs = stream.map(ys, process)
        await zs

这是使用管道的等效实现：

async def main3(urls):
    async with aiohttp.ClientSession() as session:
        await (stream.repeat(session)
               | pipe.zip(stream.iterate(urls))
               | pipe.starmap(fetch, ordered=False, task_limit=10)
               | pipe.map(process))

您可以使用以下协程对其进行测试：

async def fetch(session, url):
    await asyncio.sleep(random.random())
    return url

async def process(data):
    print(data)

在此 demonstration and the documentation 中查看更多 aiostream 示例。

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Python async/await 正在下载 url 列表

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