标签：none open art div print 解释器 调度 style opened
参考博客： www.cnblogs.com/yuanchenqi/articles/5733873.html
并发：一段时间内做一些事情
并行：同时做多件事情
线程是操作系统能够进行运算调度的基本单位，一个线程就是一个指令集
IO 密集型任务或函数 计算密集型任务函数
t1 = threading.Thread( target=foo, args=( , ))
t1.start()
# _author: lily # _date: 2019/1/29 import threading import time class MyThread(threading.Thread): def __init__(self, num): threading.Thread.__init__(self) self.num = num def run(self): # 定义每个线程要运行的函数 print(‘running on number %s‘ % self.num) time.sleep(3) if __name__ == ‘__main__‘: t1 = MyThread(1) t2 = MyThread(2) t1.start() t2.start()
# _author: lily # _date: 2019/1/28 import threading import time def music(func): for i in range(2): print(‘listening to music %s.%s‘ % (func, time.ctime())) time.sleep(1) print(‘end listening %s‘ % time.ctime()) def move(func): for i in range(2): print(‘watching at the %s.%s‘ % (func, time.ctime())) time.sleep(5) print(‘end watching %s‘ % time.ctime()) threads = [] t1 = threading.Thread(target=music, args=(‘七里香‘, )) threads.append(t1) t2 = threading.Thread(target=move, args=(‘阿甘正传‘, )) threads.append(t2) if __name__ == ‘__main__‘: for t in threads: t.start() print(‘all over %s‘ % time.ctime())
GIL: 全局解释器锁。 对于一个进程，在同一时刻，python解释器中只允许一个线程运行。
结论：在 python里，如果是 io 密集型，可以用多线程
计算密集型，改 C。
守护线程： t.setDaemon(True) 当主线程结束之后就认为程序执行完毕，不会等待 t 线程执行完毕。
得到当前线程： print(threading.current_thread())
得到当前活着的线程： print(threading.active_count())
同步锁：
原因：1. 线程共享同一资源，且进行 IO 阻塞时，对资源的操作容易被覆盖
使用：r = threading.Lock()
同步锁与GIL关系：
没有GIL ，使用同步锁，可以达到一样得效果。
# _author: lily # _date: 2019/1/29 import time import threading num = 100 def add(): global num # num -= 1 r.acquire() temp = num # time.sleep(0.0000001) print(‘ok‘) num = temp - 1 r.release() thread_list = [] r = threading.Lock() for i in range(100): t = threading.Thread(target=add) t.start() thread_list.append(t) for thd in thread_list: thd.join() print(‘final num: ‘, num)
线程死锁和递归锁：
lock = threading.Lock()
lock = threading.RLock（）
# _author: lily # _date: 2019/1/29 import threading import time class MyThread(threading.Thread): def __init__(self, name): threading.Thread.__init__(self) self.name = name def run(self): self.do_a() self.do_b() def do_a(self): # lock_a.acquire() my_lock.acquire() print(‘do_a: thread %s get lock A‘ % self.name) time.sleep(3) my_lock.acquire() print(‘do_a: thread %s get lock B‘ % self.name) # lock_b.release() # lock_a.release() my_lock.release() my_lock.release() def do_b(self): # lock_b.acquire() my_lock.acquire() print(‘do_b: thread %s get lock B‘ % self.name) time.sleep(2) # lock_a.acquire() my_lock.acquire() print(‘do_b: thread %s get lock A‘ % self.name) # lock_a.release() # lock_b.release() my_lock.release() my_lock.release() # lock_a = threading.Lock() # lock_b = threading.Lock() my_lock = threading.RLock() thread_list = [] for i in range(5): t = MyThread(i) thread_list.append(t) t.start() for t in thread_list: t.join()
标签：none open art div print 解释器 调度 style opened
原文地址：https://www.cnblogs.com/mlllily/p/10336543.html
