chrono VS Poetry

The problem is that this effects higher languages too, because they often build on libc. And on some OSes, they don't have a choice, because the system call interface is unstable and/or undocumented).

For example in rust, multiple time libraries were found to be unsound if `std::env::set_env` was ever called from a multi-threaded program. See:

https://github.com/time-rs/time/issues/293 and https://github.com/chronotope/chrono/issues/499

https://github.com/rust-lang/rust/issues/27970

https://github.com/rust-lang/rust/issues/90308

> I think library authors should be more relentless and break compatibility every few years. We just need some conventions to not do so very often.

I indeed did this years ago---I'm the original author of Chrono [1]---and it wasn't well received [2] [3] [4]. To be fair, I knew it was a clear violation of semantic versioning but I didn't see any point of obeying that until we've reached 1.0 so I went ahead. People complained a lot and I had to yank the problematic release. By then I realized many enough people religiously expect semantic versioning (for good reasons though) and it's wiser to avoid useless conflict.

[1] https://github.com/chronotope/chrono

[2] https://github.com/chronotope/chrono/issues/146#issuecomment...

[3] https://github.com/chronotope/chrono/issues/156

[4] https://github.com/chronotope/chrono/blob/main/CHANGELOG.md#...

On that note, it would also be good to configure cargo-deny so that a CI pipeline and any maintainer can easily audit the current dependency versions. Sometimes CVEs require a new major semver (looking at you, time 0.1.x and thus chrono 0.4.x), so it's not enough to rely on people installing the tool with semver-compatible updates. Automatically auditing dependencies is really important, and given how easy cargo-deny makes it, I don't think many projects have any excuse not to configure it.

The example has been randomly taken from the [Chrono][https://github.com/chronotope/chrono/blob/main/src/offset/utc.rs] crate.

libc isn't "just a wrapper". Is a massive legacy codebase filled with hacks, UBs and bugs: https://github.com/chronotope/chrono/issues/499

Would love to have people test this, you can leave feedback here: https://github.com/chronotope/chrono/issues/674.

Security issues? I'm looking at the open issues, but haven't noticed any that seem to be security related (no security related labels either). What am I missing here?

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