Python进阶教程：多线程与多进程

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import threading
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import time
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# 方式一：直接传入函数
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def worker(name, seconds):
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    time.sleep(seconds)
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    print(f"{name} 完成")
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t1 = threading.Thread(target=worker, args=("任务1", 1))
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t1.start()
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t1.join()  # 等待线程结束
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# 方式二：继承 Thread 类
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class MyThread(threading.Thread):
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    def run(self):
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        for i in range(3):
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            time.sleep(0.5)
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            print(f"{self.name} 运行中：{i}")
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t2 = MyThread()
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t2.start()
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t2.join()

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import threading
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import time
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def download(name, delay):
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    time.sleep(delay)  # 模拟网络请求
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    print(f"{name} 下载完成，耗时{delay}s")
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tasks = [("文件A", 2), ("文件B", 1), ("文件C", 3)]
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threads = []
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start = time.time()
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for name, delay in tasks:
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    t = threading.Thread(target=download, args=(name, delay))
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    t.start()
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    threads.append(t)
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for t in threads:
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    t.join()
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print(f"总耗时：{time.time() - start:.1f}s")  # 约 3s 而非 6s

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import threading
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counter = 0
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lock = threading.Lock()
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def increment(n):
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    global counter
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    for _ in range(n):
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        with lock:  # 加锁保护临界区
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            counter += 1
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threads = [threading.Thread(target=increment, args=(100000,)) for _ in range(10)]
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for t in threads:
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    t.start()
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for t in threads:
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    t.join()
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print(counter)  # 正确结果 1000000

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from concurrent.futures import ThreadPoolExecutor
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import time
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def task(i):
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    time.sleep(0.5)
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    return i * i
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with ThreadPoolExecutor(max_workers=4) as pool:
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    # 提交单个任务
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    future = pool.submit(task, 5)
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    print(future.result())  # 25
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    # 批量提交
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    results = list(pool.map(task, range(6)))
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    print(results)  # [0, 1, 4, 9, 16, 25]

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from multiprocessing import Process
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import os
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def compute(name):
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    print(f"进程 {name}，PID={os.getpid()}")
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    total = sum(range(10**7))
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    print(f"{name} 计算结果：{total}")
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if __name__ == "__main__":
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    processes = [Process(target=compute, args=(f"P{i}",)) for i in range(4)]
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    for p in processes:
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        p.start()
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    for p in processes:
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        p.join()
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    print("所有进程执行完毕")

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from concurrent.futures import ProcessPoolExecutor
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def heavy_calc(x):
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    return sum(range(x))
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with ProcessPoolExecutor(max_workers=4) as pool:
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    results = list(pool.map(heavy_calc, [10**6] * 4))
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    print(results)

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from concurrent.futures import ThreadPoolExecutor
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import time
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import random
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def download_file(url):
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    """模拟下载文件"""
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    size = random.randint(1, 10)
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    time.sleep(size * 0.1)
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    return f"{url} 下载完成（{size}MB）"
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urls = [f"https://example.com/file{i}.zip" for i in range(10)]
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start = time.time()
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with ThreadPoolExecutor(max_workers=5) as pool:
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    results = list(pool.map(download_file, urls))
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for r in results:
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    print(r)
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print(f"全部下载完成，总耗时：{time.time() - start:.1f}s")