birthday-book-app
poly-match
birthday-book-app | poly-match | |
---|---|---|
5 | 6 | |
29 | 31 | |
- | - | |
2.3 | 2.3 | |
about 1 year ago | 26 days ago | |
Rust | Python | |
Apache License 2.0 | Apache License 2.0 |
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birthday-book-app
- Rust in Anger: high-performance web applications
- Blog Post: Making Python 100x faster with less than 100 lines of Rust
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Writing python extensions never been easier… with Rust and PyO3
For the impatient, the associated GitHub repo: https://github.com/EqualTo-Software/birthday-book-app
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Rust in Anger: high-performance code in the modern web stack
Just a heads up, your "accompanying code" link appears to be broken. It links to https://github.com/EqualTo-Software/blog-post, when I think you want to link to https://github.com/EqualTo-Software/birthday-book-app.
poly-match
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Improving Interoperability Between Rust and C++
Not my experience at all. At work we rewrote a small bit of hotspot python in Rust with no issues. This was what we primarily followed: https://ohadravid.github.io/posts/2023-03-rusty-python/
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How to convince my boss that Rust is usable
Take at look at this example, it still uses Python as an interface to Rust code. Maybe you can do something similar to still achieve performance improvements without changing the entire codebase.
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GDScript is fine
People are probably downvoting because it's needlessly hyperbolic and argumentative. Nobody is saying that python isn't faster to iterate with, but they're arguing that it would take months to get negligable performance gains in a lower level language, meanwhile here is a recent post from a company that increased the execution of they're python code by 100x with less than 100 lines of Rust. They also claim that nobody cares if something runs a few milliseconds faster, when we're talking about game dev, where games are frequently judged on how many milliseconds it takes to run game logic between frames.
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Making Python 100x faster with less than 100 lines of Rust
Semi Vectorized code:
https://github.com/ohadravid/poly-match/blob/main/poly_match...
Expecting Python engineers unable to read defacto standard numpy code but meanwhile expect everyone can read Rust.....
Not to mention that the semi-vectorized code is still suboptimal. Too many for loops despite the author clearly know they can all be vectorized.
For example instead the author can just write something like:
np.argmin(
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Blog Post: Making Python 100x faster with less than 100 lines of Rust
The article links to a full implementation, so you should be able to test this.
What are some alternatives?
rustimport - Import Rust source files directly from Python!
jnumpy - Writing Python C extensions in Julia within 5 minutes.
tsify - A library for generating TypeScript definitions from rust code.
gopy - gopy generates a CPython extension module from a go package.
StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)
truffleruby - A high performance implementation of the Ruby programming language, built on GraalVM.
PythonCall.jl - Python and Julia in harmony.
numexpr - Fast numerical array expression evaluator for Python, NumPy, Pandas, PyTables and more
maturin - Build and publish crates with pyo3, cffi and uniffi bindings as well as rust binaries as python packages
rust-script - Run Rust files and expressions as scripts without any setup or compilation step.
ruff - An extremely fast Python linter and code formatter, written in Rust.
NodeCall.jl - Call NodeJS from Julia.