python threading库_python中threading和queue库实现多线程编程

秒速五厘米 2022-10-22 11:51 165阅读 0赞

摘要

本文主要介绍了利用python的 threading和queue库实现多线程编程，并封装为一个类，方便读者嵌入自己的业务逻辑。最后以机器学习的一个超参数选择为例进行演示。

多线程实现逻辑封装

实例化该类后，在.object\_func函数中加入自己的业务逻辑，再调用.run方法即可。

\# -\*- coding: utf-8 -\*-

\# @Time : 2021/2/4 14:36

\# @Author : CyrusMay WJ

\# @FileName: run.py

\# @Software: PyCharm

\# @Blog ：https://blog.csdn.net/Cyrus\_May

import queue

import threading

class CyrusThread(object):

def \_\_init\_\_(self,num\_thread = 10,logger=None):

"""

:param num\_thread: 线程数

:param logger: 日志对象

"""

self.num\_thread = num\_thread

self.logger = logger

def object\_func(self,args\_queue,max\_q):

while 1:

try:

arg = args\_queue.get\_nowait()

step = args\_queue.qsize()

self.logger.info("progress:\{\}\\\{\}".format(max\_q,step))

except:

self.logger.info("no more arg for args\_queue!")

break

"""

此处加入自己的业务逻辑代码

"""

def run(self,args):

args\_queue = queue.Queue()

for value in args:

args\_queue.put(value)

threads = \[\]

for i in range(self.num\_thread):

threads.append(threading.Thread(target=self.object\_func,args = args\_queue))

for t in threads:

t.start()

for t in threads:

t.join()

模型参数选择实例

\# -\*- coding: utf-8 -\*-

\# @Time : 2021/2/4 14:36

\# @Author : CyrusMay WJ

\# @FileName: run.py

\# @Software: PyCharm

\# @Blog ：https://blog.csdn.net/Cyrus\_May

import queue

import threading

import numpy as np

from sklearn.datasets import load\_boston

from sklearn.svm import SVR

import logging

import sys

class CyrusThread(object):

def \_\_init\_\_(self,num\_thread = 10,logger=None):

"""

:param num\_thread: 线程数

:param logger: 日志对象

"""

self.num\_thread = num\_thread

self.logger = logger

def object\_func(self,args\_queue,max\_q):

while 1:

try:

arg = args\_queue.get\_nowait()

step = args\_queue.qsize()

self.logger.info("progress:\{\}\\\{\}".format(max\_q,max\_q-step))

except:

self.logger.info("no more arg for args\_queue!")

break

\# 业务代码

C, epsilon, gamma = arg\[0\], arg\[1\], arg\[2\]

svr\_model = SVR(C=C, epsilon=epsilon, gamma=gamma)

x, y = load\_boston()\["data"\], load\_boston()\["target"\]

svr\_model.fit(x, y)

self.logger.info("score:\{\}".format(svr\_model.score(x,y)))

def run(self,args):

args\_queue = queue.Queue()

max\_q = 0

for value in args:

args\_queue.put(value)

max\_q += 1

threads = \[\]

for i in range(self.num\_thread):

threads.append(threading.Thread(target=self.object\_func,args = (args\_queue,max\_q)))

for t in threads:

t.start()

for t in threads:

t.join()

\# 创建日志对象

logger = logging.getLogger()

logger.setLevel(logging.INFO)

screen\_handler = logging.StreamHandler(sys.stdout)

screen\_handler.setLevel(logging.INFO)

formatter = logging.Formatter('%(asctime)s - %(module)s.%(funcName)s:%(lineno)d - %(levelname)s - %(message)s')

screen\_handler.setFormatter(formatter)

logger.addHandler(screen\_handler)

\# 创建需要调整参数的集合

args = \[\]

for C in \[i for i in np.arange(0.01,1,0.01)\]:

for epsilon in \[i for i in np.arange(0.001,1,0.01)\] + \[i for i in range(1,10,1)\]:

for gamma in \[i for i in np.arange(0.001,1,0.01)\] + \[i for i in range(1,10,1)\]:

args.append(\[C,epsilon,gamma\])

\# 创建多线程工具

threading\_tool = CyrusThread(num\_thread=20,logger=logger)

threading\_tool.run(args)

运行结果

2021-02-04 20:52:22,824 - run.object\_func:31 - INFO - progress:1176219\\1

2021-02-04 20:52:22,824 - run.object\_func:31 - INFO - progress:1176219\\2

2021-02-04 20:52:22,826 - run.object\_func:31 - INFO - progress:1176219\\3

2021-02-04 20:52:22,833 - run.object\_func:31 - INFO - progress:1176219\\4

2021-02-04 20:52:22,837 - run.object\_func:31 - INFO - progress:1176219\\5

2021-02-04 20:52:22,838 - run.object\_func:31 - INFO - progress:1176219\\6

2021-02-04 20:52:22,841 - run.object\_func:31 - INFO - progress:1176219\\7

2021-02-04 20:52:22,862 - run.object\_func:31 - INFO - progress:1176219\\8

2021-02-04 20:52:22,873 - run.object\_func:31 - INFO - progress:1176219\\9

2021-02-04 20:52:22,884 - run.object\_func:31 - INFO - progress:1176219\\10

2021-02-04 20:52:22,885 - run.object\_func:31 - INFO - progress:1176219\\11

2021-02-04 20:52:22,897 - run.object\_func:31 - INFO - progress:1176219\\12

2021-02-04 20:52:22,900 - run.object\_func:31 - INFO - progress:1176219\\13

2021-02-04 20:52:22,904 - run.object\_func:31 - INFO - progress:1176219\\14

2021-02-04 20:52:22,912 - run.object\_func:31 - INFO - progress:1176219\\15

2021-02-04 20:52:22,920 - run.object\_func:31 - INFO - progress:1176219\\16

2021-02-04 20:52:22,920 - run.object\_func:39 - INFO - score:-0.01674283914287855

2021-02-04 20:52:22,929 - run.object\_func:31 - INFO - progress:1176219\\17

2021-02-04 20:52:22,932 - run.object\_func:39 - INFO - score:-0.007992354170952565

2021-02-04 20:52:22,932 - run.object\_func:31 - INFO - progress:1176219\\18

2021-02-04 20:52:22,945 - run.object\_func:31 - INFO - progress:1176219\\19

2021-02-04 20:52:22,954 - run.object\_func:31 - INFO - progress:1176219\\20

2021-02-04 20:52:22,978 - run.object\_func:31 - INFO - progress:1176219\\21

2021-02-04 20:52:22,984 - run.object\_func:39 - INFO - score:-0.018769934807246536

2021-02-04 20:52:22,985 - run.object\_func:31 - INFO - progress:1176219\\22

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python threading库_python中threading和queue库实现多线程编程

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