Poetry
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Poetry | pipx | |
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377 | 38 | |
29,397 | 8,717 | |
2.3% | 5.6% | |
9.6 | 9.2 | |
1 day ago | 7 days ago | |
Python | Python | |
MIT License | MIT License |
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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.
Poetry
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Understanding Dependencies in Programming
You can manage dependencies in Python with the package manager pip, which comes pre-installed with Python. Pip allows you to install and uninstall Python packages, and it uses a requirements.txt file to keep track of which packages your project depends on. However, pip does not have robust dependency resolution features or isolate dependencies for different projects; this is where tools like pipenv and poetry come in. These tools create a virtual environment for each project, separating the project's dependencies from the system-wide Python environment and other projects.
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Implementing semantic image search with Amazon Titan and Supabase Vector
Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:
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From Kotlin Scripting to Python
Poetry
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How to Enhance Content with Semantify
The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:
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Uv: Python Packaging in Rust
Has anyone else been paying attention to how hilariously hard it is to package PyTorch in poetry?
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Boring Python: dependency management (2022)
Based on this comment 5 days ago[0], it's working? I'm not sure didn't dig in too far but based on that comment it seems fair to say that it's not fully Poetry's fault because torch removed hashes (which poetry needs to be effective) for a while only recently adding it back in.
Not sure where I would stand if I fully investigated it tho.
[0] https://github.com/python-poetry/poetry/issues/6409#issuecom...
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Fun with Avatars: Crafting the core engine | Part. 1
We will be running this project in Python 3.10 on Mac/Linux, and we will use Poetry to manage our dependencies. Later, we will bundle our app into a container using docker for deployment.
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Python Packaging, One Year Later: A Look Back at 2023 in Python Packaging
Here are the two main packaging issues I run into, specifically when using Poetry:
1) Lack of support for building extension modules (as mentioned by the article). There is a workaround using an undocumented feature [0], which I've tried, but ultimately decided it was not the right approach. I still use Poetry, but build the extension as a separate step in CI, rather than kludging it into Poetry.
2) Lack of support for offline installs [1], e.g. being able to download the dependencies, copy them to another machine, and perform the install from the downloaded dependencies (similar to using "pip --no-index --find-links=."). Again, you can work around this (by using "poetry export --with-credentials" and "pip download" for fetching the dependencies, then firing up pypiserver [2] to run a local PyPI server on the offline machine), but ideally this would all be a first class feature of Poetry, similar to how it is in pip.
I don't have the capacity to create Pull Requests for addressing these issues with Poetry, and I'm very grateful for the maintainers and those who do contribute. Instead, on the linked issues I share my notes on the matter, in the hope that it may at least help others and potentially get us closer to a solution.
Regardless, I'm sticking with Poetry for now. Though to be fair, the only other Python packaging tools I've used extensively are Pipenv and pip/setuptools. It's time consuming to thoroughly try out these other packaging tools, and is generally lower priority than developing features/fixing bugs, so it's helpful to read about the author's experience with these other tools, such as PDM and Hatch.
[0] https://github.com/python-poetry/poetry/issues/2740
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Introducing Flama for Robust Machine Learning APIs
We believe that poetry is currently the best tool for this purpose, besides of being the most popular one at the moment. This is why we will use poetry to manage the dependencies of our project throughout this series of posts. Poetry allows you to declare the libraries your project depends on, and it will manage (install/update) them for you. Poetry also allows you to package your project into a distributable format and publish it to a repository, such as PyPI. We strongly recommend you to learn more about this tool by reading the official documentation.
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How do you resolve dependency conflicts?
I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github
pipx
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Keep your AWS CLI config fresh with Cog
Use pipx to install Cog and my aws-sso-config-builder tool in the same environment:
- pipx
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Implementing Quality Checks In Your Git Workflow With Hooks and pre-commit
Given how useful pre-commit is across projects I generally recommend installing via pip install --user, making it part of a tooling virtual environment, or using pipx:
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pipx VS instld - a user suggested alternative
2 projects | 9 Dec 2023
- Pipx – Install and Run Python Applications in Isolated Environments
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Packaging a self contained CLI application for any environment?
I would recommend going with PipX. You toss in a setup.py file, put your project on github, and then anyone on any OS can pipx install your project. It's a glorious thing. The only thing they need is 1) some supported version of Python installed, 2) pipx installed. They can even get updates by calling pipx upgrade.
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Some confusion with system version and pyenv
See https://github.com/pypa/pipx/issues/278
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List of software package management systems
Good overview. There are quite a few on there I was not aware of. That said, I am not sure the organizational schema makes a tone of sense. I would assume most users that come across this would be looking for a package manager for a specific platform and then weighing the options of binary/source/etc., instead of the other way around.
Also, pipx (https://github.com/pypa/pipx) would be a good addition to the list. I'd add it but I'm not sure where it would go. Maybe every section? It's cross platform and handles both binary and source based app distributions.
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After using Python for over 2 years I am still really confused about all of the installation stuff and virtual environments
Pip is pretty simple and useful for me - you have your own environment for every script/program, requirements.txt is simple to understand too... It's kinda good solution for regular users... For more complex projects we have Poetry, PipX, that was inspired by NPM(x), I think...
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Apple Unveils MacBook Pro Featuring M2 Pro and M2 Max
What benefit would joining your cult bestow upon me that brew does not already?
My brew list is intentionally very short and my faffing about desire is limited.
Generally I use brew to pull in asdf (https://github.com/asdf-vm/asdf) to install programming languages/tooling, it works flawlessly.
I use Pipx (https://github.com/pypa/pipx) to install python thingies (such as yt-dlp) as a cli. Go and Rust handle binaries in their languages beautifully and without issues.
What are some alternatives?
Pipenv - Python Development Workflow for Humans.
opstrat - Option visualization python package
PDM - A modern Python package and dependency manager supporting the latest PEP standards
Lean and Mean Docker containers - Slim(toolkit): Don't change anything in your container image and minify it by up to 30x (and for compiled languages even more) making it secure too! (free and open source)
hatch - Modern, extensible Python project management
dust - A more intuitive version of du in rust
pyenv - Simple Python version management
private-pypi - private pypi server
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
Pyjion
virtualenv - Virtual Python Environment builder
translate-shell - :speech_balloon: Command-line translator using Google Translate, Bing Translator, Yandex.Translate, etc.