Python学习day36-并发编程(2)

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Python学习day36-并发编程(2)Process的一些常用方法和属性join获取当前进程pid和父进程pidname和is_aliveterminatedaemonTips:抢票软件的原理

Python学习day36-并发编程(2)

Process的一些常用方法和属性

join

join的主要用法是在于可以让主进程等待子进程运行完后,再执行下面的语句.要注意的一点是,主进程在等待,但是子进程在正常运行.

下面是join一些简单用法,包括串行,并行以及并行的优化

 

 

 

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1

from multiprocessing import Process

2

import time

3

​

4

def foo():

5

print('进程start')

6

time.sleep(2)

7

print('进程end')

8

if __name__ == '__main__':

9

p = Process(target=foo)

10

p.start()

11

time.sleep(5)

12

p.join()  # 要等待该子进程全部执行完才会继续向下运行,主进程在等待,子进程在运行,内部会调用wait(),回收其子进程的pid号

13

print('主')

14

15

16

# 输出结果为:

17

# 进程start

18

# 进程end

19

# 主

20

​

21

​

22

​

23

# 串行,开辟内存空间要多费时间

24

def foo(x):

25

print(f'{x}进程start')

26

time.sleep(x)

27

print(f'{x}进程end')

28

if __name__ == '__main__':

29

p = Process(target=foo, args=(3,))

30

p2 = Process(target=foo, args=(2,))

31

p3 = Process(target=foo, args=(1,))

32

start = time.time()

33

p.start()

34

p.join()

35

p2.start()

36

p2.join()

37

p3.start()

38

p3.join()

39

# time.sleep(5)

40

end = time.time()

41

print(f'{end-start}')

42

print('主')

43

# 结果为:

44

# 3进程start

45

# 3进程end

46

# 2进程start

47

# 2进程end

48

# 1进程start

49

# 1进程end

50

# 6.7584381103515625这个时间不是绝对的,会根据所在机器的性能变化

51

# 主

52

​

53

​

54

​

55

# 并行,真正的同时运行

56

def foo(x):

57

print(f'{x}进程start')

58

time.sleep(x)

59

print(f'{x}进程end')

60

if __name__ == '__main__':

61

p = Process(target=foo, args=(10,))

62

p2 = Process(target=foo, args=(2,))

63

p3 = Process(target=foo, args=(1,))

64

start = time.time()

65

p.start()

66

p2.start()

67

p3.start()

68

# time.sleep(5)

69

p.join()  

70

p2.join()

71

p3.join()

72

end = time.time()

73

print(f'{end-start}')

74

print('主')

75

​

76

# 结果为:

77

# 2进程start

78

# 3进程start

79

# 1进程start

80

# 1进程end

81

# 2进程end

82

# 3进程end

83

# 3.3003978729248047

84

# 主

85

​

86

​

87

# 上述这种并行的发生看起来非常的麻烦,所以我们其实可以用一个循环把下面重复性的创建进程以及join暂停进程都放到循环里,简化代码.

88

# 并行的优化

89

​

90

def foo(x):

91

print(f'{x}进程start')

92

time.sleep(x)

93

print(f'{x}进程end')

94

​

95

​

96

if __name__ == '__main__':

97

start = time.time()

98

p_list = []# 创建一个p_list列表用来接收创建的子进程

99

for i in range(1, 4):

100

p = Process(target=foo, args=(i,))

101

p.start()

102

p_list.append(p)

103

for p in p_list:#将列表里的子进程一一拿出来循环,然后通过join分别暂停主进程,从而达到并行的目的

104

p.join()

105

end = time.time()

106

print(end - start)

107

print('主')

108

109

110

# 结果为:

111

# 2进程start

112

# 1进程start

113

# 3进程start

114

# 1进程end

115

# 2进程end

116

# 3进程end

117

# 3.275794744491577

118

# 主

 

 

获取当前进程pid和父进程pid

获取当前进程pid的常用方式有两种,分别是:

os.getpid(),这是os模块所带有的方法,可以查看当前进程的pid号

os.getppid(),注意这里是ppid,多了一个p,是查看当前进程的父进程的pid号

子进程对象.pid

 

 

 

xxxxxxxxxx

30

 

 

 

 

1

from multiprocessing import Process, current_process  # 获取当前进程的对象

2

​

3

import time, os

4

​

5

​

6

def task():

7

print('子进程start')

8

print('在子进程中查看自身的pid', current_process().pid)

9

print('在子进程中查看自身的pid', os.getpid())

10

print('在子进程中查看父进程的pid', os.getppid())

11

time.sleep(200)

12

print('子进程end')

13

​

14

​

15

if __name__ == '__main__':

16

p = Process(target=task)

17

p.start()

18

print('在主进程查看子进程的pid', p.pid)  # 一定写在子进程启动之后,即start之后

19

print('主进程pid', os.getpid())

20

print('主')

21

22

23

# 运行结果为:(这里pid每次执行都是不一样的,都是重新分配的)

24

# 在主进程查看子进程的pid 9964

25

# 主进程pid 11584

26

# 主

27

# 子进程start

28

# 在子进程中查看自身的pid 9964

29

# 在子进程中查看自身的pid 9964

30

# 在子进程中查看父进程的pid 11584

 

 

name和is_alive

name() 进程名称,可以手动定义

is_alive() 判断进程是否还存在,只要运行完了就返回false,即便是僵尸进程也是false

 

 

 

xxxxxxxxxx

31

 

 

 

 

1

from multiprocessing import Process, current_process

2

import time

3

​

4

​

5

def foo():

6

print('进程start')

7

print(current_process().name)

