python中threading和queue库实现多线程编程

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_Mayimport queueimport threadingclass 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_Mayimport queueimport threadingimport numpy as npfrom sklearn.datasets import load_bostonfrom sklearn.svm import SVRimport loggingimport sysclass 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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