importthread# 创建一个锁对象lock=thread.allocate_lock()defthread_safe_print(msg):# 请求锁lock.acquire()try:# 打印消息print(msg)finally:# 释放锁lock.release()# 创建多个线程并调用线程安全的打印函数thread.start_new_thread(thread_safe_print,("Thread 1",))thread.start_new_thread(thread_safe_pri...
sys.stdout = ThreadSafeFile(sys.stdout) # Create and start multiple threads thrs = [] for i in range(8): thrs.append(threading.Thread(target = targ)) print 'Starting' for t in thrs: t.start() for t in thrs: t.join() print 'Done' 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11...
threads = [Thread(target=safe_add), Thread(target=safe_sub)]fortinthreads: t.start()fortinthreads: t.join()print(f"最终:{a}") 使用Lock或RLock保护临界区,确保同一时刻只有一个线程访问共享资源。 4. 生产者-消费者模型 通过queue.Queue实现线程间安全的数据交换: fromqueueimportQueuefromthreadingimport...
Python库的开发者们接受了这个设定,即默认Python是thread-safe,所以开始大量依赖这个特性,无需在实现时考虑额外的内存锁和同步操作。但是GIL的设计有时会显得笨拙低效,但是此时由于内置库和第三方库已经对GIL形成了牢不可破的依赖,想改革GIL反而变得困难了(晕!)。所以目前的现状就是,Python的多线程在多核CPU上,只对...
import threading # 创建一个锁对象 print_lock = threading.Lock() def safe_print(*args, **kwargs): # 获取锁 with print_lock: # 在锁保护下执行 print 函数 print(*args, **kwargs) # 定义两个线程 def thread1(): for i in range(5): safe_print("Thread 1:", i) def thread2(): for...
print(f"Thread {threading.current_thread().name} released {connection}") # 创建一个最多允许3个并发连接的连接池 pool = ConnectionPool(3) threads = [] for i in range(10): t = threading.Thread(target=worker, args=(pool,), name=f"Thread-{i}") threads.append(t) t.start() for t ...
thread1.join()thread2.join()print('主线程结束') 在这个示例中,我们定义了两个函数print_numbers和print_letters,分别用于打印数字和字母。然后创建了两个线程thread1和thread2,并将这两个函数作为目标函数传递给线程。通过调用start方法启动线程,线程开始执行各自的目标函数。最后,使用join方法等待两个线程执行完毕...
下面是一个使用 thread 的例子: import thread from time import sleep, time def loop(num): print('start loop at:', time()) sleep(num) print('loop done at:', time()) def loop1(num): print('start loop 1 at:', time()) sleep(num) ...
producer(queue): queue.put('Product') def consumer(queue): print(queue.get()) q = Queue() producer_thread = Thread(target=producer, args=(q,)) consumer_thread = Thread(target=consumer, args=(q,)) producer_thread.start() consumer_thread.start() producer_thread.join() consumer_thread....
python.org/3/howto/logging-cookbook.html#:~:text=Although%20logging%20is%20thread%2Dsafe,...