26 python 初学（线程、同步锁、死锁和递归锁）

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

1. 使用 join 就会造成船串行，失去了多线程的意义

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()