pyflow VS Nuitka

Very cool! Of note, I made something along these lines a few years ago, although with a slightly broader scope to also include managing and installing python versions. I abandoned it due to lack of free time, and edge cases breaking things. The major challenge is that Python packages that aren't wheels can do surprising things due to setup.py running arbitrary code. (https://github.com/David-OConnor/pyflow)

Pyflow

Pyflow takes care of the use when you need pyenv to isolate different python versions, pipx to isolate some global python-based tools, and isolated, reproducible builds per project with on tool. I highly recommend people to give it go.

https://github.com/David-OConnor/pyflow#a-thoroughly-biased-...

Pyflow is a similar implementation of PEP582. NGL I wonder if it's better because of how good Rust stuff is. Probably a lot faster. Looks like you can install it via Pypi. I should've tested it before moving to PDM. Though it seems dev is a bit slow. Hmmm.

I’m personally complaining that pip is so much behind cargo. I have some hope with Pyflow though.

I literally stumbled into this issue again today. Has anyone leveraged Pyflow before? It looks pretty slick for keeping things organized. I don't do heavy dev work, just need something to keep things generally tidy. Was curious if anyone had used it and their opinion on it.

PDM is pretty new so it’s not entirely clear how it’ll play out but if you’re interested in PEP 582 then it’s really that or pyflow.

It's a good safeguard, and it's going in the direction of the other initiatives to make python package management default behavior saner.

PEP 852 is the another one to follow up: https://www.python.org/dev/peps/pep-0582/

It basically uses the concept of node_modules, making python interpreters local any local __pypackages__ directory. There are 2 differences though:

- unlike JS, python can only have one version of one lib

- but since having several versions of python often matters, you may have several __pypackages__/X.Y sub dirs to catter to each of them

It does also force you to use "-m" to use commands, which is the best practice anyway. I hope it will make jupyter fix "-m" on windows for them because that's a blocker for beginners.

If you are not already using "-m", start now. It solves a lot of different problems with running python cli programs.

E.G: instead of running "black" or "pylint", do "python -m black" or "python -m pylint". Or course you may want to chose a specific version of python, so "python3.8 -m black" for unix, or "py -3.8 -m black" on windows.

To test out __pypackages__, give a try to the pdm project: https://github.com/pdm-project/pdm

At last, some other tools that I wish people knew more about that solves packaging issues:

- pyflow (https://github.com/David-OConnor/pyflow): it's a package manager like poetry, but it also install whatever python you want like pyenv. Except it provides the binary, no need to compile anything. It's a young project, but I wish it succeeds because it's really a great concept.

- shiv (shiv.readthedocs.io/): it leverage the concept of zipapp, meaning the ability that python has to execute python inside a zip file. It's a successor to pex. Basically it lets you bundle your code + all deps from virtualenv inside a zip, like a Java .war file. You can then run the resulting zip, a .pyz file, like if it was a regular .py file. It will unzip on the first run automatically. It makes deployment almost as easy as with golang.

- nuitka (shiv.readthedocs.io/): take your code and all dependancies, turn them into C, and compiles it. Although it does require a bit of setup, since it needs headers and a compiler, it results reliably in a standalone compiled executable that will run on the same architecture with no need for anything else. Also it will speed up your Python program, up to 4 times.

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