pixi
pyflow
pixi | pyflow | |
---|---|---|
5 | 12 | |
1,961 | 1,306 | |
9.5% | - | |
9.8 | 0.0 | |
4 days ago | about 1 year ago | |
Rust | Rust | |
BSD 3-clause "New" or "Revised" License | 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.
pixi
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Xmake: A modern C/C++ build tool
re: C/C++ development: anybody using conda/pixi for dependency management? Here's an example of compiling a C++ SDL program using pixi and the SDL dependency from conda-forge [1].
Seems viable as a replacement for things like vckpg [2] which only builds from source.
I'm still researching this but it seems like rattler [3] is the tool to use to build/publish packages. The supported repos are: prefix.dev's own hosting, anaconda.org, artifactory or a self-hosted server.
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1: https://github.com/prefix-dev/pixi/blob/main/examples/cpp-sd...
2: https://github.com/microsoft/vcpkg
3: https://prefix-dev.github.io/rattler-build/latest/authentica...
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Install Asdf: One Runtime Manager to Rule All Dev Environments
I recently started using https://github.com/prefix-dev/pixi for Python projects. I really love it so far, but this tool looks a bit more mature, which makes sense considering pixi is relatively new.
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Pyenv – lets you easily switch between multiple versions of Python
Have you tried https://pixi.sh/ ? It brings Cargo/NPM/Poetry like commands and lock files to the Conda ecosystem, and now can manage and lock PyPI dependencies alongside by using uv under the hood.
I haven't been using anything CUDA, but the scientific geospatial stack is often a similar mess to install, and it's been handling it really well.
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Uv: Python Packaging in Rust
Isn't this basically what pixi wants to be? Wouldn't it be better to work together?
https://github.com/prefix-dev/pixi/
- Pixi: Package Management Made Easy
pyflow
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Uv: Python Packaging in Rust
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)
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Incompatible Child Dependencies -- how are they resolved?
Pyflow
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Freezing Requirements with Pip-Tools
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-...
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Empty npm package '-' has over 700,000 downloads
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.
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pip and cargo are not the same
I’m personally complaining that pip is so much behind cargo. I have some hope with Pyflow though.
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XKCD | Python Environment
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.
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Moving from pipenv to poetry or PDM
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.
- Python: Please stop screwing over Linux distros
- Pyflow: An Alternative to Poetry and Pyenv
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Cooperative Package Management for Python
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.
What are some alternatives?
rip - Solve and install Python packages quickly with rip (pip in Rust)
Poetry - Python packaging and dependency management made easy
Ferry - A Rustified package manager for python
PDM - A modern Python package and dependency manager supporting the latest PEP standards
asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more
dephell - :package: :fire: Python project management. Manage packages: convert between formats, lock, install, resolve, isolate, test, build graph, show outdated, audit. Manage venvs, build package, bump version.
tox - Command line driven CI frontend and development task automation tool.
pants - The Pants Build System
pyenv - Simple Python version management
Nuitka - Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
llama.cpp - LLM inference in C/C++
WinPython - A free Python-distribution for Windows platform, including prebuilt packages for Scientific Python.