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前言

多线程一般用于同时调用多个函数，cpu时间片轮流分配给多个任务。 优点是提高cpu的使用率，使计算机减少处理多个任务的总时间；缺点是如果有全局变量，调用多个函数会使全局变量被多个函数修改，造成计算错误，这使需要使用join方法或者设置局部变量来解决问题。python使用threading模块来实现多线程，threading.join()方法是保证调用join的子线程完成后，才会分配cpu给其他的子线程，从而保证线程运行的有序性。

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一、多线程运行无序问题

我们首先创建三个实例，t1,t2,t3 t1实例调用function1函数，t2和t3函数调用function11函数，他们都是对全局变量l1进行操作
代码如下，

import threading,time

l1 = []
#创建RLock锁，acquire几次，release几次
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.创建子线程：thread类
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)
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结果如下，

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
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我们可以看到，全局变量中开头有两个0，而不是按着0，1，2，3的方式按序填充，所以可以得知全局变量在多线程中是被多个函数无序调用的。为了保证多线程有序调用全局变量，我们可以利用threading.join()的方法。

二、“join方法”解决多线程运行无序问题

我们重写了function1函数，并命名为function2，t1调用function2函数。t2,t3不变。
代码如下，

import threading,time

l1 = []
#创建RLock锁，acquire几次，release几次
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.创建子线程：thread类
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)
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结果如下，

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]
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由此可见，threading.join()方法可以解决多线程无序问题

三、threading.Thread()的常用参数

1.group：默认值None，为了实现ThreadGroup类而保留
2.target：在start方法中调用的可调用对象，即需要开启线程的可调用对象，比如函数、方法
3.name：默认为“Thread-N”，字符串形式的线程名称
4.args：默认为空元组，参数target中传入的可调用对象的参数元组
5.kwargs：默认为空字典{}，参数target中传入的可调用对象的关键字参数字典
6.daemon：默认为None

总结

以上就是python多线程常用参数和多线程有序性的介绍，后续还有更深入的多线程文章请持续关注。