python-poetry-docker-example
zpy
python-poetry-docker-example | zpy | |
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5 | 35 | |
332 | 67 | |
- | - | |
0.0 | 9.1 | |
over 1 year ago | 1 day ago | |
Dockerfile | Shell | |
MIT License | Do What The F*ck You Want To Public 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.
python-poetry-docker-example
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Docker multi stage build with Poetry feedback
I'm using this example as reference here found from Google for a multi-stage build with Poetry but I'm not sure why my Docker image hasn't changed in size. It's still 572MB when I push the build to my registry. Is it supposed to be that large for an Alpine image?
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Getting Started with Python in 2022 – pyenv and poetry
I use something like this for multi stage builds with poetry. It is a little complex, but it’s the same for every project and always works. https://github.com/michaeloliverx/python-poetry-docker-example/blob/master/docker/Dockerfile
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Confusion with unit and integration testing in CI pipeline
I've been using this Dockerfile as a template of sorts because it pretty clearly delineates the various stages and concerns in a multi-stage Dockerfile.
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Integration testing Azure DevOps Pipelines for AKS deployment
I have a multi-stage Dockerfile, that is pretty similar to this one, where one of the stages runs my unit tests. The step before running the production stage is running this stage to see if any unit tests fail. If not, it should complete the production build, and then move on to integration tests.
- Keep seeing "npm run start" on production stages in multi-stage Docker builds
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.
What are some alternatives?
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
hatch - Modern, extensible Python project management
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.
wheezy.template - A lightweight template library.
taskipy - the complementary task runner for python
zplug - :hibiscus: A next-generation plugin manager for zsh
tox-pin-deps - Run tox environments with strictly pinned dependencies (and no project or code changes).
rye - a Hassle-Free Python Experience
pip - The Python package installer
zsh-defer - Deferred execution of Zsh commands
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows