Memray: The endgame Python memory profiler - Talk Python to Me Ep.425

Publié le: 01 janvier 1970
sur la chaîne: Talk Python

2,414

Understanding how your Python application is using memory can be tough. First, Python has it's own layer of reused memory (arenas, pools, and blocks) to help it be more efficient. And many important Python packages are built in natively compiled languages like C and Rust often times making that section of your memory opaque. But with Memray, you can way deeper insight into your memory usage. We have Pablo Galindo Salgado and Matt Wozniski back on the show to dive into Memray, the sister project to their pystack one we recently covered.

▬▬▬▬ About the podcast ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

This video is the uncut, live recording of the Talk Python To Me podcast ( https://talkpython.fm ). We cover Python-focused topics every week and publish the edited and polished version in audio form. Subscribe in your podcast player of choice (100% free) at https://talkpython.fm/subscribe.

▬▬▬▬ Guests ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

Pablo Galindo Salgado: / pyblogsal
Matt Wozniski: https://github.com/godlygeek

▬▬▬▬ Links and resources from the show ▬▬▬▬▬▬▬▬▬▬▬▬

pytest-memray: https://github.com/bloomberg/pytest-m...
PEP 669 – Low Impact Monitoring for CPython: https://peps.python.org/pep-0669/
Memray discussions: https://github.com/bloomberg/memray/d...
Mandlebrot Flamegraph example: https://bloomberg.github.io/memray/_s...
Python allocators: https://bloomberg.github.io/memray/py...
Profiling in Python: https://docs.python.org/3/library/pro...
PEP 693 – Python 3.12 Release Schedule: https://peps.python.org/pep-0693/

Listen this episode on Talk Python: https://talkpython.fm/episodes/show/4...
Episode transcripts: https://talkpython.fm/episodes/transc...

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