117笔记问答在Python多进程编程中，实现资源共享需要使用multiprocessing模块中的Value、Array和Manager等类。这些类允许你在多个进程之间共享数据。下面是一些示例：
- 使用
Value实现共享整数：
import multiprocessing
def worker(shared_value):
shared_value.value += 1
if __name__ == "__main__":
shared_value = https://www.yisu.com/ask/multiprocessing.Value("i", 0)
processes = [multiprocessing.Process(target=worker, args=(shared_value,)) for _ in range(10)]
for process in processes:
process.start()
for process in processes:
process.join()
print("Shared value:", shared_value.value)
- 使用
Array实现共享列表：
import multiprocessing
def worker(shared_array):
for i in range(len(shared_array)):
shared_array[i] += 1
if __name__ == "__main__":
shared_array = multiprocessing.Array("i", [0] * 10)
processes = [multiprocessing.Process(target=worker, args=(shared_array,)) for _ in range(10)]
for process in processes:
process.start()
for process in processes:
process.join()
print("Shared array:", shared_array[:])
- 使用
Manager实现共享复杂数据结构：
import multiprocessing
def worker(shared_dict):
shared_dict["key"] += 1
if __name__ == "__main__":
shared_dict = multiprocessing.Manager().dict({"key": 0})
processes = [multiprocessing.Process(target=worker, args=(shared_dict,)) for _ in range(10)]
for process in processes:
process.start()
for process in processes:
process.join()
print("Shared dictionary:", shared_dict)
注意：在使用multiprocessing模块时，需要确保代码在if __name__ == "__main__":条件下运行，以避免在Windows操作系统上出现递归创建子进程的问题。