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?
Thanks! we found script-like frameworks like Streamlit are nice for small apps, but hard to reason about for larger apps. We went with a declarative approach more similar to React.
FastAPI has been working well for us, but we're not strongly coupled to it - in the future it would be easy to swap it out if needed.
Right now Reflex is meant for full-stack apps, but portability is something people have asked us for.
We're working on making Reflex work in different environments like Jupyter notebooks, and we're also exploring using Reflex for widgets [1] that can be embedded in pre-existing apps, so you can add interactive Python elements easily without rewriting your whole app.
We need to compile down to React/HTML in the end as it's the only way to render a webpage. By "pure Python" we meant from the developer's perspective they won't have to touch React or Javascript.
We only use React for the UI layer and to send events. Since all the state/logic is kept in Python you won't see Javascript errors during runtime, and debugging can mostly be done in Python land.
We want to support any UI feature that you can build with React/NextJS. We will expand our core to include components like rich text inputs but we also have a way to wrap any React library so you're not locked into the components we provide: https://pynecone.io/docs/advanced-guide/wrapping-react
Keeping the state on the server allows us to run arbitrary Python code and libraries in our event handlers that update the state. Currently only the ui is compiled to React but the logic stays in Python.
We’re working to offload more logic to the client in the for purely UI operations like you mention, and in the future want to leverage wasm once it’s more mature.
Yeah we’re only hosting on a single region at the moment so there can be latency depending on your location. We’re working on using edge computing to speed this up.
Cofounder of Pynecone here - thanks for the feedback. We’re prioritizing improving our docs and example apps in the upcoming weeks and will have a ChatGPT clone example. Definitely want to improve the onboarding experience and showcase these more complex use cases.
We use Websockets for state interactions, so the latency may depend on your internet connection + distance to server. We will improve this in the future by leveraging more edge computing and WebAssembly to execute closer to / on the client.
The ORM is a wrapper around SQLAlchemy, so only SQL databases for now. But since everything is in Python, you can still connect to any other database/service like you normally would.
I'll look why the search doesn't bring it up - see our event chain example here for how we do async event handlers: https://pynecone.io/docs/state/events
Only the frontend is compiled to JS/React. All the logic and state updates stay in Python and are run on the server, so we don't have to transpile arbitrary Python.
Our goal is for the user to never have to see JS. We try to catch most errors in Python during compile time. We're also not trying to reinvent things like CSS styles, just make them accessible in Python.
We use the `cloudpickle` library which supports most data types. We found the state size doesn't impact performance too much - our main website's state is quite large but the Redis loads stay fast.
Source code here: https://github.com/picklelo/webcritic