shelf VS Poetry

Shelf

To be honest, there's not much to it! It's a single-file add-on for the shelf package with about 100 lines of code, and the comment for the ProxyHandler class at the top sums up the shelf-proxy package pretty well:

The Dart Language Tour has all of this basic stuff but better, and when you're done, look at the shelf package on pub.dev if you want to get started on creating a server.

These are the best backend frameworks for Dart right now but you can use the shelf package if you want a slightly different approach

In this blog, I will talk about the benchmarks of Flask (Python), Express (JavaScript), Shelf (Dart), dart_frog (Dart) and Conduit (Dart), and my opinions on Dart on the server side.

Thats all what I found - https://github.com/dart-lang/shelf/issues/29 Looks like this is the most recent updated package, not very well know, which can handle cookies - https://pub.dev/packages/shelf\_secure\_cookie

There was a time, I want to start a new project and have to choose what technologies to use for the frontend and backend parts as well. Research gets me to Aqueduct and Shelf, both of them weren't looking actively developing and supported and that leads me to the idea to make my own small micro-framework like Echo for Golang or Bottle for Python. And it was easy to decide: I've had time and motivation :)

Dart Frog 🐸 es un framework web construido sobre Shelf inspirado por Next.JS, Remix y Express.

shelf

We are't using one of the frameworks for Dart on the backend (Conduit, Dart Frog) and instead built on top of shelf for both the projects we've used Dart on the backend for - one we went for a gRPC approach and the implemented a REST API.

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