iplib3 VS Poetry

Instead of keeping all the code at the repository root, maybe consider a more traditional project structure. As far as examples go, I've got this for an executable, and I think this works for a more complex project.

What that means in practice, I have yet to figure out how to explain in the simplest way possible, but perhaps an example repository might help somewhat. The details more or less boil down to

First, some values simply never change. For example, my iplib3 has plenty of hard-coded constants set by the IPv4 and IPv6 specifications and there's no need to have those in some external config file because, again, unless the standard gets updated those are constant.

I haven't touched this codebase in a while (although I really should), but it serves as one of my better examples for object-oriented programming. It's reasonably large, yet meticulously linted: https://github.com/Diapolo10/iplib3

I don't have any projects using setuptools anymore so unfortunately I can't give an example for that, but if Poetry is fine then iplib3 will probably suffice. Focus on the imports and the project structure, and maybe pyproject.toml, everything else is just noise.

Well, my GitHub profile is part of my flair in this subreddit, feel free to dig around. My latest project was an attempt to port the ms JavaScript library to Python, and I think I did alright. Other things I can highlight would be my iplib3 package, a server implementation for the EguiValet messaging service, and finally I've got a fairly unfinished text colouring utility called escapyde.

And iplib3 could use some cleanup, such as redesigning the inheritance to add support for seamless conversion between all supported types. The documentation should also be written as right now there's basically nothing.

You could maybe take a look at my iplib3 project for some examples. Alternatively, the EguiValet server project should be fine too.

While I have a very recent project that would otherwise be a perfect example, it does something a bit unusual with imports so I'll instead use iplib3 as an example, even though I haven't had time to work on it lately.

The Pytest documentation does a much better job at explaining how this works in practice than I ever could. I don't have any super simple example repositories, but iplib3 might work: https://github.com/Diapolo10/iplib3/blob/main/tests/test_address.py

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.

Poetry provides packaging and dependency management for Python. If you haven't already, install poetry via pip:

Poetry

The Semantify repository provides an example Astro.js project. Ensure you have poetry installed, then build the project from the root of the repository:

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

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...

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.

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/

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.

I started using poetry. The problem is poetry will not install if there is dependency conflict and there is no way to ignore: github