I’ve been using Streamlit for quick internal tools and dashboards, but a colleague introduced me to Reflex, so I’m trying it out as another way to build Python web apps.

What caught my attention is that Reflex is a full-stack Python framework for building web apps with UI, state, backend logic, data models, and deployment in one codebase. This is especially suitable for Python backend developers who seek to build more scalable and production-ready web apps.

What Reflex is

Reflex describes itself as an open-source Python framework for building full-stack web apps in pure Python. The docs highlight a few things that make it interesting:

  • You build the UI in Python
  • App state and event handlers live in Python
  • The framework supports backend logic and database integration
  • You can run locally and deploy from the same workflow

In practice, that makes Reflex feel closer to a Python-first app framework than a lightweight plotting/dashboard layer.

Quick start for developers

According to the Reflex docs, the simplest local setup is:

mkdir my-app
cd my-app
uv init
uv add reflex
uv run reflex init
uv run reflex run

A few notes:

  • Reflex recommends Python 3.10+
  • uv is the preferred project and package manager in the docs
  • reflex init creates a new app in the current directory
  • reflex run starts the app in development mode with hot reload

If you want logs while debugging, you can run:

uv run reflex run --loglevel debug

A tiny mental model

If you’re coming from Streamlit, the easiest way to think about Reflex is:

  • Streamlit: very fast for data apps and internal dashboards
  • Reflex: more structured for building app-like experiences with state, routing, and a larger component model

That means Reflex may take a bit more setup, but it may also scale better when the app starts feeling less like a notebook and more like a product.

Minimal example shape

A Reflex app usually has:

  • a state class
  • UI components
  • event handlers that update state
  • a page layout built from components

That separation is useful if you want your app to grow beyond a single script.

A simple beginner path is:

  1. Initialize the app with reflex init
  2. Open the generated project structure
  3. Find the page and state files
  4. Change one text label
  5. Add one button and one event handler
  6. Run reflex run and watch hot reload

That small loop is enough to understand the framework’s core model quickly.

Useful things to remember

  • reflex init creates the app scaffold
  • reflex run is the main local dev command
  • reflex deploy is the deployment path in the CLI
  • uv run keeps the workflow isolated and reproducible
  • The docs also provide markdown-friendly pages for AI tools through llms.txt

My first impression

Reflex looks promising if I want to build something more app-like than a Streamlit script, especially when I care about state, structure, and a cleaner separation between UI and logic.

I’m still early in the learning curve, but this seems worth a serious try for projects that may outgrow a quick dashboard.

Conclusion

For now, I’d describe Reflex as:

  • a good fit for Python-first product prototypes
  • a fuller app framework than Streamlit
  • a candidate for more structured internal tools and workflows

I’ll keep experimenting with it and see where it fits best.