#一個程序運行起來之後，代碼+用到的資源稱之為進程，它是操作系統分配資源的基本單位，不僅可以通過線程完成多任務，進程也是可以的
#進程之間是相互獨立的
#cpu密集的時候適合用多進程

#多進程並發
import multiprocessing
from multiprocessing import Pool
import time
def test1():
    for i in range(10):
        time.sleep(1)
        print(‘test‘, i)

def test2():
    for i in range(10):
        time.sleep(
 
1)
        print(‘test‘, i)

if __name__ == ‘__main__‘:
    p1 = multiprocessing.Process(target=test1)
    p2 = multiprocessing.Process(target=test2)
    p1.start()
    p2.start()

#進程之間不共享
import multiprocessing
from multiprocessing import Pool
import time
import threading
g_num = 0
def edit():
    
 
global g_num
    for i in range(10):
        g_num += 1

def reader():
    print(g_num)


if __name__ == ‘__main__‘:
    # t1 = threading.Thread(target=edit)
    # t2 = threading.Thread(target=reader)
    # t1.start()
    # t2.start()
    p1 = multiprocessing.Process(target=edit)
    p2 = multiprocessing.Process(target=reader())
    p1.start()
    p1.join()
    p2.start()
 

#進程池實現並發
import multiprocessing
from multiprocessing import Pool
import time
import threading
g_num = 0
def test1():
    for i in range(10):
        time.sleep(1)
        print(‘test1‘, i)

def test2():
    for i in range(10):
        time.sleep(1)
        print(‘test2‘, i)


if __name__ == ‘__main__‘:
    # t1 = threading.Thread(target=edit)
    # t2 = threading.Thread(target=reader)
    # t1.start()
    # t2.start()
    # p1 = multiprocessing.Process(target=edit)
    # p2 = multiprocessing.Process(target=reader())
    # p1.start()
    # p1.join()
    # p2.start()
    pool = Pool()
    pool.apply_async(test1)
    pool.apply_async(test2)
    pool.close()
    pool.join()

python3多進程和進程池