在Python中进行并行计算求和可以通过使用多进程或多线程来实现。以下是使用多进程和多线程的示例代码:
使用多进程:import multiprocessingdef sum_worker(data_chunk, result_queue): result = sum(data_chunk) result_queue.put(result)data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]chunk_size = len(data) // 4result_queue = multiprocessing.Queue()processes = []for i in range(4): start = i * chunk_size end = start + chunk_size p = multiprocessing.Process(target=sum_worker, args=(data[start:end], result_queue)) processes.append(p) p.start()for p in processes: p.join()total_sum = 0while not result_queue.empty(): total_sum += result_queue.get()print(total_sum)使用多线程:import threadingdef sum_worker(data_chunk, result_list): result = sum(data_chunk) result_list.append(result)data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]chunk_size = len(data) // 4result_list = []threads = []for i in range(4): start = i * chunk_size end = start + chunk_size t = threading.Thread(target=sum_worker, args=(data[start:end], result_list)) threads.append(t) t.start()for t in threads: t.join()total_sum = sum(result_list)print(total_sum)这些代码示例中,将数据分成4个部分,然后分别使用多进程和多线程来计算每个部分的和,最后将结果汇总得到总和。在实际应用中,可以根据需要调整数据分割的方式和线程/进程数量来实现更高效的并行计算。




