Nuitka VS rfcs

Thanks for the feedback! I'm Syrus, main author of the work on py2wasm.

We already opened a PR into Nuitka to bring the relevant changes upstream: https://github.com/Nuitka/Nuitka/pull/2814

We envision py2wasm being a thin layer on top of Nuitka, as also commented in the article.

From what we gathered, we believe that there's usefulness on having py2wasm as a separate package, as py2wasm would also need to ship the precompiled Python distribution (3.11) for WASI (which will not be needed for the other Nuitka use cases), apart of also shipping other tools that are not directly relevant for Nuitka

This is a good place to mention https://nuitka.net/ which aims to compile python programs into standalone binaries.

For Python, you could make a proper deployment binary using Nuitka (in standalone mode – avoid onefile mode for this). I'm not pretending it's as easy as building a Go executable: you may have to do some manual hacking for more unusual unusual packages, and I don't think you can cross compile. I think a key element you're getting at is that Go executables have very few dependencies on OS packages, but with Python (once you've sorted the actual Python dependencies) you only need the packages used for manylinux [2], which is not too onerous.

[1] https://nuitka.net/

[2] https://peps.python.org/pep-0599/#the-manylinux2014-policy

glee is rich in blogging features but has some drawbacks. One of the main drawbacks is its compatibility with multiple operating systems and system architectures. We lost one potential customer due to glee incompatibility in macOS. Another major issue is the deployment time. We built the first version of glee entirely in Python and used nuitka, nuitka compiles Python programs into a single executable binary file. We need to create three separate stages for creating executable binaries for Windows, Mac, and Linux in deployment, and it takes around 20 minutes to complete.

There is already an AOT compiler for Python: Nuitka[0]. But I don't think it's much faster.

And then there is mypyc[1] which uses mypy's static type annotations but is only slightly faster.

And various other compilers like Numba and Cython that work with specialized dialects of Python to achieve better results, but then it's not quite Python anymore.

[0] https://nuitka.net/

[1] https://github.com/python/mypy/tree/master/mypyc

Nuitka deals pretty well with those in general: https://nuitka.net/

Hi HN,

Has anyone explored Nuitka [1] and developed understanding from a blank slate?

Is there any toy version of this, so that one can start playing with the language translation concepts?

Is there any underlying theory/inspiration upon which this project is built?

Are there any similar projects, in say other languages?

[1] https://github.com/Nuitka/Nuitka

That's more of cultural problem in the Python community.

If I provide an end user software to my client written an Python (so not a backend, not a lib...), I will compile it with nuitka (https://github.com/Nuitka/Nuitka) and hide the stack trace (https://www.bitecode.dev/p/why-and-how-to-hide-the-python-st...) to provide a stand alone executable.

This means the users don't have to know it's made with Python or install anything, and it just works.

However, Python is not like Go or Rust, and providing such an installer requires more than work, so a huge part of the user base (which have a lot of non professional coders) don't have the skill, time or resources to do it.

And few people make the promotion of it.

I should write an article on that because really, nobody wants to setup python just to use a tool.

As for a simpler option, you could use a "compiler": https://github.com/Nuitka/Nuitka

RFC: Add large language models to Rust

https://github.com/rust-lang/rfcs/pull/3603

Man, SO and family has really gone downhill. That top answer is absolutely terrible. In fact, if you care, you can literally look at the RFC discussion here to see the actual debate: https://github.com/rust-lang/rfcs/pull/582

Basically, `for x in y` is kind of redundant, already sorta-kinda supported by itertools, and there's also a ton of macros that sorta-kinda do it already. It would just be language bloat at this point.

Literally has nothing to do with memory management.

Congrats!

> Similarly, uv does not yet generate a platform-agnostic lockfile. This matches pip-tools, but differs from Poetry and PDM, making uv a better fit for projects built around the pip and pip-tools workflows.

Do you expect to make the higher level workflow independent of requirements.txt / support a platform-agnostic lockfile? Being attached to Rye makes me think "no".

Without being platform agnostic, to me this is dead-on-arrival and unable to meet the "Cargo for Python" aim.

> uv supports alternate resolution strategies. By default, uv follows the standard Python dependency resolution strategy of preferring the latest compatible version of each package. But by passing --resolution=lowest, library authors can test their packages against the lowest-compatible version of their dependencies. (This is similar to Go's Minimal version selection.)

> uv allows for resolutions against arbitrary target Python versions. While pip and pip-tools always resolve against the currently-installed Python version (generating, e.g., a Python 3.12-compatible resolution when running under Python 3.12), uv accepts a --python-version parameter, enabling you to generate, e.g., Python 3.7-compatible resolutions even when running under newer versions.

This is great to see though!

I can understand it being a flag on these lower level, directly invoked dependency resolution operations.

While you aren't onto the higher level operations yet, I think it'd be useful to see if there is any cross-ecosystem learning we can do for my MSRV RFC: https://github.com/rust-lang/rfcs/pull/3537

How are you handling pre-releases in you resolution? Unsure how much of that is specified in PEPs. Its something that Cargo is weak in today but we're slowly improving.

In the early days of Rust there was a debate about whether to support "green threads" and in doing that require runtime support. It was actually implemented and included for a time but it creates problems when trying to do library or embedded code. At the time Go for example chose to go that route, and it was both nice (goroutines are nice to write and well supported) and expensive (effectively requires GC etc). I don't remember the details but there is a Rust RFC from when they removed green threads:

https://github.com/rust-lang/rfcs/blob/0806be4f282144cfcd55b...

I did some more digging. By RFC 899, I believe Alex Crichton meant PR 899 in this repo:

https://github.com/rust-lang/rfcs/pull/899

Still, no real discussion of why unbuffered stderr.

Rust has had a stable SIMD vector API[1] for a long time. But, it's architecture specific. The portable API[2] isn't stable yet, but you probably can't use the portable API for some of the more exotic uses of SIMD anyway. Indeed, that's true in .NET's case too[3].

Rust does all this SIMD too. It just isn't in the standard library. But the regex crate does it. Indeed, this is where .NET got its SIMD approach for multiple substring search from in the first place[4]. ;-)

You're right that Rust's standard library is conservatively vectorized though[5]. The main thing blocking this isn't the lack of SIMD availability. It's more about how the standard library is internally structured, and the fact that things like substring search are not actually defined in `std` directly, but rather, in `core`. There are plans to fix this[6].

[1]: https://doc.rust-lang.org/std/arch/index.html

[2]: https://doc.rust-lang.org/std/simd/index.html

[3]: https://github.com/dotnet/runtime/blob/72fae0073b35a404f03c3...

[4]: https://github.com/dotnet/runtime/pull/88394#issuecomment-16...

[5]: https://github.com/BurntSushi/memchr#why-is-the-standard-lib...

[6]: https://github.com/rust-lang/rfcs/pull/3469