多線程python的實(shí)現(xiàn)及多線程有序性
前言
多線程一般用于同時(shí)調(diào)用多個(gè)函數(shù),cpu時(shí)間片輪流分配給多個(gè)任務(wù)。 優(yōu)點(diǎn)是提高cpu的使用率,使計(jì)算機(jī)減少處理多個(gè)任務(wù)的總時(shí)間;缺點(diǎn)是如果有全局變量,調(diào)用多個(gè)函數(shù)會(huì)使全局變量被多個(gè)函數(shù)修改,造成計(jì)算錯(cuò)誤,這使需要使用join方法或者設(shè)置局部變量來(lái)解決問(wèn)題。python使用threading模塊來(lái)實(shí)現(xiàn)多線程,threading.join()方法是保證調(diào)用join的子線程完成后,才會(huì)分配cpu給其他的子線程,從而保證線程運(yùn)行的有序性。
一、多線程運(yùn)行無(wú)序問(wèn)題
我們首先創(chuàng)建三個(gè)實(shí)例,t1,t2,t3 t1實(shí)例調(diào)用function1函數(shù),t2和t3函數(shù)調(diào)用function11函數(shù),他們都是對(duì)全局變量l1進(jìn)行操作
代碼如下:
import threading,time l1 = [] #創(chuàng)建RLock鎖,acquire幾次,release幾次 lock = threading.RLock() def function1(x,y): for i in range(x): l1.append(i) if i == 0: time.sleep(1) end_time = time.time() print("t{} is finished in {}s".format(y,end_time -time1 )) def function11(x,y): for i in range(x): l1.append(i) end_time = time.time() print("t{} is finished in {}s".format(y, end_time -time1)) #2.創(chuàng)建子線程:thread類 if __name__ == '__main__': t1 = threading.Thread(target= function1, args = (100,1)) t2 = threading.Thread(target= function11, args = (100,2)) t3 = threading.Thread(target= function11, args = (100,3)) time1 = time.time() print("time starts in {}".format(time1)) t1.start() t2.start() t3.start() print(l1)
結(jié)果如下:
runfile('E:/桌面/temp.py', wdir='E:/桌面')
time starts in 1656474963.9487
t2 is finished in 0.0s
t3 is finished in 0.0s
[0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
t1 is finished in 1.0152690410614014s
我們可以看到,全局變量中開(kāi)頭有兩個(gè)0,而不是按著0,1,2,3的方式按序填充,所以可以得知全局變量在多線程中是被多個(gè)函數(shù)無(wú)序調(diào)用的。為了保證多線程有序調(diào)用全局變量,我們可以利用threading.join()的方法。
二、“join方法”解決多線程運(yùn)行無(wú)序問(wèn)題
我們重寫了function1函數(shù),并命名為function2,t1調(diào)用function2函數(shù)。t2,t3不變。
代碼如下:
import threading,time l1 = [] #創(chuàng)建RLock鎖,acquire幾次,release幾次 lock = threading.RLock() def function1(x,y): for i in range(x): l1.append(i) if i == 0: time.sleep(1) end_time = time.time() print("t{} is finished in {}s".format(y,end_time -time1)) def function11(x,y): for i in range(x): l1.append(i) end_time = time.time() print("t{} is finished in {}s".format(y,end_time -time1)) def function2(x,y): for i in range(x): l1.append(i) if i == 0: time.sleep(1) end_time = time.time() print("t{} is finished in {}s".format(y,end_time -time1)) #2.創(chuàng)建子線程:thread類 if __name__ == '__main__': t1 = threading.Thread(target= function2, args = (100,1)) t2 = threading.Thread(target= function11, args = (100,2)) t3 = threading.Thread(target= function11, args = (100,3)) time1 = time.time() print("time starts in {}".format(time1)) t1.start() t1.join() t2.start() t3.start() print(l1)
結(jié)果如下:
runfile('E:/桌面/temp.py', wdir='E:/桌面')
time starts in 1656476057.441827
t1 is finished in 1.0155227184295654s
t2 is finished in 1.0155227184295654s
t3 is finished in 1.0155227184295654s
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]
由此可見(jiàn),threading.join()方法可以解決多線程無(wú)序問(wèn)題
三、threading.Thread()的常用參數(shù)
1.group:默認(rèn)值None,為了實(shí)現(xiàn)ThreadGroup類而保留
2.target:在start方法中調(diào)用的可調(diào)用對(duì)象,即需要開(kāi)啟線程的可調(diào)用對(duì)象,比如函數(shù)、方法
3.name:默認(rèn)為“Thread-N”,字符串形式的線程名稱
4.args:默認(rèn)為空元組,參數(shù)target中傳入的可調(diào)用對(duì)象的參數(shù)元組
5.kwargs:默認(rèn)為空字典{},參數(shù)target中傳入的可調(diào)用對(duì)象的關(guān)鍵字參數(shù)字典
6.daemon:默認(rèn)為None
總結(jié)
到此這篇關(guān)于多線程python的實(shí)現(xiàn)及多線程有序性的文章就介紹到這了,更多相關(guān)python多線程內(nèi)容請(qǐng)搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家!
