Python多進程VS多線程

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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 itertoolsfrom concurrent.futures import ProcessPoolExecutorresult = []# 回呼函數，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，進程並行不支援類方法、閉包等            函數參數和傳回值必須相容pickle序列化，進程間的通訊需要        """        future_result = pool.submit(calc, keep_stock_threshold,                                    buy_change_threshold)        # 當進程完成任務即calc運行結束後的回呼函數        future_result.add_done_callback(when_done)print(sorted(result)[::-1][:10])

 

# 多線程from concurrent.futures import ThreadPoolExecutorresult = []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