Python中如何实现带优先级、超时和延迟的进程池

2023-04-11 00:00:00 优先级超时延迟

Python中可以通过标准库multiprocessing中的Pool类和Queue类实现带优先级、超时和延迟的进程池。具体实现步骤如下：

创建任务队列及各种参数的队列。

from multiprocessing import Pool, Queue

tasks_queue = Queue()
priority_queue = Queue()
timeout_queue = Queue()
delay_queue = Queue()

往任务队列中添加任务。

tasks_queue.put(('pidancode.com',))
tasks_queue.put(('皮蛋编程',))

从队列中获取各种参数，并将任务加入进程池。

pool = Pool(processes=4)

while True:
    try:
        task = tasks_queue.get(timeout=1)
        priority = priority_queue.get(timeout=1)
        timeout = timeout_queue.get(timeout=1)
        delay = delay_queue.get(timeout=1)

        result = pool.apply_async(run_task, task, priority=priority)
        results[result] = timeout

        time.sleep(delay)

    except Empty:
        if len(results) == 0:
            break

运行任务的函数run_task需要支持优先级、超时和延迟。

import time

def run_task(task, priority=0):
    print('Running %s with priority %d' % (task[0], priority))
    time.sleep(1)
    return task

在上述代码中，我们需要借助一个字典results来保存任务的结果和超时时间，每隔一段时间检查这个字典中的任务是否超时，若已超时则从进程池中终止该任务。这里简单演示一下如何检查任务是否超时。

for result, timeout in results.items():
    if timeout > 0:
        timeout -= 1
        results[result] = timeout
    else:
        result.terminate()
        results.pop(result)

完整代码如下：

from multiprocessing import Pool, Queue
from queue import Empty
import time

def run_task(task, priority=0):
    print('Running %s with priority %d' % (task[0], priority))
    time.sleep(1)
    return task

tasks_queue = Queue()
priority_queue = Queue()
timeout_queue = Queue()
delay_queue = Queue()

tasks_queue.put(('pidancode.com',))
tasks_queue.put(('皮蛋编程',))

pool = Pool(processes=4)
results = {}

while True:
    try:
        task = tasks_queue.get(timeout=1)
        priority = priority_queue.get(timeout=1)
        timeout = timeout_queue.get(timeout=1)
        delay = delay_queue.get(timeout=1)

        result = pool.apply_async(run_task, task, priority=priority)
        results[result] = timeout

        time.sleep(delay)

    except Empty:
        if len(results) == 0:
            break

    for result, timeout in results.items():
        if timeout > 0:
            timeout -= 1
            results[result] = timeout
        else:
            result.terminate()
            results.pop(result)

此处没有实现真正的优先级机制，只是让任务可传入优先级参数，并打印出来以作演示。可以根据实际需求对此代码做些修改。

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