python中threading和queue库实现多线程编程

这篇文章主要介绍了python中threading和queue库实现多线程编程,文中通过示例代码介绍的非常详细,对大家的学习或者工作具有一定的参考学习价值,需要的朋友们下面随着小编来一起学习学习吧

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

到此这篇关于python中threading和queue库实现多线程编程的文章就介绍到这了,更多相关python 多线程编程内容请搜索html中文网以前的文章或继续浏览下面的相关文章希望大家以后多多支持html中文网!

以上就是python中threading和queue库实现多线程编程的详细内容,更多请关注0133技术站其它相关文章!

赞(0) 打赏
未经允许不得转载:0133技术站首页 » python