gdbghidra
py-spy
gdbghidra | py-spy | |
---|---|---|
2 | 25 | |
296 | 11,913 | |
0.7% | - | |
10.0 | 6.4 | |
over 4 years ago | 14 days ago | |
Java | Rust | |
MIT License | MIT License |
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gdbghidra
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Debugging a Mixed Python and C Language Stack
#284
> "Users can do [mixed mode] debugging with GDB (and/or other debuggers) and log the session in a notebook; in particular in order to teach.*
Your question is specifically about IDEs with support for mixed-mode debugging (with gdb), so I went looking for an answer:
https://wiki.python.org/moin/DebuggingWithGdb (which is not responsive and almost unreadable on a mobile device) links to https://fedoraproject.org/wiki/Features/EasierPythonDebuggin... , which mentions the py-list, py-up and py-down, py-bt, py-print, and py-locals GDB commands that are also described in * https://devguide.python.org/gdb/ **
> https://wiki.python.org/moin/PythonDebuggingTools Ctrl-F "gdb" mentions: DDD, pyclewn (vim), trepan3k (which is gdb-like and supports breaking at c-line and also handles bytecode disassembly)
> Apparently, GHIDRA does not have a debugger but there is a plugin for following along with gdb in ghidra called https://github.com/Comsecuris/gdbghidra [...] * https://github.com/Comsecuris/gdbghidra/blob/master/data/gdb... (zero dependencies)*
> https://reverseengineering.stackexchange.com/questions/1392/... lists a number of GUIs for GDB; including voltronnn:
>> There's Voltron, which is an extensible Python debugger UI that supports LLDB, GDB, VDB, and WinDbg/CDB (via PyKD) and runs on macOS, Linux and Windows. For the first three it supports x86, x86_64, and arm with even arm64 support for lldb while adding even powerpc support for gdb.
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Possibly a dumb question, but is it possible to install a plugin made for an older version of Ghidra on a newer version?
I'm new to Ghidra and I'm trying to get the gdbghidra plugin on the last version, but when I go to File>Install Extension, I can't tick the left box as the name is highlighted in red due to it being made for 9.0.1
py-spy
- Minha jornada de otimização de uma aplicação django
- Graphical Python Profiler
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Grasshopper – An Open Source Python Library for Load Testing
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
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Debugging a Mixed Python and C Language Stack
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
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python to rust migration
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.
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Has anyone switched from numpy to Rust?
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 ;)
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Trace your Python process line by line with minimal overhead!
Any advantages/disadvantages compared to py-spy [1]?
[1]: https://github.com/benfred/py-spy
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Python 3.11 delivers.
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.
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Tales of serving ML models with low-latency
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.
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Profiling a Python library written in Rust (Maturin)
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.
What are some alternatives?
debugger - A visual debugger for Jupyter notebooks, consoles, and source files
pyflame
voltron - A hacky debugger UI for hackers
pyinstrument - 🚴 Call stack profiler for Python. Shows you why your code is slow!
python-uncompyle6 - A cross-version Python bytecode decompiler
memory_profiler - Monitor Memory usage of Python code
icecream - 🍦 Never use print() to debug again.
line_profiler
profiling
filprofiler - A Python memory profiler for data processing and scientific computing applications
yappi - Yet Another Python Profiler, but this time multithreading, asyncio and gevent aware.
Sampling Profiler for Python - Simple Python sampling profiler