#!-*-coding:utf-8-*-
#
加用户态的锁,与全局解释器锁不一样(GIL)
import threading, time
def run(n):
    lock.acquire()
#获取用户态锁 也叫互斥锁Mutex
   
global num #操作
    #time.sleep(0.1) #
加了sleep之后程序变串行的了 一般不要加
   
num +=1
   
lock.release() #释放用户态锁

lock=threading.Lock()
num=
0
t_objs = []
for i in range(1000):
    t = threading.Thread(
target=run, args=("t %s" % i,))
    t.start()
    t_objs.append(t) 
# 把每个线程实例都加进来 不阻塞后面线程的启动
for t in t_objs: #取列表里的每个线程
   
t.join() #等待并行的每个线程全都执行完毕 在往下走

print("----all threads has finished...",threading.current_thread(),threading.active_count())
print("num",num)

  

import threading, time
def run1():
   
print("grab the first part data")
    lock.acquire()
   
global num
    num +=
1
   
lock.release()
   
return num

def run2():
   
print("grab the second part data")
    lock.acquire()
   
global num2
    num2 +=
1
   
lock.release()
   
return num2

def run3():
    lock.acquire()
    res = run1()
   
print('--------between run1 and run2-----')
    res2 = run2()
    lock.release()
   
print(res, res2)

num, num2 =
0, 0
lock = threading.RLock() #递归锁
for i in range(1):
    t = threading.Thread(
target=run3)
    t.start()

while threading.active_count() != 1:
   
print(threading.active_count())
else:
   
print('----all threads done---')
   
print(num, num2)


import threading,time
def run(n):
    semaphore.acquire()
#信号量 相当于若干把锁 同时开启5个线程
   
time.sleep(1)
   
print("run the thread:%s\n"%n)
    semaphore.release()
#同时释放5把锁

if __name__=="__main__":
    semaphore=threading.BoundedSemaphore(
5) #最多允许5个线程同时运行 相当于有5把锁
   
for i in range(20):
        t=threading.Thread(
target=run,args=(i,))
        t.start()

while threading.active_count() !=1:
   
pass
else
:
   
print("---all threads done----")