django-rest-framework VS warehouse

- 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.

pip install PackageName: installs a package (you can browse the available packages in the Python Package Index)

python3 -m pip install \ --trusted-host test.pypi.org --trusted-host test-files.pythonhosted.org \ --index-url https://test.pypi.org/simple/ \ --extra-index-url https://pypi.org/simple/ \ piper_whistle==$(python3 -m src.piper_whistle.version)

In my experience so far, I can use a vast amount of the Python Standard Library to build Wasm-powered serverless applications. The caveat I currently understand is that Python’s implementation of TCP and UDP sockets, as well as Python libraries that use threads, processes, and signal handling behind the scenes, will not compile to Wasm. It is worth noting that a similar caveat exists with libraries that I find on The Python Package Index (PyPI) site. While these caveats might limit what can be compiled to Wasm, there are still a ton of extremely powerful libraries to leverage.

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.

From there, I needed to learn a bit about PyPi or Python Package Index, which is the home for all the wonderful packages that you know if you have ever run the handy pip install command. PyPi has a pretty quick and easy onboarding, which requires a secured account be created and, for the purposes of submitting packages from CLI, an API token be generated. This can be done in your PyPi profile. Once logg just navigate to https://pypi.org/manage/account/ and scroll down to the API tokens section. Click “Add Token” and follow the few steps to generate an API token which is your access point to uploading packages. With all this in place, I was able to use twine to handle the package upload. First I needed to install twine, again as simple as pip install twine. In order for twine to access my API token during the package upload process, it needed to read it from .pypirc file that contains the token info. For some that file may exist already, for me I was required to create it. Working in windows I simply used a text editor to create it in my home user directory ($HOME/.pypirc). The file contents had a TOML like format looked like this:

I have published the package to Python Package Index, commonly called PyPi, and in this post, I'll be sharing the steps I had to follow in the process.

Register at PyPI.org

According to the stats on the original link, there are over 25,000 identified secret ids/keys/tokens in the data. And it looks like that's just identifiable secrets, e.g. "Google API Keys" that I'm guessing are identifiable because they have a specific pattern, and may be missing other secrets that use less recognizable patterns.

I mean, sure, compared to the 478,876 Projects claimed on https://pypi.org/, that's a pretty small minority. On the other hand, I'd guess a many Python packages don't use these particular services, or even need to connect to a remote service at all, so the area for this class of mistake should be even smaller.

And mistakes do happen, but that's a pretty big thing to miss if you are knowingly publishing your code with the expectation other people will be reading it.

PyPi package

Does pypi.org display the Union of all keywords, the keywords of the most recent release, the keywords of the first release or some other weird combination like the intersection?