正文

2 添加线程 add thread

import threading

显示线程的状态

threading.active_count()  # 显示有多少个已经激活的线程

threading.enumerate()  # 显示已经激活的现场具体情况

[<_MainThread(MainThread, started 5844)>,
 <Thread(IOPub, started daemon 7116)>,
 <Heartbeat(Heartbeat, started daemon 9816)>,
 <ControlThread(Control, started daemon 4020)>,
 <HistorySavingThread(IPythonHistorySavingThread, started 4124)>,
 <ParentPollerWindows(Thread-4, started daemon 10940)>]

threading.current_thread()  # 显示正在运行的线程

<_MainThread(MainThread, started 5844)>

添加一个线程

def thread_job():
    print("Thid is an added Thread, number is %s" % threading.current_thread())

def main():
    added_thread = threading.Thread(target=thread_job)  # 添加一个线程: 目标thread_job
    added_thread.start()  # 运行这个线程

if __name__ == "__main__":
    main()

Thid is an added Thread, number is <Thread(Thread-8, started 7464)>

3 join 功能

import threading
import time

def thread_job():
    print("T1 start\n")
    for i in range(10):
        time.sleep(0.1)  # 每步暂停0.1秒
    print("T1 finish\n")
    
def T2_job():
    print('T2 start\n')
    print('T2 finish')
    

def main():
    added_thread = threading.Thread(target=thread_job, name='T1')
    thread2 = threading.Thread(target=T2_job, name='T2')
    
    added_thread.start()
    thread2.start()
    
    added_thread.join()  # 加入到主线程
    thread2.join()
    
    print('all done\n')
    
if __name__ == "__main__":
    main()

T1 start
T2 start

T2 finish

T1 finish

all done

当加入到主线程后，主线程中所有线程执行完毕后才会打印'all done\n'

4 Quene 功能

处理多线程中target函数没有返回值的情况

import threading
import time
from queue import Queue


def job(l, q):
    for i in range(len(l)):
        l[i] **= 2
    q.put(l)  # 将计算后的列表放到q中

    
def multithreading():
    q = Queue()
    threads = []
    data = [[1, 2, 3], [3, 4, 5], [4, 4, 4], [5, 5, 5]]
    for i in range(4):  # 创建4个线程
        t = threading.Thread(target=job, args=(data[i], q))  # args给target函数传递参数
        t.start()
        threads.append(t)
    for thread in threads:
        thread.join()
    results = []
    for _ in range(4):
        results.append(q.get())  # 从队列中拿出数据, 加入到results列表中
    print(results)

    
if __name__ == '__main__':
    multithreading()

[[1, 4, 9], [9, 16, 25], [16, 16, 16], [25, 25, 25]]

5 不一定有效率 GIL

在处理较简单的问题时, 由于切换线程需要耗费时间(GIL), 多线程不一定比单线程用时更短(每个时刻只能有一个线程在CPU工作)
为什么多线程有时候会比单线程耗时更短? 因为有些时候会边运算边读写数据. 解决方法: 多核运算
分别用常规方法和多线程方法计算0-99999求和的四倍
Python GIL全局解释器锁详解（深度剖析）

import threading
from queue import Queue
import copy
import time


def job(l, q):
    res = sum(l)
    q.put(res)


def multithreading(l):  # 多线程方法
    q = Queue()
    threads = []
    for i in range(4):
        t = threading.Thread(target=job, args=(copy.copy(l), q), name='T%i' % i)
        t.start()
        threads.append(t)
    [t.join() for t in threads]
    total = 0
    for _ in range(4):
        total += q.get()
    print(total)


def normal(l):  # 常规方法
    total = sum(l)  # 对序列求和
    print(total)


if __name__ == '__main__':
    l = list(range(1000_000))

    s_t = time.time()
    normal(l * 4)
    print('normal:', time.time() - s_t)

    s_t = time.time()
    multithreading(l)
    print('multithreading:', time.time() - s_t)

1999998000000
normal: 0.1690812110900879
1999998000000
multithreading: 0.24041318893432617

6 锁 lock

一般只有在共享内存时才会用得到, 防止不同次运行程序时出现不同的情况

未添加锁的情况

import threading


def job1():
    global A  # A 是一个全局变量
    for i in range(10):
        A += 1
        print('job1', A)
    
    
def job2():
    global A  # A 是一个全局变量
    for i in range(10):
        A += 10
        print('job2', A)
    
    
if __name__ == '__main__':
    A = 0
    t1 = threading.Thread(target=job1)
    t2 = threading.Thread(target=job2)
    t1.start()
    t2.start()
    t1.join()
    t2.join()

job1job2 11
job2 21
job2 31
job2 41
job2 51 
job2 61
job2 71
job2 81
job2 91
job2 101
1
job1 102
job1 103
job1 104
job1 105
job1 106
job1 107
job1 108
job1 109
job1 110

上了锁的情况

只有job1运行完才会运行job2

import threading


def job1():
    global A, lock  # 定义锁
    lock.acquire()  # 上锁
    for i in range(10):
        A += 1
        print('job1', A)
    lock.release()  # 解锁
    
    
def job2():
    global A, lock  # A 是一个全局变量
    lock.acquire()  # 上锁
    for i in range(10):
        A += 10
        print('job2', A)
    lock.release()  # 解锁
    
    
if __name__ == '__main__':
    lock = threading.Lock()
    A = 0
    t1 = threading.Thread(target=job1)
    t2 = threading.Thread(target=job2)
    t1.start()
    t2.start()
    t1.join()
    t2.join()

job1 1
job1 2
job1 3
job1 4
job1 5
job1 6
job1 7
job1 8
job1 9
job1 10
job2 20
job2 30
job2 40
job2 50
job2 60
job2 70
job2 80
job2 90
job2 100
job2 110