npm VS Poetry

The fact that JSON doesn't support comments is so annoying, and I always thought that Douglas Crockford's rationale for this basically made no sense ("They can be misused!" - like, so what, nearly anything can be misused. So without support for comments e.g. in package.json files I have to do even worse hacky workaround bullshit like "__some_field_comment": "this is my comment"). There is of course jsonc and JSON5 but the fact that it's not supported everywhere means 10 years later we still can't write comments in package.json (there is https://github.com/npm/npm/issues/4482 and about a million related issues).

Things like the sparkline charts on npmjs (e.g. https://www.npmjs.com/package/npm ) are interactive SVGs. I think they're pretty common for data visualizations of all kinds

I actually did a POC 7 years ago about this - https://github.com/tanepiper/steal-ur-stuff

It was reported to npm at the time, but they chose to ignore it - https://github.com/npm/npm/issues/17724

Every time this pops up, I'm reminded of the day that the NPM registry started returning 418 responses.

I remember being at a training course that day and my manager asking me what we could do to fix it because our CI was failing to pull dependencies from NPM.

Trying to explain that NPM was returning a status code intended as an April Fools joke and which was never meant to see the light of production was quite difficult

https://github.com/npm/npm/issues/20791

I should really get around to how I discovered this 6 years ago and still nothing done about it

Whenever something like this comes up I usually have to tap the sign (and the original report)

NPM is not "Node Package Manager". https://www.npmjs.com/package/npm

> which can be overriden with env setting

Support for this is not great. Lots of packages still don't support this properly. My experience matches the 2015 comment https://github.com/npm/npm/issues/775#issuecomment-71294085

> Not sure why "symlinks" would be involved.

If you make your node_modules a symlink, multiple packages will fail. Even if you're not interested in doing that, others are.

> What NPM does is leaps and bounds ahead

Unless you change your node / gyp version. It doesn't really have a concept of runtime version. You can restrict it, but not have two concurrent versions if they conflict.

[email protected] was released in May 2017 and it seems to address many of the issues that Yarn aims to solve. Do keep an eye on it!

I think it's had been supposed to do that since forever. Apart from some bug in npm 5.3. Are you sure your package-lock versions actually conform to the semver ranges in your package.json?

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