Python_multiprocessing1.py

#Python_multiprocessing1.py
#2create processing
'''
import multiprocessing as mp
#import threading as td

def job(a,d):
    print('aaa')

if __name__=='__main__':
    #t1=td.Thread(target=job,args=(1,2))
    p1=mp.Process(target=job,args=(1,2))
    
    #t1.start()
    p1.start()
    #t1.join()
    p1.join()
#windows need to cmd model running
##C:\DATA\Python>python Python_multiprocessing1.py
##aaa
##C:\DATA\Python>
'''

#3.queue processing output

'''
#mp.Process can't retrn , need use queue.

import multiprocessing as mp
def job(q):
    res=0
    for i in range(100):
        res += i+i**2+i**3
    q.put(res)

if __name__=='__main__':
    q=mp.Queue()
    p1=mp.Process(target=job,args=(q,))     #note:q,
    p2=mp.Process(target=job,args=(q,))
    
    p1.start()
    p2.start()
    p1.join()
    p2.join()
    res1=q.get()
    res2=q.get()
    print(res1+res2)
    
'''

#4.multiprocessing comparison
'''
import multiprocessing as mp
import threading as td
import time

def job(q):
    res=0
    for i in range(1000000):
        res += i+i**2+i**3
    q.put(res)

def multicore():
    q=mp.Queue()
    p1=mp.Process(target=job,args=(q,))     #note: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):
        for i in range(1000000):
            res += i+i**2+i**3
    print('normal:',res)

def multithread():
    q=mp.Queue()
    t1=td.Thread(target=job,args=(q,))     #note: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()
    st3=time.time()
    print('multicore time:',st3-st2)

'''


#5.multiprocessing pool    
'''    
import multiprocessing as mp

def job(x):
    return x*x

def multicore():
    pool=mp.Pool(processes=2)                   #core number\
    
    res=pool.map(job,range(10))                 #map:auto assign resource
    print(res)
    
    res = pool.apply_async(job,(2,))            #apply_async:just one process
    print(res.get())
    
    multi_res=[pool.apply_async(job,(i,)) for i in range(10)]
    print([res.get() for res in multi_res])     #map AND Iteration
            

if __name__=='__main__':
    multicore()
'''

#6.multiprocessing shared memory
'''
import multiprocessing as mp
value=mp.Value('d',1)           #(type,vlaue)
array=mp.Array('i',[1,2,3])     #just list,can't multiarry
'''

#7.multiprocessing lock
import multiprocessing as mp
import time

def job(v,num,l):
    l.acquire()
    for _ in range(10):
        time.sleep(0.1)
        v.value += num
        print(v.value)
    l.release()

def multicore():
    l=mp.Lock()
    v=mp.Value('i',0)
    p1=mp.Process(target=job, args=(v,1,l))
    p2=mp.Process(target=job, args=(v,3,l))
    p1.start()
    p2.start()
    p1.join()
    p2.join()

if __name__=='__main__':
    multicore()