多線程：適用於處理I/O密集型任務和並發執行的阻塞操作
多進程：適用於處理計算密集型任務

# 多進程
import itertools
from concurrent.futures import ProcessPoolExecutor
result = []

# 回調函數，通過add_done_callback任務完成後調用
def when_done(r):
    # when_done在主進程中運行
    result.append(r.result())

"""
    with class_a() as a: 上下文管理器
"""
with ProcessPoolExecutor() as pool:
    
 
for keep_stock_threshold, buy_change_threshold in             itertools.product(keep_stock_list, buy_change_list):

        """
            submit提交任務：使用calc函數和的參數通過submit提交到獨立進程
            提交的任務必須是簡單函數，進程並行不支持類方法、閉包等
            函數參數和返回值必須兼容pickle序列化，進程間的通信需要
        """
        future_result 
 
= pool.submit(calc, keep_stock_threshold,
                                    buy_change_threshold)
        # 當進程完成任務即calc運行結束後的回調函數
        future_result.add_done_callback(when_done)
print(sorted(result)[::-1][:10])

# 多線程
from concurrent.futures import ThreadPoolExecutor

result = []
 
def when_done(r):
    result.append(r.result())

with ThreadPoolExecutor(max_workers=8) as pool:
    for keep_stock_threshold, buy_change_threshold in             itertools.product(keep_stock_list, buy_change_list):
        future_result = pool.submit(calc, keep_stock_threshold,
                                    buy_change_threshold)
        future_result.add_done_callback(when_done)

Python多進程VS多線程