问题在于如何在Python中为这个类分配内存，而问题更多的是出于好奇而不是现实生活价值。
以下后处理类处理大量数据（numpy数组）。这是实际代码的简化版本，以使问题可读。基类的共享数据现在替换为characteristic_length变量。
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作为处理内存的python方式的陌生人，我很好奇是否将characteristic_length放在子类中会大大提高性能吗？
基于python文档，我认为派生类实例有一个指向定义基类的地址的指针。如果子类中的查找失败，则在基类中继续。这听起来像使用基类属性来存储派生类共享的数据是非常昂贵的。
在实际应用程序中，共享数据有点大numpy数组，但对所有派生类都是通用的。懒惰，我想避免分别读取每个子类的数据。有关如何有效解决这个问题的任何指示？
答案 0 :(得分：1)
最简单的解决方案是使numpy数组成为全局数组。如果您想阻止用户修改该数组，可以将writable flag设置为False。
或者你可以使它成为Reader类的class属性。