python cpu密集运算为何要使用多进程？
由于GIL的存在python 的多线程在cpu密集情况下基本没用，反而效率降低。但是为什么使用多进程可以有效利用处理器的多个核心？
多进程时每个进程不也是分时占用cpu的吗？多进程时每个进程只有一个主线程，也只占用处理器一个核心，但是为什么代码测试多进程可以占满所有cpu核心呢？
代码：
#!python3
import time
import os, sys, getopt
from threading import Thread
from multiprocessing import Process
import logging, coloredlogs
logger = logging.getLogger('TIMER')
formatter = logging.Formatter('%(asctime)s %(msecs)03d : %(message)s')
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s',
# datefmt='%a, %d %b %Y %H:%M:%S'
)
ProcessNum = 1
def loop():
start =time.process_time()
mr = 300000000
pr = 0
for i in range(0,mr):
pr = i
end = time.process_time()
logger.warning('pid {} coast time: {}'.format(os.getpid(),str(end-start)[:5] ))
def muti_process():
for i in range(ProcessNum):
t = Process(target=loop)
t.start()
logger.warning('start.... muti_process')
def muti_threads():
for i in range(1):
t = Thread(target=loop)
t.start()
logger.warning('start.... muti_threads')
if __name__ == '__main__':
muti_process()
# muti_threads()修改ProcessNum = 1，2，3，4 测试得到如下结果：
ProcessNum = 1
2019-05-11 21:18:03,469 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:18:14,419 process.py[line:22] WARNING pid 3849 coast time: 10.89ProcessNum = 2
2019-05-11 21:18:39,443 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:18:39,445 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:18:50,638 process.py[line:22] WARNING pid 3856 coast time: 11.14
2019-05-11 21:18:50,644 process.py[line:22] WARNING pid 3857 coast time: 11.15ProcessNum =3
2019-05-11 21:19:01,319 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:19:01,321 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:19:01,324 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:19:17,286 process.py[line:22] WARNING pid 3864 coast time: 15.61
2019-05-11 21:19:17,415 process.py[line:22] WARNING pid 3863 coast time: 15.78
2019-05-11 21:19:17,466 process.py[line:22] WARNING pid 3862 coast time: 15.82ProcessNum =4
2019-05-11 21:19:28,140 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:19:28,143 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:19:28,147 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:19:28,157 process.py[line:29] WARNING start.... muti_process
2019-05-11 21:19:48,927 process.py[line:22] WARNING pid 3867 coast time: 19.68
2019-05-11 21:19:49,049 process.py[line:22] WARNING pid 3870 coast time: 19.68
2019-05-11 21:19:49,085 process.py[line:22] WARNING pid 3869 coast time: 19.65
2019-05-11 21:19:49,092 process.py[line:22] WARNING pid 3868 coast time: 19.64代码运行环境，操作系统: osx Mojave ，CPU ：2.7G core i5(物理双核 支持超线程）， python： Python 3.7.1
当 ProcessNum = 1 时可以看到 运行loop中的代码一个进程需要几乎11秒的时间。
当 ProcessNum = 2 时， 每个进程运行的时间也为11秒多一点，总时间也只花了大约11秒，也就是说 2个进程应该是并行运行的？？
问题就是这里的2个进程可以同时运行在同一个处理器的不同核心上？
当 ProcessNum = 3 时总时间为 15.7秒 ，这相当于 3个进程运行在2个核心上，每个进程花了10秒左右。
当 ProcessNum = 4 时总时间为 19.6秒 ，这相当于 4个进程运行在2个核心上，每个进程花了10秒左右。
为何会产生这样的测试结果？
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