maud VS Poetry

I would like to mention maud in this context:

https://github.com/lambda-fairy/maud

It is refreshingly different from other Rust templating libraries. It uses a proc-macro that compiles your HTML into Rust code. I also happen to use it in conjunction with HTMX and it works very well for me (at least in small projects).

You can also use HTML templating with crates like askama, tera and maud! This can be combined with the power of lightweight JavaScript libraries like htmx to speed up time to production. You can read more about this on our other article about using HTMX with Rust which you can find here.. We also collaborated with Stefan Baumgartner on an article for serving HTML with Askama!

I think a lot of us reach for Jinja-style templates so it feels a little more like we're writing bare HTML. But they're of course still just templates, and they need a build step before they become valid HTML.

So it's true, if you're willing to use a DSL embedded in your server language (like JSX), then you'll have the full language tooling available to you. And this probably isn't giving up much over language-specific templates.

A JSX-equivalent for the Rust server-side rendering world would probably be maud [1] or leptops [2].

[1] https://github.com/lambda-fairy/maud

[2] https://github.com/leptos-rs/leptos

Maud as a performant templating engine that will ensure your templates are well-formed at compile-time and, in effect, minify the generated HTML output by not passing through unnecessary whitespace.

Maud is a fast Slim/Haml-esque templating engine which will automatically minify your HTML at no extra charge because whitespace isn't significant in its syntax.

If you want to do backend development, give actix-web or Axum a try. If you need templating, take a look at Maud and if you want an ORM, take a look at SeaORM.

Personally, I'd recommend Maud if you don't need something with runtime reloading. Not only is it much faster, it implements a template language that is effectively the Rust-syntax equivalent to Slim or Haml using a procedural macro, so you get compile-time verification that your HTML output is well-formed.

For templating, Maud is fast, gives compile-time well-formedness guarantees, and outputs minified HTML by default as a side-effect of it being based on Rust macros. (It's of a similar design philosophy to Slim and Haml)

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