解决Python 进程池Pool中一些坑

q=Manager().Queue()#Manager中的Queue才能配合Pool
po = Pool() # 无穷多进程

p=Pool()
q=Manager().Queue()
with open('/home/cctv/data/stage_file/stage_{}.txt'.format(int(time.time())), 'w') as w1:
 p.apply_async(write_json, args=(video_path, 0,0.6,w1,q,i[0],))

import time 
from multiprocessing import Pool 
test = [1,2,3,4,5,6,7,8]
def run(fn):
 time.sleep(1)
 return fn*fn
s = time.time()
for i in test:
 run(i)
e = time.time()
print('直接循环 执行时间:',e - s)
pool = Pool(8)
s = time.time()
for i in test: 
 pool.apply(run, (i,))
e = time.time()
print('apply 执行时间:',e - s)
pool1 = Pool(8)
s = time.time()
res = []
for i in test: 
 r = [pool1.apply_async(run, (i,))]
 res.append(r)
pool1.close()
pool1.join()
e = time.time()
print([i.get() for i in r])
print('apply_async 执行时间:',e - s)
 
pool2 = Pool(8)
r = pool2.map(run,test)
pool2.close()
pool2.join() 
e1 = time.time()
print(r)
print('map执行时间:',e1 - e)
pool3 = Pool(8)
pool3.map_async(run,test)
pool3.close()
pool3.join() 
e1 = time.time()
print('map_async执行时间:',e1 - e)

直接循环 执行时间: 8.004754781723022
apply 执行时间: 8.016774654388428
[64]
apply_async 执行时间: 1.1128439903259277
[1, 4, 9, 16, 25, 36, 49, 64]
map执行时间: 1.181443452835083
map_async执行时间: 2.3679864406585693