python网络编程：一边延迟启动，一边准备as_completed

原代码：

import asyncio as aio
async def Sleeper(s=1):
    t = f'Sleeper for {s} seconds'
    await aio.sleep(s)
    print(t)
    return t
 
 
async def main():
    tasks = [Sleeper(1.1), Sleeper(1)]
 
    async def sub():
        nonlocal tasks
        for i in range(len(tasks)):
            tasks[i] = aio.create_task(tasks[i])
            if i < len(tasks) - 1:
                await aio.sleep(10)  # 阻塞！
 
    await sub()
    for t in aio.as_completed(tasks):
        text = await t  # 等不到
        print('✅ ' + text)
 
aio.run(main())

这会有性能问题，sub()会阻塞下方的aio.as_complted的执行！

deepseek解决方案

import asyncio as aio
 
async def Sleeper(s=1):
    t = f'Sleeper for {s} seconds'
    await aio.sleep(s)
    print(t)
    return t
 
async def main():
    tasks = [Sleeper(1.1), Sleeper(1)]
 
    async def process_task(task):
        text = await task
        print('✅ ' + text)
 
    async def sub():
        for i in range(len(tasks)):
            # 创建任务并立即启动处理协程
            task = aio.create_task(tasks[i])
            aio.create_task(process_task(task))
            # 除最后一个任务外，每个任务创建后等待10秒
            if i < len(tasks) - 1:
                await aio.sleep(10)
 
    await sub()
 
aio.run(main())

其实就是js里.then()的曲折实现

真正解决方案

async def task_1by1( 
    coros: List[Coroutine],
    callback: Callable[[aio.Task], object] = None,
    duration=RELAX
 ):
    """
    Run tasks one by one with a duration of `duration` seconds
 
    - callback: accept `Task` object as argument only
    ```python
    def callback(task: asyncio.Task[TYPE_OF_RETURN]):
        if task.cancelled():
            msg = "Download cancelled"
            raise Exception(msg)
        t = task.result()
        return t
    ```
    """
    tasks = []
    for i in range(len(coros)):
        c = coros[i]
        t = aio.create_task(c)
        if callback and callable(callback):
            t.add_done_callback(callback)
        tasks.append(t)
        if i < len(coros) - 1:
            await aio.sleep(duration)
    results = await aio.gather(*tasks)
    return results