相關(guān)文章
TensorFlow人工智能學(xué)習(xí)按索引取數(shù)據(jù)及維度變換詳解
這篇文章主要為大家介紹了TensorFlow人工智能學(xué)習(xí)按索引取數(shù)據(jù)及維度變換的示例詳解,有需要的朋友可以借鑒參考下,希望能夠有所幫助2021-11-11Python爬蟲(chóng)urllib和requests的區(qū)別詳解
這篇文章主要介紹了Python爬蟲(chóng)urllib和requests的區(qū)別詳解,本篇文章通過(guò)簡(jiǎn)要的案例,講解了該項(xiàng)技術(shù)的了解與使用,以下就是詳細(xì)內(nèi)容,需要的朋友可以參考下2021-09-09python實(shí)現(xiàn)ftp文件傳輸系統(tǒng)(案例分析)
最近做了一個(gè)簡(jiǎn)單的文件傳輸系統(tǒng),基于ftp協(xié)議,使用python語(yǔ)言開(kāi)發(fā),雖然python里面已經(jīng)有ftplib模塊,可以很容易的實(shí)現(xiàn)ftp服務(wù)器,這篇文章主要介紹了python實(shí)現(xiàn)ftp文件傳輸系統(tǒng)的案例分析,需要的朋友可以參考下2020-03-03Python機(jī)器學(xué)習(xí)之實(shí)現(xiàn)模糊照片人臉恢復(fù)清晰
GFPGAN是騰訊開(kāi)源的人臉修復(fù)算法,它利用預(yù)先訓(xùn)練好的面部?GAN(如?StyleGAN2)中封裝的豐富和多樣的先驗(yàn)因素進(jìn)行盲臉?(blind?face)修復(fù)。這篇文章主要為大家介紹通過(guò)GFPGAN實(shí)現(xiàn)模糊照片人臉恢復(fù)清晰,需要的朋友可以參考一下2021-12-12python數(shù)據(jù)類型相關(guān)知識(shí)擴(kuò)展
今天帶大家學(xué)習(xí)Python數(shù)據(jù)類型的擴(kuò)展知識(shí),文中有非常詳細(xì)的介紹介代碼示例,對(duì)正在學(xué)習(xí)python的小伙伴有很大的幫助,需要的朋友可以參考下2021-05-05Python中pandas模塊DataFrame創(chuàng)建方法示例
這篇文章主要介紹了Python中pandas模塊DataFrame創(chuàng)建方法,結(jié)合實(shí)例形式分析了DataFrame的功能,以及pandas模塊基于列表、字段與數(shù)組創(chuàng)建DataFrame的相關(guān)操作技巧,需要的朋友可以參考下2018-06-06Python flask與fastapi性能測(cè)試方法介紹
這篇文章主要介紹了Python flask與fastapi性能測(cè)試方法,文中通過(guò)示例代碼介紹的非常詳細(xì),對(duì)大家的學(xué)習(xí)或者工作具有一定的參考學(xué)習(xí)價(jià)值,需要的朋友們下面隨著小編來(lái)一起學(xué)習(xí)吧2022-12-12