Streamlit vs. NiceGUI: Choose the Best Python Web Framework

Building web applications with Python doesn’t have to be complicated. Two frameworks make it especially easy: Streamlit and NiceGUI. Both let you create interactive web apps using mostly Python, but they shine in different scenarios.

Streamlit is optimized for data apps: dashboards, exploratory analysis, and ML demos. You write a Python script and Streamlit renders it as an app, with lots of built-in components for charts and tables.

NiceGUI is better suited for building application-style UIs (forms, admin panels, controls, monitoring tools). It’s built around a FastAPI server and a web UI layer, giving you more control over events, state, and backend capabilities.

Quick Comparison Overview

Feature	Streamlit	NiceGUI
Best For	Data apps, dashboards	General web apps, desktop-like UIs
Learning Curve	Very easy	Easy
Customization	Limited	High
Backend	Built-in	FastAPI
Real-time Updates	Automatic reruns	Event-driven

For more Python web frameworks, see: Best Python Web Frameworks

Key Differences Between Streamlit and NiceGUI

1. Primary Purpose

Streamlit: Built specifically for data science, ML, and analytics dashboards
NiceGUI: Designed for general-purpose web applications with desktop-like interfaces

2. Development Approach

Streamlit: Script-based - runs from top to bottom on each interaction (often called “reruns”)
NiceGUI: Event-driven - responds to specific user actions

3. Customization Level

Streamlit: Limited customization, focuses on rapid prototyping
NiceGUI: Highly customizable with direct access to HTML/CSS/JS when needed

4. Backend Architecture

Streamlit: Built-in server runtime with session/state patterns
NiceGUI: FastAPI-based backend with more explicit control over routing and integration

5. Real-time Features

Streamlit: Interaction triggers a script rerun; you manage state/caching to keep it responsive
NiceGUI: Event-driven updates; good fit for “live UI” patterns (monitoring/control panels)

6. Learning Curve

Streamlit: Extremely beginner-friendly, no web dev knowledge needed
NiceGUI: Slightly steeper but still accessible, benefits from web dev basics

7. Community & Resources

Streamlit: Large community, extensive documentation, Streamlit Cloud hosting
NiceGUI: Growing community, good documentation, self-hosting focused

8. License & Cost

Streamlit: Apache 2.0, free with Streamlit Community Cloud (with limitations)
NiceGUI: MIT License, completely free and open source

When to Choose Each Framework

Choose Streamlit if you need:

Data dashboards with charts, tables, and visualizations
ML model interfaces for demos and prototypes
Rapid development with minimal coding
Built-in data handling (CSV, JSON, databases)
Easy deployment on Streamlit Cloud

Example use cases:

Sales analytics dashboard
Machine learning model demo
Financial data explorer
Research data visualization

Choose NiceGUI if you need:

Desktop-like applications in the browser
Real-time interactions without page reloads
Custom UI components and layouts
Advanced backend features (authentication, APIs)
Full control over user experience

Example use cases:

Project management tools
IoT device controllers
Interactive forms and surveys
Real-time monitoring systems

Getting Started: Code Examples

Both frameworks are beginner-friendly, but Streamlit has a slight edge for absolute beginners.

Streamlit Example: Data Dashboard

import streamlit as st
import pandas as pd

st.title('Sales Dashboard')

data = pd.DataFrame({
    'Month': ['Jan', 'Feb', 'Mar', 'Apr'],
    'Sales': [100, 150, 120, 200],
})

month_filter = st.selectbox('Select Month', data['Month'])
filtered = data[data['Month'] == month_filter]

st.bar_chart(data.set_index('Month'))
st.write(f'Sales for {month_filter}: ${int(filtered["Sales"].iloc[0])}')

NiceGUI Example: Interactive Form

from nicegui import ui

def handle_submit():
    ui.notify(f'Hello {name.value}! You are {age.value} years old.')

ui.label('User Information Form')

with ui.row():
    name = ui.input('Name', placeholder='Enter your name')
    age = ui.number('Age', value=25, min=0, max=120)

ui.button('Submit', on_click=handle_submit)

ui.run()

Key Differences in the Code:

Streamlit: Linear, script-like flow - perfect for data workflows
NiceGUI: Component-based with explicit event handling - better for interactive apps

NiceGUI Advantages

Real-Time Interactions

Event/callback-driven UI updates
Good fit for monitoring, controls, and “app-like” UIs

FastAPI Integration

You can take advantage of FastAPI concepts (routing, dependencies, middleware) as your app grows
Useful when you need APIs alongside the UI, or want more control over auth and request handling

Note: “built-in authentication and user management” isn’t automatic in FastAPI itself. You typically implement auth using FastAPI patterns and libraries, then integrate it with your app.

Advanced Customization

More layout and component control than Streamlit
Can integrate with web concepts when needed (styling and custom behavior)

Development Experience

Good local dev workflow and straightforward self-hosting
Works well in containers when you need repeatable deployment

Flexibility

Natural fit for event-driven apps
Can integrate with existing Python services and libraries

Streamlit Advantages

Data Apps First

Excellent defaults for pandas DataFrames, charts, and common analytics workflows
Great for ML demos and internal dashboards

Ultra-Simple Development Model

Very low “web framework” overhead: write Python top-to-bottom
Easy to iterate quickly and share prototypes with teammates

Deployment Options

Streamlit Community Cloud is convenient for quick publishing
Also deployable to your own infrastructure (VPS, containers, etc.)

Data-Focused Widgets

Strong widget set for filters, inputs, and interactive exploration
Built-in caching and session state patterns help keep apps responsive

Strong Ecosystem

Large community, lots of examples and integrations

Making Your Choice: Decision Guide

Choose Streamlit if:

✅ You’re building data dashboards or ML demos
✅ You want rapid prototyping with minimal code
✅ You’re new to web development
✅ You need built-in data visualization
✅ You want easy deployment and sharing

Choose NiceGUI if:

✅ You need real-time interactions without page reloads
✅ You’re building general-purpose web apps
✅ You want desktop-like UI in the browser
✅ You need advanced backend features
✅ You want full customization control

Quick Start Resources

Streamlit:

NiceGUI:

Final Verdict

Both frameworks excel in their domains. Streamlit dominates data science applications with its simplicity and built-in data tools. NiceGUI shines for interactive web applications that need desktop-like functionality.

The best choice depends on your project requirements, not on which framework is “better” overall. Start with the one that matches your immediate needs - you can always explore the other later as your projects evolve.

Streamlit vs. NiceGUI: Choose the Best Python Web Framework

Table of Contents

Quick Comparison Overview