8

time.sleep(2)

9

print('进程end')

10

​

11

​

12

if __name__ == '__main__':

13

p = Process(target=foo, name='nick')

14

# p2 = Process(target=foo, name='jack')

15

# p3 = Process(target=foo, name='mata')

16

p.start()

17

# p2.start()

18

# p3.start()

19

print(p.is_alive())# 判定进程是否还活着,返回值是True活着False

20

print(p.name)# 输出进程的名字,也可以是自身赋予的值,如果自己没有赋值系统默认的就是Process-数字

21

# print(p2.name)

22

# print(p3.name)

23

​

24

25

# 结果是:

26

# True

27

# nick

28

# 进程start

29

# nick

30

# 进程end

31

​

 

 

terminate

手动结束子进程,但其实只是给操作系统发送了一个关闭进程的请求,需要时间才能完成,推荐在后面加上p.join()来实时判断进程是否已经结束了,也就是说进程只有执行完了才会进行下面的语句.

 

 

 

xxxxxxxxxx

18

 

 

 

 

1

from multiprocessing import Process, current_process

2

import time

3

​

4

​

5

def foo():

6

print('进程start')

7

print(current_process().name)

8

time.sleep(2)

9

print('进程end')

10

​

11

​

12

if __name__ == '__main__':

13

p = Process(target=foo, name='nick')

14

p.start()

15

p.terminate()

16

# p.join()

17

print(p.is_alive())

18

# print(p.name)

 

 

daemon

守护进程(本质就是一个子进程)

1. 守护进程会在父进程结束之后就随之结束(实际上父进程代码执行完了守护进程就会结束,而不是父进程完全结束)
2. 守护进程不能创建子进程

 

 

 

x

 

 

 

 

1

from multiprocessing import Process, current_process

2

import time

3

​

4

​

5

def foo():

6

print('守护进程start', time.time())

7

time.sleep(3)

8

print('守护进程end', time.time())

9

​

10

​

11

def task():

12

print('子进程start', time.time())

13

time.sleep(5)

14

print('子进程end', time.time())

15

​

16

​

17

if __name__ == '__main__':

18

p = Process(target=foo, name='nick')

19

p2 = Process(target=task, name='nick')

20

p.daemon = True  # 定义为守护进程,必须要在start之前定义

21

p.start()

22

p2.start()

23

time.sleep(2)

24

print('主', time.time())

25

# 结果为:

26

# 守护进程start 1568278460.6168563

27

# 子进程start 1568278460.6188455

28

# 主 1568278462.376258

29

# 子进程end 1568278465.6189692

30

​

31

​

32

# 可以看到上述例程的结果里没有守护进程结束的输出语句,因为父进程已经结束了,所以守护进程跟随父进程结束了,后面的就没有打印.

 

 

Tips:抢票软件的原理

先来语言分析一波,抢票的总体流程是怎样的,12306的数据库里肯定有实时的票数以及票价,我们购买的时候呢,就要发一个请求,包括查询和购买都要发请求,然后12306的服务器给我们返回数据库里的票数,可是我们都知道,网络是有延迟的,数据传输也是需要时间的,所以很可能同时有很多人,同时查询这个车次的票,然后得到还有一张票的消息(比如),然后这些人都点击购买,那么12306会把这个票给哪个用户呢?

其实这种情况下我们如果用并行进程的概念是行不通的,因为延迟的情况下就有可能很多人都买到了这张票,可是实际情况是不可能的,所以这里为了数据的安全以及逻辑的缜密,我们就要牺牲效率,转而用串行的方法来处理这个事情,尽管效率会慢很多,但是不会出现一张票同时卖给很多人的情况.也就是说用join方法来实现串行.

例程如下:

 

 

 

x

 

 

1

# 这里我们需要在文件的同目录创建一个db.txt文件

2

# 在文件里写{"count": 1}

3

from multiprocessing import Process, current_process

4

import time

5

import json

6

import os

7

​

8

​

9

def search():

10

    time.sleep(1)  # 模拟网络io

11

    with open('db.txt', 'rt', encoding='utf-8')as f:

12

        res = json.load(f)

13

        print(f'还剩{res["count"]}张票')

14

​

15

​

16

def get():

17

    with open('db.txt', 'rt', encoding='utf-8')as f:

18

        res = json.load(f)

19

        print(f'还剩{res["count"]}张票')

20

    time.sleep(1)  # 模拟网络io

21

    if res['count'] > 0:

22

        res['count'] -= 1

23

        with open('db.txt', 'wt', encoding='utf-8')as f:

24

            json.dump(res, f)

25

            f.flush()

26

            print(f'{os.getpid()}抢票成功')

27

            time.sleep(1)  # 模拟网络io

28

​

29

    else:

30

        print('票已经售空!~!~!~!~!~!~!~!')

31

    # current_process().terminate()

32

​

33

​

 

 

34

def task():

35

    #search()

36

    get()

37

​

38

​

39

if __name__ == '__main__':

40

    for i in range(5):

41

        p = Process(target=task)

42

        p.start()

43

        p.join()

44

# 输出结果为:

45

# 还剩1张票

46

# 11576抢票成功

47

# 还剩0张票

48

# 票已经售空!~!~!~!~!~!~!~!

49

# 还剩0张票

50

# 票已经售空!~!~!~!~!~!~!~!

51

# 还剩0张票

52

# 票已经售空!~!~!~!~!~!~!~!

53

# 还剩0张票

54

# 票已经售空!~!~!~!~!~!~!~!

55

​

 

 

当然实际的抢票软件肯定做了更多的优化,不会这么简单,但是大概逻辑是差不多的.