python线程池ThreadPoolExecutor和进程池ProcessPoolExecutor使用

Python线程池与进程池介绍

最新推荐文章于 2025-10-30 15:32:08 发布

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#python编程 #进程池 #线程池

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博客主要介绍了Python编程中的线程池ThreadPoolExecutor和进程池ProcessPoolExecutor，聚焦于信息技术领域中Python多线程和多进程的相关内容。

1、线程池ThreadPoolExecutor

"""
    线程池，使用单核CPU
"""
from concurrent.futures import ThreadPoolExecutor
import random
import time
import threading
from datetime import datetime
import multiprocessing
import numpy as np


def print_func(x):
    sleep_time = random.randint(1, 10)
    sleep_time = 2
    time.sleep(sleep_time)
    # 线程中进行大计算量，观察CPU使用情况，使用单核CPU
    x1 = np.random.rand(1000, 1000)
    x2 = np.random.rand(1000, 1000)
    y = np.matmul(x1, x2)
    print("current time: {}, process id: {}, thread id: {}, get: {}, sleep time: {}s".format(
        datetime.now().strftime("%Y-%m-%d %H:%M:%S"), multiprocessing.current_process().ident,
        threading.currentThread().ident,
        x, sleep_time))
    return x


print("strart time: {}".format(datetime.now().strftime("%Y-%m-%d %H:%M:%S")))
pool = ThreadPoolExecutor(max_workers=4)
task_list = []
for i in range(50):
    # 默认异步提交任务到线程池
    task = pool.submit(print_func, i)
    task_list.append(task)
    """
    status = task.done()
    # 同步等待线程返回结果
    while not status:
        status = task.done()
    # 线程执行完成后，done()返回为True，获取线程返回结果
    result = task.result()
    # print("result: {}".format(result))
    """
for task in task_list:
    while not task.done():
        continue
    print(task.result())
end_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
print("end time: {}".format(end_time))

2、进程池ProcessPoolExecutor

"""
    进程池，使用多核CPU
"""
from concurrent.futures import ProcessPoolExecutor
import random
import time
import threading
from datetime import datetime
import multiprocessing
import numpy as np


def print_func(x):
    sleep_time = random.randint(1, 10)
    sleep_time = 2
    time.sleep(sleep_time)
    x1 = np.random.rand(1000, 1000)
    x2 = np.random.rand(1000, 1000)
    y = np.matmul(x1, x2)

    print("current time: {}, process id: {}, thread id: {}, get: {}, sleep time: {}s".format(
        datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
        multiprocessing.current_process().ident,
        threading.currentThread().ident,
        x, sleep_time))
    return x


if __name__ == '__main__':
    print("strart time: {}".format(datetime.now().strftime("%Y-%m-%d %H:%M:%S")))
    pool = ProcessPoolExecutor(max_workers=4)
    task_list = []
    for i in range(50):
        # 默认异步提交任务到进程池
        task = pool.submit(print_func, i)
        task_list.append(task)
        """
        status = task.done()
        # 同步等待进程返回结果
        while not status:
            status = task.done()
        # 进程执行完成后，done()返回为True，获取进程返回结果
        result = task.result()
        print("result: {}".format(result))
        """
    for task in task_list:
        while not task.done():
            continue
        print(task.result())
    end_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    print("end time: {}".format(end_time))