python并发编程实战（九）：使用多进程multiprocessing模块加速程序的运行（python多进程实现并发）

python并发编程实战（九）：使用多进程multiprocessing模块加速程序的运行（python多进程实现并发）

有了多线程threading，为什么还要用多进程multiprocessing

多进程multiprocessing知识梳理（对比多线程threading）

代码实战：单线程、多线程、多进程对比CPU密集计算速度

tmp/06.thread_process_cpu_bound.py

import mathfrom concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutorimport timePRIMES = [112272535095293] * 100def is_prime(n): if n < 2: return False if n == 2: return True if n % 2 == 0: return False sqrt_n = int(math.floor(math.sqrt(n))) for i in range(3, sqrt_n + 1, 2): if n % i == 0: return False return Truedef single_thread(): for number in PRIMES: is_prime(number)def multi_thread(): with ThreadPoolExecutor() as pool: pool.map(is_prime, PRIMES)def multi_process(): with ProcessPoolExecutor() as pool: pool.map(is_prime, PRIMES)if __name__ == '__main__': start = time.time() single_thread() end = time.time() print("single_thread, cost: ", end - start, "seconds") start = time.time() multi_thread() end = time.time() print("multi_thread, cost: ", end - start, "seconds") start = time.time() multi_process() end = time.time() print("multi_process, cost: ", end - start, "seconds")

运行结果：

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