zpy VS hatch

zpy – Zsh helpers for Python venvs, with uv or pip-tools

If your interactive shell is zsh, you could give my project zpy a try, particularly the function pipz that it provides, which is a lightweight pipx clone with great completions and good speed.

I can immediately see some things rye is doing differently, like keeping the venvs themselves free of pip and pip-tools. I wonder in your explorations if you've tried rtx for managing python installations, or my own zpy wrapper of pip-tools+venv (which can also replace pipx).

My patterns in this regard aren't exactly mainstream, as I use flit+pip-tools+zpy (the latter being my own Zsh interface for Python dependency and environment operations), but FWIW here's how I go about nested requirements.

For managing venvs and dependencies and apps, I use my own frontend to pip-tools + venv, zpy. And for running tasks which require an activated venv, I use nox.

If anyone's interested in a pipx clone with excellent tab completion, I would appreciate any feedback on pipz, a function of my zsh plugin for python environment and dependency management: zpy

https://github.com/andydecleyre/zpy

For concise and practical interactive usage of those tools, with excellent tab completion, I made the Zsh frontend zpy.

I also use my own Zsh wrapper functions with it, so for example: https://i.imgur.com/YX8bWy8.png

I'm a big fan of (and small contributor to) pip-tools, but both poetry and pipenv offer management of more stuff, which understandably appeals to folks seeking a simple comprehensible workflow.

Pip-tools is also a bit lower level, offering flexibility and compatibility which I relish, but also requiring more attention from the user to set things up as they wish.

If you or anyone else enjoying pip-tools is a Zsh user and interested in trying out my higher level functions to ease interactive use of pip-tools, venvs, and also isolated app installs (like pipx), I would love some feedback on zpy: https://github.com/AndydeCleyre/zpy

I'm very happy to answer any questions about it right here or as GitHub issues.

This is FAR from some big mainstream thing, but I use (and am happy to answer any questions about) my own Zsh frontend to venv+pip-tools+pip, zpy.

Configuring Tools and Dependencies: Hatch, a package manager and environment tool, was used to simplify the setup process. Installing and configuring Hatch was straightforward, ensuring the Python environment was set up correctly. Essential dependencies like FastAPI and Uvicorn were specified in the pyproject.toml file for easy management.

Workspaces is unblocked now, it depended on a large refactor which has now been merged: https://github.com/pypa/hatch/pull/1602

In my free time, it's the only thing I'm working on!

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/

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

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.

Try using hatch: https://hatch.pypa.io/latest/

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).

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).

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.