Move From Low Code to Reflex
Architecture That Scales, Code That Stays Clean
Streamlit, Dash, and Gradio get you prototyping fast, but you hit walls — rerun model, callback spaghetti, no real-time, no production path. Reflex gives you declarative state, event-driven updates, and production-ready output from day one.
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Have been playing with Reflex since January and realized I should just say, from a fellow YC member: love the architecture decisions you guys are making!
Alex AtallahCo-founder & CEO, OpenSeaCompare
How You Benefit
With Reflex vs.
Streamlit, Dash, Gradio
Streamlit, Dash, and Gradio get you prototyping fast. Reflex lets you finish. Here's how Reflex compares to the leading low-code Python frameworks.
ReflexStreamlit, Dash, Gradio
Architecture and state management.
- Your app only updates the parts that changed — no unnecessary reruns, so it stays fast even with large data
- User sessions remember where they are — multi-step workflows, background tasks, and real-time updates all work without extra effort
- The event-driven model keeps your code clean and organized, even as your app gets more complex
- Streamlit reruns your entire script every time a user clicks anything, leading to memory leaks and slowdowns that make it unreliable for long-term use
- Dash works fine for small apps, but as they grow the logic gets spread across many separate callback functions with no native support for object-oriented state, making it hard to follow and maintain
- Gradio is built for ML model demos — it's not a general-purpose app framework
Real-time and interactivity.
- Changes on the server show up instantly in the browser — no refresh needed, no extra setup
- Live dashboards, real-time data feeds, and collaborative features just work out of the box
- Fully event-based — your app can react to specific user actions like edits, clicks, and selections as they happen
- Streamlit can't push updates to the user — nothing happens in the browser until the user clicks something to trigger a full script rerun
- Dash has no built-in way to push live updates — getting real-time data requires workarounds like constant polling or adding custom extensions
- Gradio only handles simple input-in, output-out interactions for ML models — it's not built for apps that need to respond to complex user actions
Code structure and maintainability.
- Clean Python class structure keeps your code organized and easy to follow, even as apps grow to multiple pages and features
- Real projects with complexity use roughly half the code compared to the same app built in Dash
- Teams that tried other Python frameworks found Reflex significantly cleaner to maintain and extend
- Dash scatters your logic across many separate callback functions that become harder to trace as the app grows
- Streamlit's simple script approach works at first but falls apart when you need complex page flows or shared state across views
- Gradio's simple interface definitions can't support complex multi-page app structures
Customization and UI components.
- No limits on what you can build — use any React component in pure Python with full control over styling and layout
- Complete design flexibility without ever leaving the Python ecosystem
- Most low-code Python frameworks offer very basic layout and styling options with little flexibility
- Lack of customization is one of the most commonly cited frustrations across low-code Python tools — building anything beyond the default look typically requires dropping into React, TypeScript, or JavaScript
Built-in functionality.
- Authentication, database management, background jobs, file uploads, and role-based access all come built in
- Everything you need to go from prototype to production without stitching together a patchwork of separate tools
- SSO and user management are included — no third-party libraries or workarounds needed
- Streamlit has no built-in auth, database access, or background processing — even simple things like a loading button require workarounds
- The Dash open-source package has no auth, no background tasks, and no database layer — each one needs a separate library
- Gradio is focused narrowly on ML demos and lacks general-purpose app features entirely
Deployment and the prototype-to-production gap.
- Compiles to a FastAPI backend with a React frontend on an async web server — production-ready and container-friendly from the start
- Fits into Git, pull requests, automated testing, and CI/CD from day one — no separate production rewrite needed
- What you build is what you ship — you're in production without having to rebuild
- All low-code tools are seen as prototyping tools — teams build a first version, then have to rebuild the real thing from scratch when it's time to ship to production
- Streamlit apps hit out-of-memory errors under load with even moderately large datasets, and its rerun model fundamentally limits production scalability
- Open-source Dash runs on Flask and requires manual infrastructure setup to scale
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Why Reflex Over
Streamlit, Dash, Gradio
Low-code Python frameworks get you prototyping fast. Reflex lets you finish. Declarative state, real-time updates, production-ready output from day one.
Architecture That Scales
Declarative state, event-driven updates, and reactive re-renders. Only affected components update — no full script reruns or callback spaghetti.
Real-Time Out of the Box
WebSocket sync means server changes show up instantly in the browser. Live dashboards and collaborative features work natively.
Clean, Maintainable Code
Python class-based state keeps logic organized. Real projects use roughly half the code compared to equivalent Dash apps.
Full Customization
Wrap any React component from Python. Complete design flexibility without leaving the Python ecosystem.
Production-Ready Built-Ins
Auth, ORM, database migrations, background jobs, and file uploads — everything you need to ship without stitching together libraries.
What You Build Is What You Ship
Compiles to FastAPI + React. Fits Git, CI/CD, and container deployment from day one. No prototype-to-production rewrite.
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