asgiref VS libcurl

uvicorn is an ASGI server that is recommended for running FastAPI applications.

I can't seem to be able to edit on mobile. OP either meant this, or its variation, such as async_to_sync and sync_to_async.

https://github.com/django/asgiref/blob/main/asgiref/sync.py

Ofc this is a python example. I have no idea how it works in different languages.

FastAPI is a popular Python Web framework that developers use to create RESTful APIs. It is based on Pydantic and Python-type hints that assist in the serialization, deserialization, and validation of data. In this tutorial, we will use FastAPI to create a simple "Hello World" application. We test and run the application locally. FastAPI requires a ASGI server to run the application production such as Uvicorn.

Look at the intended semantics [1], and then read the implementation [2]. Can you figure out if the implementation is correct? Can you infer the possible limitations of the approach at glance? Can your async library actually handle being called with multiple event loops installed?

I have zero trust in this code and I have been bitten by fixes to this library that introduced deadlocks in my own code.

[1] https://github.com/django/asgiref#synchronous-code--threads.

[2] https://github.com/django/asgiref/blob/main/asgiref/sync.py#...

Using WebSockets in Django utilizes asynchronous Python and Django channels, making the process straightforward. Using Django channels, you can create an ASGI server, and then create a group where users can send text messages to all the other users in the group in real time. This way, you are not communicating with a particular user, but with a group, multiple users can be added.

If you're interested in the architecture itself I recommend you start by making yourself familiar with [ASGI specification](https://asgi.readthedocs.io/en/latest/) .

We switched to using strong typing derived from the asgiref for typing ASGI types, which makes Starlite the strongest type framework of its kind.

Then, in another terminal window, we use curl to hit the endpoint:

Made a PR to curl in line with the above: https://github.com/curl/curl/pull/13338

Through the Fast Forward program, we give free services and support to open source projects and the nonprofits that support them. We support many of the world’s top programming languages (like Python, Rust, Ruby, and the wonderful Scratch), foundational technologies (cURL, the Linux kernel, Kubernetes, OpenStreetMap), and projects that make the internet better and more fun for everyone (Inkscape, Mastodon, Electronic Frontier Foundation, Terms of Service; Didn’t Read).

From the GitHub Issue itself, the maintainer did end up creating a PR to fix a related issue: https://github.com/curl/curl/issues/12983

Also, the bot filed another issue despite the complaints.

This Docker image is designed to support implementing Github Actions with Python. As of version 4.0.0., it starts with the official python docker image as the base which is a Debian OS. It specifically uses python:3-slim to keep the image size down for faster loading of Github Actions that use pyaction. On top of the base, we've installed curl gpg, git, and the GitHub CLI. We added curl and gpg because they are needed to install the GitHub CLI, and they may come in handy anyway (especially curl) when implementing a GitHub Action.