stackcollapse-ghc VS py-spy

stackcollapse-ghc

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py-spy

• Minha jornada de otimização de uma aplicação django
  5 projects | dev.to | 13 Mar 2024
• Graphical Python Profiler
  4 projects | news.ycombinator.com | 5 Jul 2023
• Grasshopper – An Open Source Python Library for Load Testing
  3 projects | news.ycombinator.com | 1 May 2023

  For CPU cycles, py-spy[0] is getting more and more used. For RAM, I would like to known too...

  [0] -- https://github.com/benfred/py-spy

• Debugging a Mixed Python and C Language Stack
  4 projects | news.ycombinator.com | 25 Apr 2023

  Theres also Py Spy, a profiling tool that can generate flame charts containing a mix of python and C (or C++) calls.

  https://github.com/benfred/py-spy

  It's worked really well for my needs

• python to rust migration
  5 projects | /r/rust | 23 Apr 2023

  You should profile your consumer to check the bottlenecks. You can use the excellent py-spy(written in Rust). IMO a few usage of Numba there and there should solve your performance issues.

• Has anyone switched from numpy to Rust?
  1 project | /r/rust | 11 Mar 2023

  So as a first step you'll want to profile your program to figure out where it's slow, and hopefully that'll also tell you why it's slow. I'm the (biased) author of the Sciagraph profiler which is designed for this sort of application (https://sciagraph.com) but you can also try py-spy, which isn't as well designed for data processing/analysis applications (e.g. it won't visualize parallelism at all) but can still be informative (https://github.com/benfred/py-spy). Both are written in Rust ;)

• Trace your Python process line by line with minimal overhead!
  3 projects | news.ycombinator.com | 15 Jan 2023

  Any advantages/disadvantages compared to py-spy [1]?

  [1]: https://github.com/benfred/py-spy

• Python 3.11 delivers.
  4 projects | /r/programming | 15 Dec 2022

  Python profiling is enabled primarily through cprofile, and can be visualized with help of tools like snakeviz (output flame graph can look like this). There are also memory profilers like memray which does in-depth traces, or sampling profilers like py-spy.

• Tales of serving ML models with low-latency
  1 project | /r/mlops | 4 Dec 2022

  A good profiler would be https://github.com/benfred/py-spy . If you run your app/benchmark with it, it should be able to draw a flamegraph telling you where the majority of time is spent. The info here is quite fine grained so it would already tell you where the bottleneck is. Without a full-fledged profiler you can also measure the timings in various parts of the code to understand where the bottleneck is.

• Profiling a Python library written in Rust (Maturin)
  2 projects | /r/learnrust | 25 Oct 2022

  Might be worth raising an issue on py-spy (a python profiler written in rust which "supports profiling native python extensions written in languages like C/C++ or Cython" to see if that can close the loop.