zpy
pip-tools
zpy | pip-tools | |
---|---|---|
35 | 58 | |
67 | 7,477 | |
- | 0.7% | |
9.1 | 8.9 | |
3 days ago | 5 days ago | |
Shell | Python | |
Do What The F*ck You Want To Public License | BSD 3-clause "New" or "Revised" 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.
zpy
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This Week In Python
zpy – Zsh helpers for Python venvs, with uv or pip-tools
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Canonical blocked installing, or uninstalling pip packages on Ubuntu 23.04, what it can be done to solve these issues?
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.
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As if there weren't enough packaging tools already: mitsuhiko/rye: an experimental alternative to poetry/pip/pipenv/venv/virtualenv/pdm/hatch/…
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).
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How do I build up my package's extra dependencies from groups of dependencies in a pyproject.toml?
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.
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What is your workflow for managing virtual environments for personal projects?
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.
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One Does Not Simply 'pip install'
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
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pipenv or virtualenv ?
For concise and practical interactive usage of those tools, with excellent tab completion, I made the Zsh frontend zpy.
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How to know what a package depend on when pip is installing it?
I also use my own Zsh wrapper functions with it, so for example: https://i.imgur.com/YX8bWy8.png
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I moved away from Poetry for Python
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.
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Any recent updates in dependency management?
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.
pip-tools
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Pyenv – lets you easily switch between multiple versions of Python
> 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.
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lockfiles for hatch projects
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.
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Setting up Django in a Better Way in 5 Minutes and Understanding How It Works
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.
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just-pip-tools: An example of managing python dependencies as layered lock files with just and pip-tools
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.
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Maintaining virtual environments
For small projects I recommend pip-tools. Just write packet list in requirements.in and pip-compile compile a requirements.txt with comments.
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how to upgrade psycopg2 to psycopg3 as per django latest documentation
Take a look at pip-tools, great package. https://github.com/jazzband/pip-tools
- Single-file scripts that download their dependencies
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What are people using to organize virtual environments these days?
pip-tools
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How to know what a package depend on when pip is installing it?
I recommend generating a lockfile to document this information, as you might do with pip-tools.
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A not so unfortunate sharp edge in Pipenv
Check out pip-tools [1] which does exactly that, albeit in a slightly more polished way.
[1]: https://github.com/jazzband/pip-tools
What are some alternatives?
hatch - Modern, extensible Python project management
Poetry - Python packaging and dependency management made easy
agkozak-zsh-prompt - A fast, asynchronous Zsh prompt with color ASCII indicators of Git, exit, SSH, virtual environment, and vi mode status. Framework-agnostic and customizable.
PDM - A modern Python package and dependency manager supporting the latest PEP standards
wheezy.template - A lightweight template library.
Pipenv - Python Development Workflow for Humans.
taskipy - the complementary task runner for python
conda - A system-level, binary package and environment manager running on all major operating systems and platforms.
zplug - :hibiscus: A next-generation plugin manager for zsh
pip - The Python package installer
tox-pin-deps - Run tox environments with strictly pinned dependencies (and no project or code changes).
miniforge - A conda-forge distribution.