python-threading模块&多线程&守护线程&线程锁

 1 import threading,time
 2 
 3 def insert_db():
 4     time.sleep(3)
 5     print(‘insert_db over‘)
 6 
 7 
 8 start_time = time.time()
 9 for i in range(3): # 串行的方式
10     insert_db()
11 end_time = time.time()
12 print(‘串行的执行时间：‘,end_time-start_time)
13 
14 start_time2 = time.time()
15 # 第二种方式，思路是判断当前存活的线程个数
16 for i in range(3):
17     t = threading.Thread(target = insert_db)
18     t.start()
19 
20 # threading.activeCount()返回当前活跃的线程数
21 while threading.activeCount() != 1:
22     pass
23 end_time2 = time.time()
24 
25 print(‘多线程的执行时间：‘,end_time2-start_time2)
26 print(‘over.....‘)

 1 import threading,time
 2 
 3 def insert_db():
 4     time.sleep(3)
 5     print(‘insert_db over‘)
 6 
 7 
 8 start_time = time.time()
 9 for i in range(3): # 串行的方式
10     insert_db()
11 end_time = time.time()
12 print(‘串行的执行时间：‘,end_time-start_time)
13 
14 # 统计多线程执行时间：方式一
15 threads = []
16 start_time2 = time.time()
17 for i in range(3):
18     t = threading.Thread(target=insert_db)
19     t.start()
20     threads.append(t)
21 
22 for t in threads:
23     t.join() # 等待子线程执行完成，主线程在接着执行
24 
25 end_time2 = time.time()
26 
27 print(‘多线程的执行时间：‘,end_time2-start_time2)
28 print(‘over.....‘)

 1 import threading,time
 2 
 3 def insert_db():
 4     time.sleep(3)
 5     print(‘insert_db over‘)
 6 
 7 
 8 start_time = time.time()
 9 for i in range(3): # 串行的方式
10     insert_db()
11 end_time = time.time()
12 print(‘串行的执行时间：‘,end_time-start_time)
13 
14 # 统计多线程执行时间：方式一
15 threads = []
16 start_time2 = time.time()
17 for i in range(3):
18     t = threading.Thread(target=insert_db)
19     t.start()
20     threads.append(t)
21 
22 # for t in threads:
23 #     t.join() # 等待子线程执行完成，主线程在接着执行
24 
25 end_time2 = time.time()
26 
27 # 多线程的执行时间： 0.0010039806365966797？？为啥不对？
28 # 主线程，也就是程序一开始运行的时候，最初的那个线程
29 # 这里的时间是主线程跑完的时间，没包含子线程执行的时间
30 # 子线程，通过thread类实例化的线程，都是子线程
31 print(‘多线程的执行时间：‘,end_time2-start_time2)
32 print(‘over.....‘)

 1 import threading
 2 import requests
 3 import hashlib
 4 
 5 def down_load(url):
 6     name = hashlib.md5(url.encode()).hexdigest()
 7     r = requests.get(url)
 8     with open(‘%s.jpg‘%name,‘wb‘) as fw:
 9         fw.write(r.content)
10 
11 
12 l = [
13     ‘http://www.nnzhp.cn/wp-content/themes/QQ/images/logo.jpg‘,
14     ‘http://www.nnzhp.cn/wp-content/uploads/2016/12/2016aj5kn45fjk5-150x150.jpg‘,
15     ‘http://www.nnzhp.cn/wp-content/themes/QQ/images/thumbnail.png‘
16 ]
17 
18 # 串行下载
19 for url in l:
20     down_load(url)
21 
22 # 多线程下载
23 for i in l:
24     t = threading.Thread(target=down_load,args=[i])
25     t.start()
26 
27 while threading.activeCount() != 1:
28     pass
29 
30 print(‘down load over ...‘)

1 # #多线程运行函数是，函数的返回值是拿不到的
2 # #所以定义一个list，把函数运行的结果都存进去就ok
3 # case_result = []
4 #
5 # def run_case(case_name):
6 #     print(‘run case...‘,case_name)
7 #     case_result.append({case_name:‘success‘})

 1 # 守护线程:一旦主线程死掉，那么守护线程不管有没有执行完成，全部结束
 2 
 3 import threading
 4 import time
 5 
 6 def talk(name):
 7     print(‘正在和%s聊天‘%name)
 8     time.sleep(200)
 9 
10 def shipin(name):
11     print(‘正在和%s视频‘%name)
12     time.sleep(300)
13 
14 print(‘qq主窗口‘)
15 t1 = threading.Thread(target=talk,args=[‘lzh‘])
16 # 如果没有设置为守护线程，所有线程运行结束后，程序才会结束
17 # 设置线程为守护线程
18 t1.setDaemon(True)
19 t1.start()
20 
21 
22 t2 = threading.Thread(target=shipin,args=[‘zsb‘])
23 # 设置线程为守护线程
24 t2.setDaemon(True)
25 t2.start()
26 
27 
28 time.sleep(5)
29 print(‘结束。。。‘)
30 
31 #所有线程运行结束后，程序才会结束

 1 # 线程锁
 2 #多个线程同时操作同一个数据的时候，会有问题
 3 
 4 import  threading
 5 
 6 count = 0
 7 lock = threading.Lock()
 8 
 9 def test():
10     global  count
11 
12     #lock.acquire(timeout = 3) #加锁,单位？？
13 
14     count += 1
15 
16     # lock.release() #解锁
17     # 线程死锁
18 
19 for i in range(100):
20     t = threading.Thread(target = test)
21     t.start()
22 
23 print(count)