static-analysis
py-spy
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static-analysis | py-spy | |
---|---|---|
15 | 25 | |
12,858 | 11,850 | |
1.8% | - | |
9.4 | 6.4 | |
9 days ago | 16 days ago | |
Rust | Rust | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
static-analysis
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Static Analysis Tools for C
Readers should also peruse the 'Multiple languages' section, many of the big names, Coverity, Klocwork et al. are listed there.
see https://github.com/analysis-tools-dev/static-analysis#multip...
- Static-analysis – A curated list of static analysis (SAST) tools and linters
- Are you in favor of small functions/clean code or opposed to it?
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Looking for feedback on our new website for Code Analysis Tools
this is Matthias from https://analysis-tools.dev.
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Beating a dead horse?
Not an area I've had to deal with much unfortunately. Here is also a curated list of SAST tools grouped by technology. It can take quite some time to properly vet tools like this, but you might find something valuable in there.
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Checked C
https://github.com/analysis-tools-dev/static-analysis
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From Novice to contributor to Linux Kernel and/or other Low-Level projects
You can for example rely on static analyzers and scan the repositories (just please take care of making sure that any fix you make actually makes sense, sometimes people will just make whatever causes the reports to go away without understanding them). This site lists a bunch of them for different languages -> https://analysis-tools.dev/
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What's the best free security scan tool for C/C++ files?
There's a bunch on https://github.com/analysis-tools-dev/static-analysis
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Does anyone know of any tool for calculating the cyclomatic complexity of pascal-based source code?
https://github.com/analysis-tools-dev/static-analysis - general list of SAST
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?
solana - Web-Scale Blockchain for fast, secure, scalable, decentralized apps and marketplaces.
pyflame
awesome-rust - A curated list of Rust code and resources.
pyinstrument - 🚴 Call stack profiler for Python. Shows you why your code is slow!
find-sec-bugs - The SpotBugs plugin for security audits of Java web applications and Android applications. (Also work with Kotlin, Groovy and Scala projects)
python-uncompyle6 - A cross-version Python bytecode decompiler
rust-blog - Educational blog posts for Rust beginners
memory_profiler - Monitor Memory usage of Python code
awesome-linters - A community-driven list of awesome linters.
icecream - 🍦 Never use print() to debug again.
dynamic-analysis - ⚙️ A curated list of dynamic analysis tools and linters for all programming languages, binaries, and more.
line_profiler