import multiprocessing as mp

def job(a,b):
 print('abc')
if __name__=='__main__':
 p1=mp.Process(target=job,args=(1,2))
 p1.start()
 p1.join()

import multiprocessing as mp

def job(q):
 res=0
 for i in range(1000):
 res+=i+i**2+i**3
 q.put(res)

 
if __name__ == '__main__':
 q=mp.Queue()
 p1 = mp.Process(target=job,args=(q,))#注意当参数只有一个时，应加上逗号
 p2 = mp.Process(target=job,args=(q,)) 
 p1.start()
 p2.start()
 
 p1.join()
 p2.join()
 res1=q.get()
 res2=q.get()
 print(res1+res2)

import multiprocessing as mp
import threading as td
import time

def job(q):
 res = 0
 for i in range(10000000):
 res += i+i**2+i**3
 q.put(res) # queue

def multicore():
 q = mp.Queue()
 p1 = mp.Process(target=job, args=(q,))
 p2 = mp.Process(target=job, args=(q,))
 p1.start()
 p2.start()
 p1.join()
 p2.join()
 res1 = q.get()
 res2 = q.get()
 print('multicore:' , res1+res2)

def normal():
 res = 0
 for _ in range(2):#线程或进程都构造了两个，进行了两次运算，所以这里循环两次
 for i in range(10000000):
  res += i+i**2+i**3
 print('normal:', res)

def multithread():
 q = mp.Queue()
 t1 = td.Thread(target=job, args=(q,))
 t2 = td.Thread(target=job, args=(q,))
 t1.start()
 t2.start()
 t1.join()
 t2.join()
 res1 = q.get()
 res2 = q.get()
 print('multithread:', res1+res2)

if __name__ == '__main__':
 st = time.time()
 normal()
 st1= time.time()
 print('normal time:', st1 - st)
 multithread()
 st2 = time.time()
 print('multithread time:', st2 - st1)
 multicore()
 print('multicore time:', time.time()-st2)

import multiprocessing as mp

def job(x):
 return x*x

def multicore():
 pool=mp.Pool(processes=2)#定义一个Pool，并定义CPU核数量为2
 res=pool.map(job,range(10))
 print(res)
 res=pool.apply_async(job,(2,))
 print(res.get())
 multi_res=[pool.apply_async(job,(i,)) for i in range(10)]
 print([res.get()for res in multi_res])

if __name__=='__main__':
 multicore()

res=pool.apply_async(job,(2,))
print(res.get())

res = pool.apply_async(job, (2,3,4,))

TypeError: job() takes exactly 1 argument (3 given)

multi_res = [pool.apply_async(job, (i,)) for i in range(10)]

print([res.get() for res in multi_res])

import multiprocessing as mp

value1 = mp.Value('i', 0) 
value2 = mp.Value('d', 3.14)

array = mp.Array('i', [1, 2, 3, 4])

import multiprocessing as mp
import time

def job(v,num):
 for _ in range(10):
 time.sleep(0.1)#暂停0.1s，让输出效果更明显
 v.value+=num #v.value获取共享变量值
 print(v.value)
 
def multicore():
 v=mp.Value('i',0)#定义共享变量
 p1=mp.Process(target=job,args=(v,1))
 p2=mp.Process(target=job,args=(v,3))
 p1.start()
 p2.start()
 p1.join()
 p2.join()


if __name__=='__main__':
 multicore()

 l = mp.Lock() # 定义一个进程锁

 p1 = mp.Process(target=job, args=(v,1,l)) # 需要将Lock传入
 p2 = mp.Process(target=job, args=(v,3,l)) 

def job(v, num, l):
 l.acquire() # 锁住
 for _ in range(5):
 time.sleep(0.1) 
 v.value += num # v.value获取共享内存
 print(v.value)
 l.release() # 释放

def job(v, num, l):
 l.acquire() # 锁住
 for _ in range(5):
 time.sleep(0.1) 
 v.value += num # 获取共享内存
 print(v.value)
 l.release() # 释放

def multicore():
 l = mp.Lock() # 定义一个进程锁
 v = mp.Value('i', 0) # 定义共享内存
 p1 = mp.Process(target=job, args=(v,1,l)) # 需要将lock传入
 p2 = mp.Process(target=job, args=(v,3,l)) 
 p1.start()
 p2.start()
 p1.join()
 p2.join()

if __name__ == '__main__':
 multicore()