zpy VS pip-tools

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.

> Why is the "requirements.txt" file a stupid flat listing of all transitive dependencies with pinned versions? It makes it harder to change library versions even if there are no true conflicts.

My friend, here is what you seek: https://github.com/jazzband/pip-tools

requirements.txt is flat because it's really the output of `pip freeze`. It's supposed to completely and exactly rebuild the environment. Unfortunately it's far too flexible and people abuse it by putting in only direct dependencies etc.

If you're writing packages, you don't need a requirements.txt at all, by the way. Package dependencies (only direct dependencies) live in pyproject.toml with the rest of the package config. requirements.txt (and pip tools) are only for when you want to freeze the whole environment, like for a server deployment.

For all my projects I found myself regenerating manual lock files using complex shell commands with pip-compile to get a reproducible environments across devices using a custom pre-install-command. I finally decided that instead of hacking together the same solution on all my projects I would build a plugin that handles this complexity for me.

Instead of venv, we are using pip-tools in this starter kit. pip-tools take things further in dependency management. Check out what pip-tools does in their official GitHub repo. In short, it helps your project find the best match for the dependent packages. For example, you might need two packages A and B in your project that requires same package C under the hood. But A requires any version of C from 1.0.1 to 1.0.10 and B requires any version of C from 1.0.7 to 1.0.15. Pip tools will automatically compile the version of 'C' that suits for both of your packages.

I've created a small project called just-pip-tools that combines pip-tools and just to manage Python dependencies in a layered approach. This isn't a magic bullet; it's a set of files you can adapt to your needs.

For small projects I recommend pip-tools. Just write packet list in requirements.in and pip-compile compile a requirements.txt with comments.

Take a look at pip-tools, great package. https://github.com/jazzband/pip-tools

pip-tools

I recommend generating a lockfile to document this information, as you might do with pip-tools.

Check out pip-tools [1] which does exactly that, albeit in a slightly more polished way.

[1]: https://github.com/jazzband/pip-tools