reflex VS reflex-examples

Hey thanks for the feedback. We're working on relaxing our dependencies [1] to make reflex more compatible. Do you remember what libraries you had the conflict with?

[1] https://github.com/reflex-dev/reflex/pull/2796

Thanks! Pue looks cool, thanks for sharing. I see some similarities to https://reflex.dev in terms of providing a declarative dom expression language with built-in conditionals and loop primitives.

In the dynamic world of web development, Python has emerged as a dominant force, especially in backend development – the primary focus of this blog post. Although it's worth mentioning that there are ongoing efforts to use Python for the frontend as well, like Reflex (previously known as Pynecone, they presumably had to change their name because of Pinecone vector database), which even garnered support from Y Combinator. Samuel Colvin (creator of Pydantic) is also working on FastUI (he literally just released the first version in December 2023).

They have a ready to use LLM chat App, which makes it more likely I will check it out.

https://github.com/reflex-dev/reflex

We will use Reflex to build this chatbot.

To learn more about Reflex, you can read here: https://reflex.dev/

Reflex is an open-source, full-stack Python framework that makes it easy to build and deploy web apps in minutes. You have most of the features of a frontend library like Reactjs and a backend framework like Django in one with ease in development and deployment. All while developing in a single language PYTHON.

Repo : https://github.com/reflex-dev/reflex

This article is based on the local_auth example on reflex_examples GitHub page: https://github.com/reflex-dev/reflex-examples/tree/main/local_auth

We're working on built-in auth components, but you can also write your own. See the twitter demo for an example.

Your counter source code link actually links to the clock source code instead of: https://github.com/pynecone-io/pynecone-examples/tree/main/counter

This demo app where we make a lightweight UI around Dalle-e showcases our framework's strengths. The entire code is around 60 lines in a single Python file for the entire frontend and backend. (This example just calls the OpenAI API, but you can just as easily call your own Python models instead)