你试试这个 from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor import multiprocessing import os # I/O 密集型任务 def io_task(file_name): with open(file_name, 'r') as f: data = f.read() print(f"[{os.getpid()}] I/O task completed.") return data # CPU 密集型任务 def cpu_task(data): result = sum([i**2 for i in range(10**7)]) print(f"[{os.getpid()}] CPU task completed.") return result def main(): # 定义文件名 file_name = 'large_file.txt' # 使用线程池处理 I/O 密集型任务 with ThreadPoolExecutor(max_workers=2) as thread_pool: future_io = thread_pool.submit(io_task, file_name) # 等待 I/O 任务完成并获取结果 io_result = future_io.result() # 使用进程池处理 CPU 密集型任务 with ProcessPoolExecutor(max_workers=2) as process_pool: future_cpu = process_pool.submit(cpu_task, io_result) # 等待 CPU 任务完成 cpu_result = future_cpu.result() print("Final CPU result:", cpu_result) if __name__ == '__main__': main()
932837498@qq.co 发表于 2020-7-7 09:37 只有等下次了，今年受疫情影响减少出差次数 上海的出城都要报备,,,,,,,,,,,,
