为什么objgraph无法捕获np.array()的增长?

问题描述

查看代码:

import objgraph
import numpy as np
objgraph.show_growth()
j = 20
y = []
for i in range(5):
    for l in range(j):
        y.append(np.array([np.random.randint(500),np.random.randint(500)]))
    print 'i:',i
    objgraph.show_growth()
    print '___'
    #objgraph.show_most_common_types(limit=100)
    j += 1

结果是:

i: 1
wrapper_descriptor 1596 +3
weakref 625 +1
dict 870 +1
method_descriptor 824 +1
i: 2
i: 3
i: 4

对于2、3和4时代，它没有显示任何增长.但它应该表明numpy.array的数量在增加

For the 2,3 and 4 epoch, it shows nothing growing. But it should show that the number of numpy.array grows

推荐答案

我对objgraph不太熟悉，但是我认为同一问题也适用于其他Python堆分析工具，例如.

I'm not that familiar with objgraph specifically, but I think the same issue applies to other Python heap analysis tools such as heapy.

Numpy数组是用C实现的，它们在内部通过自己的引用计数调用Py_INCREF和Py_DECREF.因此，Python 垃圾收集器不会对其进行跟踪.像heapy和(大概)objgraph这样的工具使用Python垃圾收集器来跟踪对对象的引用，因此，numpy数组对它们不可见.

Numpy arrays are implemented in C, and do their own reference counting by internally calling Py_INCREF and Py_DECREF. As such, they are not tracked by the Python garbage collector. Tools like heapy and (presumably) objgraph use the Python garbage collector to track references to objects, so as a result numpy arrays are invisible to them.

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