gil 在CPU密集型多线程和单线程执行效率对比

直接用单线程执行for循环，执行5次，计算执行的时间

import logging
import datetime

FORMAT = '%(threadName)s %(thread)d %(message)s'
logging.basicConfig(format=FORMAT, level=logging.INFO)

start = datetime.datetime.now()

def calc():
    sum = 0
    for _ in range(100000000):
        sum += 1

calc()
calc()
calc()
calc()
calc()

delta = (datetime.datetime.now() - start).total_seconds()
logging.info(delta)

用多线程的方式，同样的for循环，使用5个线程跑，统计执行的时间

import threading
import logging
import datetime

FORMAT = '%(threadName)s %(thread)d %(message)s'
logging.basicConfig(format=FORMAT, level=logging.INFO)

start = datetime.datetime.now()

def calc():
    sum = 0
    for _ in range(100000000000):
        sum += 1
lst = []
for i in range(5):
    t = threading.Thread(target=calc, )
    lst.append(t)
    t.start()

for i in lst:
    i.join()

delta = (datetime.datetime.now() - start).total_seconds()
logging.info(delta)

两个测试结果来看，在CPython中，对于CPU密集型而言，多线程没特别大的优势，和一个线程的执行时间相差不是特别大