gil 在CPU密集型多線程和單線程執行效率對比

直接用單線程執行for循環，執行5次，計算執行的時間

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)

用多線程的方式，同樣的for循環，使用5個線程跑，統計執行的時間

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)

兩個測試結果來看，在CPython中，對於CPU密集型而言，多線程沒特別大的優勢，和一個線程的執行時間相差不是特別大