一文分享Python进程间通信的3种正确方法

import multiprocessing as mp

CONFIG = {"date_format": "%Y-%m-%d", "max_len": 100}
results = []  # 用来收集所有子进程的结果

def process_line(line):
    # 用CONFIG里的配置处理数据
    cleaned = do_clean(line, CONFIG)
    results.append(cleaned)  # 试图把结果存到全局列表里
    return cleaned

if __name__ == "__main__":
    with mp.Pool(4) as pool:
        pool.map(process_line, data)
    print(len(results))  # 0！居然是0！

from multiprocessing import Process, Queue

def worker(q):
    # 从队列取数据，直到收到结束信号
    while True:
        item = q.get()
        if item is None:  # None作为“没有更多任务”的信号
            break
        result = item * 2
        q.put(result)  # 把处理结果放回队列

if __name__ == "__main__":
    q = Queue()
    
    # 启动工作进程
    p = Process(target=worker, args=(q,))
    p.start()
    
    # 主进程往队列里放任务
    for i in range(10):
        q.put(i)
    
    # 发送结束信号
    q.put(None)
    p.join()
    
    # 从队列里拿结果
    while not q.empty():
        print(q.get())

from multiprocessing import Process, Manager

def worker(shared_list, shared_dict, value):
    shared_list.append(value)
    shared_dict[value] = value * 2

if __name__ == "__main__":
    with Manager() as manager:
        # 创建共享的列表和字典
        shared_list = manager.list(["初始数据"])
        shared_dict = manager.dict()
        
        processes = []
        for i in range(5):
            p = Process(target=worker, args=(shared_list, shared_dict, i))
            processes.append(p)
            p.start()
        
        for p in processes:
            p.join()
        
        print(list(shared_list))  # ['初始数据', 0, 1, 2, 3, 4]
        print(dict(shared_dict))   # {0: 0, 1: 2, 2: 4, 3: 6, 4: 8}

from multiprocessing import shared_memory
import numpy as np

# 主进程：创建共享内存
shm = shared_memory.SharedMemory(create=True, size=1024)
# 用numpy访问这块内存
arr = np.ndarray((256,), dtype=np.int32, buffer=shm.buf)
arr[:] = np.arange(256)  # 存入数据

# 子进程可以拿到shm.name后连接到同一块内存
# shm_b = shared_memory.SharedMemory(name=shm.name)
# arr_b = np.ndarray((256,), dtype=np.int32, buffer=shm_b.buf)
# 读写arr_b就能直接修改arr的数据

# 清理
shm.close()
shm.unlink()  # 释放共享内存块

from multiprocessing.managers import SharedMemoryManager

with SharedMemoryManager() as smm:
    sl = smm.ShareableList(range(2000))
    # 多个进程可以共享sl
    # 退出with块时，所有共享内存自动释放