cookiecutter-hypermodern-python
Poetry
cookiecutter-hypermodern-python | Poetry | |
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9 | 378 | |
1,727 | 29,631 | |
- | 1.6% | |
3.0 | 9.7 | |
1 day ago | 5 days ago | |
Python | Python | |
MIT License | MIT License |
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cookiecutter-hypermodern-python
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A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
Hypermodern Python Cookiecutter
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Boring Python: Code Quality
There is also a 'hypermodern' cookie cutter template for python projects - I've used it several times now and it works mostly out of the box:
https://github.com/cjolowicz/cookiecutter-hypermodern-python
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What's your default way setting up packages, testing, linting, and imports
See https://github.com/cjolowicz/cookiecutter-hypermodern-python for a template and https://cjolowicz.github.io/posts/hypermodern-python-01-setup/ for some background explanation.
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Do you need docs such as mkdocs or sphinx on private github projects?
I often see templates like COOKIETEMPLE or HYPERMODERN python add a separate directory called docs which either uses sphinx or mkdocs or readthedocs and has github actions for publishing docs.
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Here are 5 Python project starter templates after digging through 100s of them that I think are spot o
Vouching for https://github.com/cjolowicz/cookiecutter-hypermodern-python .
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I developed a template for starting new Python projects! Features: Poetry, GitHub CI/CD, MkDocs, publishing to PyPi/Artifactory, Pytest, Tox, black and isort.
Seems pretty similar to https://cookiecutter-hypermodern-python.readthedocs.io/
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Just created an open-source text adventure game engine. Still didn't upload to PyPi but will soon!
Check out Hypermodern python https://cjolowicz.github.io/posts/hypermodern-python-01-setup/ and the cookiecutter for it https://github.com/cjolowicz/cookiecutter-hypermodern-python
- [D] Going beyond average ML Engineer
- Are there any books or videos that describe how to organize large projects?
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?
https://github.com/python-poetry/poetry/issues/6409
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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
[1] https://github.com/python-poetry/poetry/issues/2184
[2] https://pypi.org/project/pypiserver/
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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
What are some alternatives?
py-healthchecks.io - A python client for healthchecks.io. Supports the management api and ping api
Pipenv - Python Development Workflow for Humans.
reorder-python-imports - Rewrites source to reorder python imports
PDM - A modern Python package and dependency manager supporting the latest PEP standards
awesome-pytest - A curated list of awesome pytest resources
hatch - Modern, extensible Python project management
Adventura
pyenv - Simple Python version management
mutmut - Mutation testing system
pip-tools - A set of tools to keep your pinned Python dependencies fresh.
pre-commit - A framework for managing and maintaining multi-language pre-commit hooks.
virtualenv - Virtual Python Environment builder