Describe the issue:

At my job, I was doing some memory analysis on our application in order to identify possible memory leaks.

To do this, I've used the package memray, which offers a lot of handy commands to identify memory leaks by generating a flame graphs that identifies memory chuncks allocated after tracking starts and not deallocated after tracking ends.

Reproduce the code example:

# test_numpy_leak.py
import numpy as np


def main():
    for _ in range(1_000_000):
        a = np.array([[1, 2], [3, 5]])
        b = np.array([1, 2])
        np.linalg.solve(a, b)


if __name__ == "__main__":
    main()

Error message:

In order to reproduce the analysis, use the following commands:

• PYTHONMALLOC=malloc python -m memray run --native test_numpy_leak.py
• python -m memray flamegraph --leaks memray-test_numpy_leak.py.XXXX.bin, where XXXX is the number of the file specified in its name.

After running these commands, it generates an HTML file, so you can open in your browser and see a flame graph, like the one above. I highlighted in red the section where memray reports a memory leak, if I hover it, it says that 4 allocations was made (32.0 MiB in total).

The line of code that is leaking memory is the following:

Python and NumPy Versions:

1.26.2
3.11.9 (main, Jul 19 2024, 18:26:46) [GCC 14.1.1 20240522]

Runtime Environment:

No response

Context for the issue:

Actually, I was just worried if this memory leak could scale and do more damage