Python中有多线程的支持。Python的threading模块提供了多线程编程的基本工具。在下面,我将列举一些基础的多线程用法和一些高级用法,并提供相应的源代码,其中包含中文注释。
基础用法:
创建和启动线程
import threading import time # 定义一个简单的线程类 class MyThread(threading.Thread): def run(self): for _ in range(5): print(threading.current_thread().name, "is running") time.sleep(1) # 创建两个线程实例 thread1 = MyThread(name="Thread-1") thread2 = MyThread(name="Thread-2") # 启动线程 thread1.start() thread2.start() # 主线程等待所有子线程结束 thread1.join() thread2.join() print("Main thread exiting")
线程同步 - 使用锁
import threading # 共享资源 counter = 0 # 创建锁 counter_lock = threading.Lock() # 定义一个简单的线程类 class MyThread(threading.Thread): def run(self): global counter for _ in range(5): with counter_lock: # 使用锁保护临界区 counter += 1 print(threading.current_thread().name, "Counter:", counter) # 创建两个线程实例 thread1 = MyThread(name="Thread-1") thread2 = MyThread(name="Thread-2") # 启动线程 thread1.start() thread2.start() # 主线程等待所有子线程结束 thread1.join() thread2.join() print("Main thread exiting")
高级用法:
使用线程池
import concurrent.futures import time # 定义一个简单的任务函数 def task(name): print(f"{name} is running") time.sleep(2) return f"{name} is done" # 使用线程池 with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor: # 提交任务给线程池 future_to_name = {executor.submit(task, f"Thread-{i}"): f"Thread-{i}" for i in range(5)} # 获取任务结果 for future in concurrent.futures.as_completed(future_to_name): name = future_to_name[future] try: result = future.result() print(f"{name}: {result}") except Exception as e: print(f"{name}: {e}")
使用Condition进行线程间通信
import threading import time # 共享资源 shared_resource = None # 创建条件变量 condition = threading.Condition() # 定义一个写线程 class WriterThread(threading.Thread): def run(self): global shared_resource for _ in range(5): with condition: shared_resource = "Write data" print("Writer wrote:", shared_resource) condition.notify() # 通知等待的线程 condition.wait() # 等待其他线程通知 # 定义一个读线程 class ReaderThread(threading.Thread): def run(self): global shared_resource for _ in range(5): with condition: while shared_resource is None: condition.wait() # 等待写线程通知 print("Reader read:", shared_resource) shared_resource = None condition.notify() # 通知写线程 # 创建写线程和读线程 writer_thread = WriterThread() reader_thread = ReaderThread() # 启动线程 writer_thread.start() reader_thread.start() # 主线程等待所有子线程结束 writer_thread.join() reader_thread.join() print("Main thread exiting")
这些例子涵盖了一些基础和高级的多线程用法。请注意,在Python中由于全局解释器锁(GIL)的存在,多线程并不能充分利用多核处理器。如果需要充分利用多核处理器,可以考虑使用multiprocessing模块进行多进程编程。
原文地址:https://www.toutiao.com/article/7304442403006530087/