Python 多线程(小试牛刀)

摘要

查阅了一下资料后，发现想要在Python通过多线程来加快任务执行不太靠谱，还是使用多进程比较好，参考以下教程：

http://python.jobbole.com/82045/

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使用到了join, lock, queue等基础的功能
关于GIL，业务复杂型可用MT，数据复杂型还是用MultiProcessing

import threading
import time
from queue import Queue

def thread_job():
    print("T1 start\n")
    for i in range(10):
        time.sleep(0.1)
    print("T1 finished\n")

def thread_job2():
    print("T2 start\n")
    print("T2 finished\n")

# Queue
def job(l,q):
    for i in range(len(l)):
        l[i] = l[i]**2
    q.put(l) # 不能return！

def thread_job3():
    q = Queue()
    threads = []
    data = [[1,2,3],[3,4,5],[4,4,4],[5,5,5]]
    for i in range(4):
        t = threading.Thread(target=job, args=(data[i],q))
        t.start()
        threads.append(t)
    for thread in threads:
        thread.join()
    results = []
    for _ in range(4):
        results.append(q.get())
    print(results)

# Lock
def job1():
    global A, lock
    lock.acquire()
    for i in range(10):
        A+=1
        print("job1: ",A)
    lock.release()

def job2():
    global A, lock
    lock.acquire()
    for i in range(10):
        A+=10
        print("job2: ", A)
    lock.release()

def main_lock():
    thread1 = threading.Thread(target=job1, name='T1')
    thread2 = threading.Thread(target=job2, name='T2')
    thread1.start()
    thread2.start()
    thread1.join()
    thread2.join()

def main():
    thread1 = threading.Thread(target=thread_job, name='T1')
    thread2 = threading.Thread(target=thread_job2, name='T2')
    thread1.start()
    thread1.join()
    thread2.start()
    thread2.join()
    print('all done\n')
    # print("Current Activate Threading: ", threading.active_count())
    # print(threading.enumerate())
    # print(threading.current_thread())

if __name__ == '__main__':
    lock = threading.Lock()
    A = 0
    main_lock()