Python C扩展-内存泄漏

Question

I'm relatively new to Python and this is my first attempt at writing a C extension.

Background In my Python 3.X project I need to load and parse large binary files (10-100MB) to extract data for further processing. The binary content is organized in frames: headers followed by a variable amount of data. Due to the low performance in Python I decided to go for a C extension to speedup the loading part.

The standalone C code outperforms Python by a factor in between 20x-500x so I am pretty satisfied with it.

The problem: the memory keeps growing when I invoke the function from my C-extension multiple times within the same Python module.

---

my_c_ext.c

#include <Python.h>
#include <numpy/arrayobject.h>
#include "my_c_ext.h"

static unsigned short *X, *Y;

static PyObject* c_load(PyObject* self, PyObject* args)
{
    char *filename;
    if(!PyArg_ParseTuple(args, "s", &filename))
        return NULL;

    PyObject *PyX, *PyY;

    __load(filename); 

    npy_intp dims[1] = {n_events};

    PyX = PyArray_SimpleNewFromData(1, dims, NPY_UINT16, X);
    PyArray_ENABLEFLAGS((PyArrayObject*)PyX, NPY_ARRAY_OWNDATA);

    PyY = PyArray_SimpleNewFromData(1, dims, NPY_UINT16, Y);
    PyArray_ENABLEFLAGS((PyArrayObject*)PyY, NPY_ARRAY_OWNDATA);

    PyObject *xy = Py_BuildValue("NN", PyX, PyY);


    return xy;
}

...

//More Python C-extension boilerplate (methods, etc..)

...

void __load(char *) {

    // open file, extract frame header and compute new_size
    X = realloc(X, new_size * sizeof(*X));
    Y = realloc(Y, new_size * sizeof(*Y));

    X[i] = ...
    Y[i] = ...

    return;
}

---

test.py

import my_c_ext as ce

binary_files = ['file1.bin',...,'fileN.bin']

for f in binary_files:
    x,y = ce.c_load(f)
    del x,y

---

Here I am deleting the returned objects in hope of lowering memory usage.

After reading several posts (eg this , this and this ), I am still stuck.

I tried to add/remove the PyArray_ENABLEFLAGS setting the NPY_ARRAY_OWNDATA flag without experiencing any difference. It is not yet clear to me if the NPY_ARRAY_OWNDATA implies a free(X) in C. If I explicitly free the arrays in C, I ran into a segfault when trying to load second file in the for loop in test.py .

Any idea of what am I doing wrong?

Answer 1

This looks like a memory management disaster. NPY_ARRAY_OWNDATA should cause it to call free on the data (or at least PyArray_free which isn't necessarily the same thing...).

However once this is done you still have the global variables X and Y pointing to a now-invalid area of memory. You then call realloc on those invalid pointers. At this point you're well into undefined behaviour and so anything could happen.

---

If it's a global variable then the memory needs to be managed globally, not by Numpy. If the memory is managed by the Numpy array then you need to ensure that you store no other way to access it except through that Numpy array. Anything else is going to cause you problems.