TOtosh·Jun 30, 2026Submission
Memray: a Memory Profiler for Python
2 points · Open discussionbloomberg
memray
Python2022–2026
bloomberg / memray
memray
Memray is a memory profiler for Python
9Distinct people
9Mentions
0Explicit recommenders
15.4KGitHub stars
What to know before exploring
What it is
Memray is a memory profiler for Python
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
No classified warning is attached to this page. Read the discussions before treating silence as approval.
Also in these discussions
- p403n1x87/austin · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year9 dated mentions
Observed mentions: 2022-04-20 19:54:19 UTC to 2026-06-30 14:21:32 UTC.
* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 1 | 1 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 6 | 1 | 5 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2026 (partial) | 2026-01-01 00:00:00 UTC | 2027-01-01 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
9 sourcesThis is awesome, thanks a lot! I'm going to introduce this in the test suites of the extension modules I maintain [0][1] and, if all goes well, eventually at work [2].
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
In Detect memory leaks of C extensions with psutil and psleakFor profiling memory consider far more advanced memray.
https://github.com/bloomberg/memray
In Scalene: A high-performance, high-precision CPU, GPU, memory profiler for PythonI've used Scalene at various times in the past few years, and always liked using it when I want to dig deeper compared to cProfile/profile. You might also want to look at:
1] https://github.com/joerick/pyinstrument
2] https://github.com/benfred/py-spy
3] https://github.com/P403n1x87/austin
4] https://github.com/bloomberg/memray
5] https://github.com/pyutils/line_profiler
In Scalene: A high-performance, high-precision CPU, GPU, memory profiler for PythonTracing code is a way to see what's happening in your code which Go provides:
https://www.infoq.com/articles/debugging-go-programs-pprof-t...
Many other language use the same technique, see Python with: https://github.com/bloomberg/memray
In More powerful Go execution tracesI collected a list of profilers (also memory profilers, also specifically for Python) here: https://github.com/albertz/wiki/blob/master/profiling.md
Currently I actually need a Python memory profiler, because I want to figure out whether there is some memory leak in my application (PyTorch based training script), and where exactly (in this case, it's not a problem of GPU memory, but CPU memory).
I tried Scalene (https://github.com/plasma-umass/scalene), which seems to be powerful, but somehow the output it gives me is not useful at all? It doesn't really give me a flamegraph, or a list of the top lines with memory allocations, but instead it gives me a listing of all source code lines, and prints some (very sparse) information on each line. So I need to search through that listing now by hand to find the spots? Maybe I just don't know how
Read the rest
to use it properly.
I tried Memray, but first ran into an issue (https://github.com/bloomberg/memray/issues/212), but after using some workaround, it worked now. I get a flamegraph out, but it doesn't really seem accurate? After a while, there don't seem to be any new memory allocations at all anymore, and I don't quite trust that this is correct.
There is also Austin (https://github.com/P403n1x87/austin), which I also wanted to try (have not yet).
Somehow this experience so far was very disappointing.
Side node, I debugged some very strange memory allocation behavior of Python before, where all local variables were kept around after an exception, even though I made sure there is no reference anymore to the exception object, to the traceback, etc, and I even called frame.clear() for all frames to really clear it. It turns out, frame.f_locals will create another copy of all the local variables, and the exception object and all the locals in the other frame still stay alive until you access frame.f_locals again. At that point, it will sync the f_locals again with the real (fast) locals, and then it can finally free everything. It was quite annoying to find the source of this problem and to find workarounds for it. https://github.com/python/cpython/issues/113939
Another side node: Bloomberg has a couple of nice open source projects. E.g. I just realized, PyStack (https://bloomberg.github.io/pystack/) is also by Bloomberg.
The real testimonials are here: https://github.com/bloomberg/memray/discussions/226
In Memray – A Memory Profiler for PythonMemray – A Memory Profiler for Python
120 points · Open discussionMemray: a memory profiler for Python
495 points · Open discussion