surface VS Poetry

I should have been more clear that my intent was to create/use a compiler for some kind of component syntax. There are lots of them, from Surface (Elixir), Blade (PHP/Laravel), and JSX (React, Vue, Etc)

There I learned more deeply about LiveView and Surface UI.

I think Surface is the ideal candidate for this. But it doesn’t have the components you are looking for but you can build anything with it. Hopefully, in future we can have set of headless components built using Surface 🤞

I have worked with Phoenix LiveView and Surface-UI for about a year; I would like to share some of the things I learned the hard way.

This is just an idea, but what about implementing using Phoenix.View(via use MyAppWeb, :view in your module)? Then assign I think has access to @conn. Then maybe work some magic to still allow Phoenix.Component syntax - but at this point, this is something I believe is a flow that might be in development. Try investigating / asking in Surface, because that is a lot more similar to React in its approach. In fact, I think Surface is where more aggressive features are pushed out, and ironed-out features get included into Phoenix. This was the case for Phoenix.Component, and HEEX.

This post is intended to get you started with surface provided components. I provided the original code and surface versions so you can compare the differences yourself without installing anything. After installing surface following the installation guide https://surface-ui.org/getting_started add surface_bulma in your mix.exs, this will allow you to use the table component.

I totally get the "Am I doing this the right way?" feeling, especially coming from Rails where everything was so opinionated and wanting to stay idiomatic.

Phoenix, while it does have opinions, is far less opinionated in the sense that it doesn't do it darndest to force you into certain conventions (for example, if your module name doesn't match your file name, Phoenix won't complain). Its generators do try and push you toward using good DDD practices (which is my opinion is a GREAT thing), but of course the generators are completely optional.

I don't have experience writing large LiveView apps but I would say that if you are familiar with any component-based frameworks (like React), I would take a look at SurfaceUI[1]. It simplifies a few "gotchas" in LiveView (though I would say they are very minor gotchas and worth learning about at some point) and gives you a component-rendering syntax more like React. Once you get going, you'll learn that LiveView doesn't have all the headaches that come with bigger React apps (like having to memoize functions or comparing props to avoid a re-render and whatnot). The recent release candidate for Phoenix 1.6 has made strides for a cleaner component syntax, but if you're having trouble with LiveView, Surface might bring some familiarity.

[1] https://github.com/surface-ui/surface

Have you seen Surface UI? Pretty cool. Collection of LiveView components. https://surface-ui.org/

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