python-asyncio 相关问题

此标记用于asyncio Python包,它提供了编写单线程并发代码的机制。 asyncio包提供从Python 3.4开始的异步I / O,事件循环,协同程序和任务。




如何立即在Websocket停止请求时立即停止函数?

我想在WebSocket中停止时立即停止立即运行生成功能。 类图像世代(碱基): 异步def过程(self,websocket,提示): ...

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对其进行了装饰。该功能在某些延期上等待。然后,我需要在其中运行一些

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Aasyncio和Paramiko并发SSH连接

import paramiko import time import asyncio async def sshTest(ipaddress,deviceUsername,devicePassword,sshPort): #finalDict try: print("Performing SSH Connection to the device") client = paramiko.SSHClient() client.set_missing_host_key_policy(paramiko.AutoAddPolicy()) client.connect(ipaddress, username=deviceUsername, password=devicePassword, port=sshPort, look_for_keys=False, allow_agent=False) print("Channel established") except Exception as e: print(e) async def main(): print("Session 1 \n") await sshTest('192.168.255.11','admin','admin','22') print("Session 2 \n") await sshTest('192.168.254.11','admin','admin','22') if __name__ == "__main__": start = time.time() asyncio.run(main()) end = time.time() print("The time of execution of above program is :", end-start)

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dateTime.strptime()正在阻止asyncio.queue.get()

在以下代码dateTime.strptime()中,正在阻止asyncio.queue.get()操作 进口时间 导入异步 从DateTime Import DateTime 从函数引入部分导入 def写(队列): da ...

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attributeError:模块'select'没有属性'select'errorasyncio

import aiohttp import asyncio import time async def download_file(url): print(f'started downloading{url}') connector = aiohttp.TCPConnector(limit=60) async with aiohttp.clientSession(connector) as session: async with session.get(url) as resp: content = await resp.read() print (f'Finished download{url}') return content async def write_file(n, content): filename = f'async_{n}.html' with open(filename,'wb') as f: print(f'started writing{filename}') f.write(content) print(f'Finished writing{filename}') async def scrape_task(n,url): content = await download_file(url) await write_file(n,content) async def main(): tasks = [] for n,url in enumerate(open('urls.txt').readlines()): tasks.append((scrape_task(n, url))) await asyncio.wait(tasks) if __name__ == '__main__': t=time.perf_counter() loop = asyncio.get_event_loop() loop.run_until_complete(main()) t2 = time.perf_counter() - t print(f'Total time taken: {t2:0.2f} seconds')

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创建的不同折叠,因为这是CPU重型任务,我决定使用

),然后对该数据执行CPU重型操作。每当处理折叠时,我都会使用

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