线程vs进程

速度

from multiprocessing import Process from threading import Thread import time def test(): pass if __name__ == '__main__': p = Process(target=test) t = Thread(target=test) start1 = time.time() p.start() p.join() end1 = time.time() start2 = time.time() t.start() t.join() end2 = time.time() print(end1 - start1) print(end2 - start2)

线程要远快于进程

资源共享

from multiprocessing import Process from threading import Thread import time x = 1 def test(): global x x= 100 print("我完成了") if __name__ == '__main__': # 查看进程是否可修改数据 p = Process(target=test) p.start() time.sleep(2) print(x) # 查看线程是否可修改数据 # t = Thread(target=test) # t.start() # # time.sleep(1) # print(x)

线程共享资源

进程间彼此隔离

何时使用多进程 和 何时使用多进程

import time from multiprocessing import Process from threading import Thread,Timer # 计算密集型函数 def compute_intensive(): res = 0 for i in range(10000000): res += 1 def block_intensive(): time.sleep(3) if __name__ == '__main__': start = time.time() p_l = [] for i in range(10): p = Process(target=compute_intensive) p_l.append(p) p.start() for i in p_l: i.join() end = time.time() print("多进程计算密集型用时", end - start, '秒') start1 = time.time() t_l = [] for i in range(10): t = Thread(target=compute_intensive) t_l.append(t) t.start() for i in t_l: i.join() end1 = time.time() print("多线程计算密集型用时", end1 - start1, '秒') print() start2 = time.time() p_l = [] for i in range(10): p = Process(target=block_intensive) p_l.append(p) p.start() for i in p_l: i.join() end2 = time.time() print("多进程IO密集型用时", end2 - start2, '秒') start3 = time.time() t_l = [] for i in range(10): t = Thread(target=block_intensive) t_l.append(t) t.start() for i in t_l: i.join() end3 = time.time() print("多线程IO密集型用时", end3 - start3, '秒')

计算密集型使用多进程

IO密集型使用多线程

转载于:https://www.cnblogs.com/marklijian/p/11575193.html

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