python中threading和queue庫實現多線程編程
摘要
本文主要介紹瞭利用python的 threading和queue庫實現多線程編程,並封裝為一個類,方便讀者嵌入自己的業務邏輯。最後以機器學習的一個超參數選擇為例進行演示。
多線程實現邏輯封裝
實例化該類後,在.object_func函數中加入自己的業務邏輯,再調用.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: 線程數 :param logger: 日志對象 """ 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 """ 此處加入自己的業務邏輯代碼 """ 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()
模型參數選擇實例
# -*- 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: 線程數 :param logger: 日志對象 """ 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 # 業務代碼 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() # 創建日志對象 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) # 創建需要調整參數的集合 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]) # 創建多線程工具 threading_tool = CyrusThread(num_thread=20,logger=logger) threading_tool.run(args)
運行結果
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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