rust
py-spy
rust | py-spy | |
---|---|---|
9 | 25 | |
4,997 | 11,864 | |
0.9% | - | |
5.2 | 6.4 | |
5 months ago | 25 days ago | |
Rust | Rust | |
Apache License 2.0 | 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.
rust
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Have you ever wanted a library to check for 69 in a string?
You can use Tensorflow for Rust to simplify that task and avoid pain with regex. Just have the right mindset.
- Rust vs cpp for a new engineer to autonomous vehicles and robotics
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Making a better Tensorflow thanks to strong typing
What is the benefit of this compared to using bindings/a wrapper to Tensorflow, or other ML libraries written in C/C++, such as this community hosted project on tensorflow's github. If it's just for fun that is a valid enough reason imo, just curious since you describe it as a better Tensorflow because of the typing vs using the python wrapper, when there already exist ways to interact with tensorflow with both Rust and other statically typed languages, also including C++ (officially supported), C#, Haskell and Scala, as well as probably having bindings not mentioned on the documentation for more niche languages.
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Integrating machine learning models into Rust applications?
(3) You could use TensorFlow as your executor: https://github.com/tensorflow/rust
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Why Static Languages Suffer From Complexity
TensorFlow has language support for TypeScript well as Rust.
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Is PyO3 library production ready?
Thank you for the restponse! With tensorflow I am probably better of with something like; [tensorflow rust bindings](https://github.com/tensorflow/rust/tree/master/src). But I believe some useful extensions are still written in python for example; [TFDV](https://github.com/tensorflow/data-validation).. and how about scikit-learn or even something that is simpler like fb-prophet that is entirely written in python?
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How mature is the QT integration?
Tensorflow bindings exist, technically, but they're in a pretty rough state AFAIK.
- Feasibility of Using a Python Image Super Resolution Library in My Rust App
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Rusticles #10 - Wed Sep 09 2020
tensorflow/rust (Rust): Rust language bindings for TensorFlow
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?
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
pyflame
leaf - Open Machine Intelligence Framework for Hackers. (GPU/CPU)
pyinstrument - 🚴 Call stack profiler for Python. Shows you why your code is slow!
anyhow - Flexible concrete Error type built on std::error::Error
python-uncompyle6 - A cross-version Python bytecode decompiler
Rustup - The Rust toolchain installer
memory_profiler - Monitor Memory usage of Python code
rusty-machine - Machine Learning library for Rust
icecream - 🍦 Never use print() to debug again.
solana - Web-Scale Blockchain for fast, secure, scalable, decentralized apps and marketplaces.
line_profiler