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這篇文章主要講解了python 在threading中處理主進程和子線程關系的方法,內容清晰明了,對此有興趣的小伙伴可以學習一下,相信大家閱讀完之后會有幫助。
之前用python的多線程,總是處理不好進程和線程之間的關系。后來發現了join和setDaemon函數,才終于弄明白。下面總結一下。
1.使用join函數后,主進程會在調用join的地方等待子線程結束,然后才接著往下執行。
join使用實例如下:
import time import random import threading class worker(threading.Thread): def __init__(self): threading.Thread.__init__(self) def run(self): t = random.randint(1,10) time.sleep(t) print "This is " + self.getName() + ";I sleep %d second."%(t) tsk = [] for i in xrange(0,5): time.sleep(0.1) thread = worker() thread.start() tsk.append(thread) for tt in tsk: tt.join() print "This is the end of main thread."
運行結果如下:
# python testjoin.py This is Thread-3;I sleep 2 second. This is Thread-1;I sleep 4 second. This is Thread-2;I sleep 7 second. This is Thread-4;I sleep 7 second. This is Thread-5;I sleep 7 second. This is the end of main thread.
這里創建了5個子線程,每個線程隨機等待1-10秒后打印退出;主線程分別等待5個子線程結束。最后結果是先顯示各個子線程,再顯示主進程的結果。
2. 如果使用的setDaemon函數,則與join相反,主進程結束的時候不會等待子線程。
setDaemon函數使用實例:
import time import random import threading class worker(threading.Thread): def __init__(self): threading.Thread.__init__(self) def run(self): t = random.randint(1,10) time.sleep(t) print "This is " + self.getName() + ";I sleep %d second."%(t) tsk = [] for i in xrange(0,5): time.sleep(0.1) thread = worker() thread.setDaemon(True) thread.start() tsk.append(thread) print "This is the end of main thread."
這里設置主進程為守護進程,當主進程結束的時候,子線程被中止
運行結果如下:
#python testsetDaemon.py
This is the end of main thread.
3、如果沒有使用join和setDaemon函數,則主進程在創建子線程后,直接運行后面的代碼,主程序一直掛起,直到子線程結束才能結束。
import time import random import threading class worker(threading.Thread): def __init__(self): threading.Thread.__init__(self) def run(self): t = random.randint(1,10) time.sleep(t) print "This is " + self.getName() + ";I sleep %d second."%(t) tsk = [] for i in xrange(0,5): time.sleep(0.1) thread = worker() thread.start() tsk.append(thread) print "This is the end of main thread."
運行結果如下:
# python testthread.py This is the end of main thread. This is Thread-4;I sleep 1 second. This is Thread-3;I sleep 7 second. This is Thread-5;I sleep 7 second. This is Thread-1;I sleep 10 second. This is Thread-2;I sleep 10 second.
補充知識:Python Thread和Process對比
原因:進程和線程的差距(方向不同,之針對這個實例)
# coding=utf-8 import logging import multiprocessing import os import time from threading import Thread logging.basicConfig( level=logging.INFO, format="%(asctime)s 【 %(process)d 】 %(processName)s %(message)s" ) def func (i): # logging.info(f'子:{os.getpid()},\t{i}') return f'子:{os.getpid()},\t{i}' def main (ctx): start01 = time.time() ts = [Thread(target=func, args=(i,)) for i in range(100)] [t.start() for t in ts] [t.join() for t in ts] end01 = time.time() - start01 logging.info(f"線程花費的時間:{end01}秒") start02 = time.time() ps = [ctx.Process(target=func, args=(i,)) for i in range(100)] [p.start() for p in ps] [p.join() for p in ps] end02 = time.time() - start02 logging.info(f"進程花費的時間:{end02}秒") if __name__ == '__main__': # windows 啟動方式 multiprocessing.set_start_method('spawn') # 獲取上下文 ctx = multiprocessing.get_context('spawn') # 檢查這是否是凍結的可執行文件中的偽分支進程。 ctx.freeze_support() main(ctx)
輸出:
2019-10-06 14:17:22,729 【 7412 】 MainProcess 線程花費的時間:0.012967586517333984秒
2019-10-06 14:17:25,671 【 7412 】 MainProcess 進程花費的時間:2.9418249130249023秒
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