rust-quiz
rust-numpy
rust-quiz | rust-numpy | |
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11 | 10 | |
1,587 | 1,019 | |
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6.2 | 8.0 | |
26 days ago | 19 days ago | |
Rust | Rust | |
Creative Commons Attribution Share Alike 4.0 | BSD 2-clause "Simplified" License |
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rust-quiz
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So you think you know C?
If you didn't like these because they're "trick" questions you likely also would not enjoy CppQuiz (https://cppquiz.org/)
However you might well enjoy https://dtolnay.github.io/rust-quiz/
Like the C++ quiz, "Undefined Behaviour" is a valid answer, however, the quiz questions are about safe Rust, so that answer is always wrong.
I still get more than half of them wrong unless given far too long to think about it.
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Introducing the "Rust Interview Handbook" - Your Go-To Resource for Rust Interview Success! 💪
Cool, but I feel like the current questions are super basic. Something you're able to answer after reading the book and toying with Rust on a weekend. Definitely needs some harder questions, maybe feel inspired by https://dtolnay.github.io/rust-quiz/?
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The Usability of Advanced Type Systems: Rust as a Case Study
> If we accept that Rust is indeed more difficult to learn than comparable systems programming languages
My problem is with "comparable systems programming languages". To me the only thing that fits there today is C++ and while a great many programming languages would be easier to learn than Rust, C++ is not one of them by a long shot.
I think the C++ Quiz https://cppquiz.org/ and the Rust Quiz https://dtolnay.github.io/rust-quiz/ illustrate handily. Neither of these languages is a walk in the park, but, notice they both have "Undefined behaviour" as a possible answer? Safe Rust doesn't actually have undefined behaviour, so you get to rule out one of the possibilities any time you don't see the "unsafe" keyword, which is in fact every time on the Rust Quiz. In C++ some of the quiz questions invoke UB, but good luck correctly guessing which ones.
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Examples of old (ca. 1.0.0+) Rust code that still compiles?
Do you actually want to question all you know about Rust? Do this amazing quiz by the famed dtolnay.
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[Media] Is the LinkedIn Rust quiz OK 🤨
If you want a correct and much harder Rust quiz, here you go.
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Anything C can do Rust can do Better
⭐ Rust Quiz - David Tolnay
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Carefully exploring Rust as a Python developer
One surprise perhaps is that both Python and C++ have multiple inheritance whereas Rust doesn't have implementation inheritance at all (Rust's traits can inherit but data structures and implementations cannot).
Both C++ and Rust have similar Quiz sites:
https://dtolnay.github.io/rust-quiz/
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An interviewee has "(interest) Rust" in his resume, which question should I ask him ?
Obligatory: https://dtolnay.github.io/rust-quiz/
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Rust (Programming Language) is now a skill that LinkedIn assesses
There is also this quiz
- Rust Quiz
rust-numpy
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Numba: A High Performance Python Compiler
On the contrary, it can use and interface with numpy quite easily: https://github.com/PyO3/rust-numpy
- Carefully exploring Rust as a Python developer
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Hmm
Once I figured out the right tools, it was easy. Its just "maturin new". It automatically converts python floats and strings. Numpy arrays come through as a special Pyarray type, that you need to unwrap, but that's just one builtin function. Using pyo3, maturin and numpy, https://github.com/PyO3/rust-numpy it's fairly easy.
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Man, I love this language.
If I'm understanding this documentation correctly then you may be able to pass the numpy array directly with func(df['col'].to_numpy) which may save some conversion.
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[D] Is Rust stable/mature enough to be used for production ML? Is making Rust-based python wrappers a good choice for performance heavy uses and internal ML dependencies in 2021?
Otherwise, though, Rust is an excellent choice. The many advantages of Rust (great package manager, memory safety, modern language features, ...) are already well documented so I won't repeat them here. Specifically for writing Python libraries, check out PyO3, maturin, and rust-numpy, which allow for seamless integration with the Python scientific computing ecosystem. Dockerizing/packaging is a non-issue, with the aforementioned libraries you can easily publish Rust libraries as pip packages or compile them from source as part of your docker build. We have several successful production deployments of Rust code at OpenAI, and I have personally found it to be a joy to work with.
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Writing Rust libraries for the Python scientific computing ecosystem
Integration with numpy uses the rust-numpy crate: Example of method that accepts numpy arrays as arguments Example of a method that returns a numpy array to Python (this performs a copy, there ought to be a way to avoid it but the current implementation has been plenty fast for my use case so far)
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Feasibility of Using a Python Image Super Resolution Library in My Rust App
This example maybe helpful.
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Julia is the better language for extending Python
Given that it's via pyO3, you could even pass the numpy arrays using https://github.com/PyO3/rust-numpy and get ndarrays at the other side.
Same no copy, slightly more user friendly approach.
Further criticism of the actual approach - even if we didn't do zero copy, there's no preallocation for the vector despite the size being known upfront, and nested vectors are very slow by default.
So you could speed up the entire thing by passing it to ndarray, and then running a single call to sum over the 2D array you'd find at the other end. (https://docs.rs/ndarray/0.15.1/ndarray/struct.ArrayBase.html...)
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Parsing PDF Documents in Rust
I believe converting between pandas Series (e.g. columns) and numpy ndarrays can be pretty cheap, right? Once they're in that format, you can use rust to work directly on the numpy memory buffer with rust-numpy. Otherwise, feather is a format designed for IPC of columnar data; pyarrow is in pandas (might be an optional dependency) and may be pretty quick for that, and rust has an arrow implementation too.
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PyO3: Rust Bindings for the Python Interpreter
https://github.com/PyO3/rust-numpy
What are some alternatives?
linkedin-skill-assessments-quizzes - Full reference of LinkedIn answers 2023 for skill assessments (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point) linkedin excel test lösungen, linkedin machine learning test LinkedIn test questions and answers
RustPython - A Python Interpreter written in Rust
cargo-llvm-lines - Count lines of LLVM IR per generic function
julia - The Julia Programming Language
db-dump - Library for scripting analyses against crates.io's database dumps
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
async-trait - Type erasure for async trait methods
rayon - Rayon: A data parallelism library for Rust
rust-sokoban - Rust Sokoban book and code samples
image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
semver-trick - How to avoid complicated coordinated upgrades
PyO3 - Rust bindings for the Python interpreter