django-rest-framework VS Poetry

- Django Rest Framework has no async support? https://github.com/encode/django-rest-framework/issues/7260

A URL shortener is a service that transforms long and complex URLs into short, easily memorable ones. This tutorial guides you through creating a URL shortener using Django REST framework and Postgres, deploying it on Koyeb.

Now, I'm converting this app into a Vue-based SPA (still powered by Django). I'm using the Django REST Framework to build the API that the SPA will interact with. (I'll be using token-based auth, via django-rest-knox. ETA: I'll actually be using djangorestframework-simplejwt.)

For the backend, we chose Python, Django Rest Framework. On the frontend, React, Redux, Saga, Sass. Let’s start with the backend, which was managed by Yegor. He writes about the server part of the project himself.

With regard to JSON API aspects of Django, have you used https://www.django-rest-framework.org/ ? I find it to be very satisfactory.

django-rest-framework and the Fetch API, or

Django REST Framework (DRF) Django REST Framework is a famous, powerful, and flexible toolkit for building Web APIs in Django. It provides a set of reusable components and tools to simplify API development, including serialization, authentication, permissions, and view sets.

I wish Django would take async more seriously. This comment gives a pretty good overview of the current situation (some points are more valid than others): https://github.com/encode/django-rest-framework/discussions/...

The Python ecosystem is strange. Where other dev communities will embrace new ways of doing things faster than most people can keep up — the Python community needs to be pulled kicking and screaming into the light once ever decade or so. Python 2 to 3, ~10 years.

async/await has been in Python since 2015, it feels like it's going to be another 5 years before we see people taking async seriously in the big packages. Same problem we had during the 2/3 transition. No library support, no developer support.

Thanks for helping Steve to complete his REST API, he is now partying🥳. You can get more information on how to use the Django REST framework to best way read the documentation. There are many alternatives to the Django REST framework, you can give them a try if you want,

[Django Rest Framework](https://www.django-rest-framework.org/) has the very nice idea of a [ViewSet](https://www.django-rest-framework.org/api-guide/viewsets/#modelviewset) that allows really minimal code to perform all the basic CRUD actions on a model.

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