uv
hatch
uv | hatch | |
---|---|---|
13 | 20 | |
11,653 | 5,399 | |
17.6% | 3.6% | |
10.0 | 9.5 | |
5 days ago | 5 days ago | |
Rust | Python | |
Apache License 2.0 | 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.
uv
- uv: An fast Python package installer and resolver, written in Rust
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Trying Out Rye
It’s worth calling out that it’s still early days for Rye. The ownership recently transitioned from Armin Ronacher to the team that develops ruff (https://astral.sh). No doubt limitations exist today, but it’s going to look a lot more like cargo as they put out more releases.
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Uv saves Home Assistant 215 compute hours per month
Happy to report that this definitely isn't a paid ad. The Home Assistant team did this on their own. I helped out by building uv for some of the architectures they needed: https://github.com/astral-sh/uv/pull/2417
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Pyenv – lets you easily switch between multiple versions of Python
https://github.com/astral-sh/uv
So fast it finally made virtual environments usable for me.
- Python's pip on steroids
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This Week in Python (February 23, 2024)
uv – An extremely fast Python package installer and resolver, written in Rust
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Multi-Stage Docker Builds for Pyton Projects using uv
Charlie Marsh and the brillant guys at Astral have helped the python ecosystem a lot with ruff and now they have released a new tool: uv.
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Ask HN: How to determine company's long term dependability? (Ello, Astral)
[2] https://github.com/astral-sh/uv
- Astral – fast Python package installer and resolver written in Rust
- An fast Python package installer and resolver, written in Rust
hatch
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Uv: Python Packaging in Rust
Exciting stuff! I view Hatch [1] as becoming the Cargo for Python because it's already close and has an existing (and growing) user base but I can definitely see depending on this for resolution and potentially not even using pip after it becomes more stable.
[1]: https://hatch.pypa.io/latest/
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lockfiles for hatch projects
I was inspired enough by the hatch sync idea that I created a PR to add that functionality to hatch: https://github.com/pypa/hatch/pull/1094
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Building and Releasing a Python CLI
Another concept I learned was about build backends, an import step which is used to initialize and install any dependencies of the app you're packaging. Since the tutorial went with using Hatch that is also what I went with, though it didn't provide a lot of useful details especially because it didn't show how to add any dependencies, so I took a look at the docs which were very nice and simple to follow.
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Is there an up-to-date python package template?
Try using hatch: https://hatch.pypa.io/latest/
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How do I install dependencies in Hatch?
I'm trying to learn Hatch, I currently use [Poetry](python-poetry.org/) to manage my dependencies, and while I'm overall happy with it, I really like the features I'm reading about with Hatch. I'm also working on learning CI pipelines & Dockerizing Python applications, and Hatch seems like a really useful tool to learn for this (and just as a general use tool).
- pipenv or virtualenv ?
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Call for questions for Guido van Rossum from Lex Fridman
Poetry 1.2 has been a pain. Which was the dev's fault though. Switching to something new while deprecating a related feature is just plain bad. I've been looking into modern alternatives like PDM and Hatch, but haven't used them (yet).
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So how do you actually deploy code/scripts?
For example, when it comes to Python, one option is to use the same packaging system that a huge number of open-source libraries and tools are published with. You can use setuptools or Hatch to build a "packaged" version of your code, and publish it to either the public PyPi repository or an internal one that you set up. Then your users can use pip to install your package, automatically fetch its dependencies, and keep it up to date, just like any other Python module.
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Scala isn't fun anymore
Don't forget the new PyPa tool on the block: Hatch.
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How to create a Python package in 2022
See also: https://github.com/pypa/hatch
What are some alternatives?
rye - a Hassle-Free Python Experience
Poetry - Python packaging and dependency management made easy
pyflow - An installation and dependency system for Python
setuptools - Official project repository for the Setuptools build system
flower - Flower: A Friendly Federated Learning Framework
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
rfcs - RFCs for changes to Rust
poetry-dynamic-versioning - Plugin for Poetry to enable dynamic versioning based on VCS tags
asdf - Extendable version manager with support for Ruby, Node.js, Elixir, Erlang & more
reloadium - Hot Reloading and Profiling for Python
asdf-python - Python plugin for the asdf version manager
PyNeuraLogic - PyNeuraLogic lets you use Python to create Differentiable Logic Programs