juniper VS fastapi

juniper

GraphQL is also an option. https://github.com/graphql-rust/juniper

Juniper has plenty of popularity, so I guess it's Rust + graph DB that doesn't get much love then... :/

rusty-gql would not be able to release without async-graphql and juniper.

I'm looking for graphql server that can do queries and mutations over websocket, like subscriptions-transport-ws. Juniper and async-graphql both looks promising and async-graphql at least uses wording Subscriptions (WebSocket transport) in features but i couldn't find much more or any examples about that from the docs or repo.

We also don’t use Node anymore. We found Node in general to be incredibly slow, not to mention single threaded. Admittedly, we did use Node (Apollo) though up until about two years ago. Now, depending on use-case, we will use Go (https://github.com/99designs/gqlgen) or Rust (https://github.com/graphql-rust/juniper). Both outperform a Node gateway but significant margins.

(example from the docs async-graphql https://async-graphql.github.io/async-graphql/en/subscription.html, juniper: https://github.com/graphql-rust/juniper/blob/master/docs/book/content/advanced/subscriptions.md)

It has been an interesting exercise developing this wrapper component. The fact that it seamlessly integrates with the FastAPI framework is just a bonus for me; I didn't plan for it since I hadn't learned FastAPI at the time. I hope you find this post useful. Thank you for reading, and stay safe as always.

FastAPI is a modern, high-performance web framework for building APIs with Python, based on standard Python type hints.

In this tutorial, I will demonstrate how to use Burr, an open source framework (disclosure: I helped create it), using simple OpenAI client calls to GPT4, and FastAPI to create a custom email assistant agent. We’ll describe the challenge one faces and then how you can solve for them. For the application frontend we provide a reference implementation but won’t dive into details for it.

That’s when I found FastAPI.

FastAPI & Uvicorn

Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696

An API application framework (such as FastAPI)

It’s been my experience that async Python frameworks tend to turn IO bound problems into CPU bound problems with a high enough request rate, because due to their nature they act as unbounded queues.

This ends up made worse if you’re using sync routes.

If you’re constrained on a resource such as a database connection pool, your framework will continue to pull http requests off the wire that a sane client will cancel and retry due to timeouts because it takes too long to get a connection out of the pool. Since there isn’t a straightforward way to cancel the execution of a route handler in every Python http framework I’ve seen exhibit this problem, the problem quickly snowballs.

This is an issue with fastapi, too- https://github.com/tiangolo/fastapi/issues/5759

Fast API.