I have also released a new tool called psleak, which detects memory leaks in C extension modules.

https://gmpy.dev/blog/2025/psutil-heap-introspection-apis

https://github.com/giampaolo/psleak/

I have done some work in this space as well such as how to write a Python C extension without leaks in the first place [0]. This also contains a section on memory leaks, using tools like your psutil [1] This also shows where the Python documentation for C extensions contains errors, omissions or is misleading. These errors can trap the unwary.

Also I developed a Python memory tracer, pymemtrace, that uses a variety of techniques (including using your psutil!) to track memory usage at different costs and levels of granularity [2].

Now psutil 7.2.0 is out I'll update both those projects.

Thanks again for all your hard work.

[0] Project: https://github.com/paulross/PythonExtensionPatterns Docs: https://pythonextensionpatterns.readthedocs.io/en/latest/ind...

[1] https://pythonextensionpatterns.readthedocs.io/en/latest/mem...

[2] Project: https://github.com/paulross/pymemtrace Docs: https://pymemtrace.readthedocs.io/

I really appreciate the support for Windows as that platform is currently underserved [3] when it comes to such memory tooling.

[0]: https://github.com/jcrist/msgspec

[1]: https://github.com/ofek/coincurve

[2]: https://github.com/DataDog/integrations-core

[3]: https://github.com/bloomberg/memray

For me, it reads as not having any soul to it, as well as changing who its target reader is throughout the post. The choice of emphasis comes across weirdly too.

I think this is a wonderful tool, but whether it’s because the author uses AI to help them write this post, or that there’s AI edited content everywhere now, I’m weary of reading and trusting something that reads like this post does.

I don’t know if this is overblown or meta-commentary on the state of online posts these days, but it’s how I’m feeling, more and more, when I see online writings.