多线程执行结果不一致

在使用多线程技术时，有时会遇到这样的问题：代码明明是照着教程写的，但每次运行的结果都不同。这可能是因为多线程的执行顺序是无法预知的，它取决于底层操作系统的调度策略、系统负载等因素。

例如，以下代码使用三个线程来处理一个队列中的数据：

import Queue
import threading
import time

exitFlag = 0

class myThread (threading.Thread):
    def __init__(self, threadID, name, q):
        threading.Thread.__init__(self)
        self.threadID = threadID
        self.name = name
        self.q = q
    def run(self):
        print "Starting " + self.name
        process_data(self.name, self.q)
        print "Exiting " + self.name

def process_data(threadName, q):
    while not exitFlag:
        queueLock.acquire()
        if not workQueue.empty():
            data = q.get()
            queueLock.release()
            print "%s processing %s" % (threadName, data)
        else:
            queueLock.release()
        time.sleep(1)

threadList = ["Thread-1", "Thread-2", "Thread-3"]
nameList = ["One", "Two", "Three", "Four", "Five"]
queueLock = threading.Lock()
workQueue = Queue.Queue(10)
threads = []
threadID = 1

# Create new threads
for tName in threadList:
    thread = myThread(threadID, tName, workQueue)
    thread.start()
    threads.append(thread)
    threadID += 1

# Fill the queue
queueLock.acquire()
for word in nameList:
    workQueue.put(word)
queueLock.release()

# Wait for queue to empty
while not workQueue.empty():
    pass

# Notify threads it's time to exit
exitFlag = 1

# Wait for all threads to complete
for t in threads:
    t.join()
print "Exiting Main Thread"

运行这段代码，可能会出现以下几种不同的执行顺序：

Starting Thread-1
Starting Thread-2
Starting Thread-3
Thread-3 processing One
Thread-2 processing Two
Thread-1 processing Three
Thread-3 processing Four
Thread-2 processing Five
Exiting Thread-1
Exiting Thread-3
Exiting Thread-2
Exiting Main Thread

Starting Thread-1
Starting Thread-2
Starting Thread-3
Thread-3 processing One
Thread-2 processing Two
Thread-1 processing Three
Thread-3 processing Four
Thread-3 processing Five
Exiting Thread-1
Exiting Thread-2
Exiting Thread-3
Exiting Main Thread

Starting Thread-1
Starting Thread-2
Starting Thread-3
Thread-1 processing One
Thread-2 processing Two
Thread-3 processing Three
Thread-1 processing Four
Thread-2 processing Five
Exiting Thread-3
Exiting Thread-1
Exiting Thread-2
Exiting Main Thread

2. 解决方案

如果需要控制多线程的执行顺序，可以采用以下几种方法：

1. 使用锁（lock）来控制对共享资源的访问。

2. 使用信号量（semaphore）来控制资源的使用数量。

3. 使用事件（event）来通知其他线程某件事已经发生。

4. 使用条件变量（condition variable）来等待某个条件满足。

5. 使用队列（queue）来协调线程之间的通信。

以下是一些代码示例：

# 使用锁来控制对共享资源的访问
import threading
lock = threading.Lock()

def worker(n):
    lock.acquire()
    print(f"Worker {n} is working")
    lock.release()

threads = [threading.Thread(target=worker, args=(i,)) for i in range(5)]
for t in threads:
    t.start()

# 使用信号量来控制资源的使用数量
import threading
semaphore = threading.Semaphore(2)

def worker(n):
    semaphore.acquire()
    print(f"Worker {n} is working")
    time.sleep(1)
    semaphore.release()

threads = [threading.Thread(target=worker, args=(i,)) for i in range(5)]
for t in threads:
    t.start()

# 使用事件来通知其他线程某件事已经发生
import threading
event = threading.Event()

def worker(n):
    event.wait()
    print(f"Worker {n} is working")

threads = [threading.Thread(target=worker, args=(i,)) for i in range(5)]
for t in threads:
    t.start()

event.set()

# 使用条件变量来等待某个条件满足
import threading
condition = threading.Condition()

def worker(n):
    condition.acquire()
    condition.wait_for(lambda: condition_is_met)
    print(f"Worker {n} is working")
    condition.release()

threads = [threading.Thread(target=worker, args=(i,)) for i in range(5)]
for t in threads:
    t.start()

condition.acquire()
condition_is_met = True
condition.notify_all()
condition.release()

# 使用队列来协调线程之间的通信
import threading
queue = Queue()

def producer():
    for i in range(5):
        queue.put(i)

def consumer():
    while True:
        item = queue.get()
        print(f"Consumer got item {item}")

producer_thread = threading.Thread(target=producer)
consumer_thread = threading.Thread(target=consumer)

producer_thread.start()
consumer_thread.start()

producer_thread.join()
queue.join()
consumer_thread.join()

通过使用这些方法，可以控制多线程的执行顺序，并确保它们按照期望的顺序执行。