python concurrent.futures.ProcessPoolExecutor：.submit() 与 .map() 的性能

使用Python进行并发编程是一种提高程序性能的有效方法。在Python中，concurrent.futures模块提供了一个方便的接口来实现并行计算。其中，ProcessPoolExecutor是concurrent.futures模块中的一个类，它提供了一种使用进程池进行并发编程的方式。

python
import concurrent.futures
def calculate_square(x):
    return x ** 2
def main():
    numbers = [1, 2, 3, 4, 5]
    # 使用.submit()方法提交任务
    with concurrent.futures.ProcessPoolExecutor() as executor:
        futures = [executor.submit(calculate_square, number) for number in numbers]
        for future in concurrent.futures.as_completed(futures):
            result = future.result()
            print(result)
    # 使用.map()方法提交任务
    with concurrent.futures.ProcessPoolExecutor() as executor:
        results = executor.map(calculate_square, numbers)
        for result in results:
            print(result)
if __name__ == '__main__':
    main()