pdoc VS Poetry

You can also use doc-strings to generate automated documentation for your code using a library like pdoc. Consider the following example from Stack-Scraper and the corresponding documentation generated using pdoc library.

I’ve used sphinx extensively and though it is one of the standards and does a ton, I do not like or recommend it. Personally, I realllly like pdoc for its simplicity. Do not confused pdoc with pdoc3

RE browser vs reading the code: sounds like you have a nicer setup than my neovim setup. Although I think my first point still holds unless CLion handles that case too.

With respect to the rest of your comment, indeed, those are issues. Although I think I take issue with you pinning this on rustdoc. I actually think it's a dance between documentation presentation (so, rustdoc), API design and familiarity with the language.

I've long said that rustdoc makes unknown unknowns difficult to discover, and this is particularly painful for folks new to Rust. Because you don't really know what to look for yet. And writing docs is a difficult exercise in perspective taking, where you need to balance what you think others know. If you assume they know too little, it's not hard to end up writing too much and adding a fair bit of noise. With that said, I agree that "too little docs" is a far more common problem than "too many docs."

But yeah, your experience is a perfect example of what I mean when I say "generics complicate APIs." They introduce indirection everywhere, and I'm not sure how much rustdoc can really help with that. You might be right that maybe there are some visualizations that can be added, but like you, I've always seen those as gimmicks in other tools that are rarely useful. IMO, a heavily generic API really requires the crate author to write more prose about how their APIs are intended to be used with lots of concrete examples.

The interesting bit here is that I've personally found the documentation experience in Rust to be far far better than any other ecosystem. All the way from writing docs up to consuming them. I've sampled many different ecosystems (C, C++, Haskell, Python, Go to name some) and other than maybe Go, I thought the doc experience was really just not great in any of them. Python specifically seems to be a case where I tend to see a lot of variance in opinion. I hated Sphinx so much, for example, that I built an alternative.[1] I also just generally dislike the output that Sphinx produces. I find that it lacks structure, and I've always had a hard time navigating my way through Python library docs.

[1]: https://github.com/mitmproxy/pdoc

Anyway, this is all my opinion. And a lot of it is based on reflecting on my own experience. I have no idea how well it generalizes. I have given this topic a lot of thought though, and have even written documentation generators for other ecosystems because I thought the other choices were bad enough to warrant spending a few weeks on such a tool.

Documentation is now generated using pdoc https://pdoc.dev. Thanks Dliwk!! (I'll get it wired up to auto-update to a webpage soon).

There's a comprehensive README.md with installation and Quickstart information on GitHub, and reference documentation (auto generated by pdoc) on GitHub Pages.

Our main docs are built with Hugo (https://github.com/mitmproxy/mitmproxy/tree/main/docs). For our API docs we use pdoc (https://pdoc.dev), which integrates well with most static site generators. pdoc is also maintained by us. :)

PEP 257 and a few others define "docstrings". Leverage them to make full use of autodoc tools. pdoc is a pretty fun tool that "just works". Build good habits from the start. Projects that have great documentation are just more attractive to me. If I come across a project that seems to do what I need, but has crappy documentation, I keep looking.

Hi HN! Some of you may remember @BurntSushi's pdoc tool, a lightweight alternative to Sphinx. We're a bit in an unfortunate situation with a hostile work assuming our name [1], but I figured that we shouldn't give in and continue the legacy of that tool. Long story short, we have just published a major new "modern Python 3" release, which hopefully makes pdoc a really compelling option again. :-)

[1] https://github.com/mitmproxy/pdoc#pdoc-vs-pdoc3

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