P4p403n1x87·Nov 20, 2025Submission
2 points · Open discussionP403n1x87
austin
C2019–2025
P403n1x87 / austin
austin
Python frame stack sampler for CPython
10Distinct people
26Mentions
0Explicit recommenders
2.2KGitHub stars
What to know before exploring
What it is
Python frame stack sampler for CPython
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.
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Also in these discussions
- benfred/py-spy · linked in 2 of the same discussions
- bloomberg/memray · 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, 5:04:57 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 year26 dated mentions
Observed mentions: 2019-12-04 00:21:27 UTC to 2025-11-20 14:06:25 UTC.
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 |
|---|---|---|---|---|---|
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 10 | 3 | 7 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 6 | 2 | 4 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 3 | 1 | 2 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 2 | 1 | 1 |
What Hacker News says
26 sourcesI am delighted to announce the 4.0 release of Austin. If you haven't heard of Austin before, it is an open-source out-of-process frame stack sampler for CPython, distributed under the GPLv3 license. It can be used to obtain statistical profiling data for a running Python application with no manual instrumentation and virtually zero impact on the runtime. You can find the code at
https://github.com/P403n1x87/austin
The main highlights of the new release are the support for Python 3.14, as well as many substantial performance improvements that make Austin one of the most accurate sampling profilers for CPython. More details about what's new and bug-fixes can be found in the changelog at
https://github.com/P403n1x87/austin/blob/master/ChangeLog
Installing Austin is as easy as running
pip install austin-dist
on any supported combination of ar
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chitecture and platform. More installation options are available in the README file from the GitHub repository, along with usage details, as well as some examples of Austin in action. Details on how to contribute to Austin's development can be found at the bottom of the page.
As for ways of using Austin, the Austin VS Code extension provides a smooth interactive profiling experience, with interactive flame graphs straight into the text editor to allow you to quickly jump to the source code with a simple click. You can find the extension on the Visual Studio Marketplace and install it directly from VS Code:
https://marketplace.visualstudio.com/items?itemName=p403n1x8...
An Austin docker image, based on the latest Ubuntu image, is also available from Docker Hub:
https://hub.docker.com/r/p403n1x87/austin
Austin is a free and open-source project. A lot of effort goes into its development to ensure the best performance and that it stays up-to-date with the latest Python releases. If you find it useful, consider sponsoring this project on GitHub at https://github.com/sponsors/P403n1x87.
I'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 PythonAustin 3.7 – Python frame stack sampler for CPython
12 points · Open discussionI 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
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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.
This seems to be heavily based on Austin
https://github.com/P403n1x87/austin/blob/master/src/version....
https://github.com/bloomberg/pystack/blob/a971a4ced371a5859f...
In Pystack: Like Pstack but for PythonThis should work with anything https://github.com/P403n1x87/austin
In Memray: a memory profiler for PythonWhat are my Python processes at?
2 points · Open discussionThe official cheat sheet for Austin, the sampling Python profiler [pdf]
1 points · Open discussionJust wanted to add Austin: Python frame stack sampler for CPython written in pure C (https://github.com/P403n1x87/austin)
In Tqdm (Python)If you follow the call stack carefully you should be able to get to the point where sklearn calls ddot_kernel_8 (indirectly in this case). Austin(p) reports source files as well, so that shouldn't be a problem (provided all the debug symbols are available). If you're collecting data with austinp, don't forget to resolve symbol names with the resolve.py utility (https://github.com/P403n1x87/austin/blob/devel/utils/resolve..., see the README for more details: https://github.com/P403n1x87/austin/blob/devel/utils/resolve...)
In Spy on Python down to the Linux kernel levelSpy on the Python garbage collector with Austin 3.1
1 points · Open discussionMake sure you have Austin (https://github.com/P403n1x87/austin) installed.
See https://p403n1x87.github.io/how-to-bust-python-performance-i... for an example.
In Show HN: Austin VS Code – Interactive Python Profiling in VS CodeThis is a TUI for the profiler Austin, whose README has a bit more detail on what it can do:
https://github.com/P403n1x87/austin
In Show HN: Austin-Tui – Spy inside a running Python program at no performance costShowing the 15 most recent of 26 sources. Enable JavaScript to search and browse every indexed mention.