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 only Python, but they excel in different areas.

Streamlit specializes in data science and machine learning apps. It transforms Python scripts into web applications automatically, with built-in support for charts, dataframes, and ML models. Perfect for dashboards and data visualization.

NiceGUI focuses on creating desktop-like web applications. Built on FastAPI with Vue.js frontend, it offers more control over UI components and interactions, making it ideal for general-purpose web apps.

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
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 backend with automatic session management
NiceGUI: FastAPI backend with full control over routing and authentication

5. Real-time Features

Streamlit: Page reloads on interaction (though cached for performance)
NiceGUI: True real-time updates without page reloads

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
import numpy as np

st.title('Sales Dashboard')

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

# Interactive elements
month_filter = st.selectbox('Select Month', data['Month'])
filtered_data = data[data['Month'] == month_filter]

# Display results
st.bar_chart(data.set_index('Month'))
st.write(f'Sales for {month_filter}: ${filtered_data["Sales"].values[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

No page reloads - instant UI updates
WebSocket-based communication for responsive apps
Perfect for live dashboards and monitoring tools

🛠️ FastAPI Backend

Built-in authentication and user management
RESTful API endpoints out of the box
OpenAPI documentation generation
Database integration and ORM support

🎨 Advanced Customization

Direct access to HTML, CSS, and JavaScript when needed
Custom components with Vue.js
Tailwind CSS for modern styling
3D visualization capabilities

📱 Modern UI Components

Rich component library (charts, tables, forms)
Mobile-responsive layouts
Drag-and-drop interfaces
File uploads and downloads

⚡ Development Experience

Hot reload during development
Lightweight and fast
Docker support for easy deployment
Works great for both web and desktop-like apps

🔧 Flexibility

Event-driven architecture
Multiple pages and routing
Background tasks and scheduling
Integration with existing Python libraries

Streamlit Advantages

📊 Data Science First

Built-in support for pandas, numpy, matplotlib
Native data visualization with charts and graphs
Seamless ML model integration (scikit-learn, TensorFlow, PyTorch)
Automatic data caching for performance

⚡ Ultra-Simple Development

Zero boilerplate code needed
Script-to-app in minutes
No HTML, CSS, or JavaScript required
Automatic layout and styling

🌐 Easy Deployment

Streamlit Community Cloud for free hosting
One-click deployment from GitHub
Built-in sharing and collaboration features
Handles scaling automatically

📈 Data-Focused Widgets

Interactive data tables with filtering/sorting
Built-in chart types (line, bar, scatter, maps)
File upload widgets for CSV, JSON, images
Form inputs optimized for data collection

🤝 Strong Ecosystem

Large, active community
Extensive documentation and tutorials
Component gallery and marketplace
Integration with popular data tools

🔄 Session State Management

Built-in state persistence across interactions
Caching decorators for expensive computations
Easy data pipeline management
Perfect for iterative data exploration

📱 Multi-Page Apps

Built-in navigation and routing
Sidebar and tab layouts
Mobile-responsive by default
Professional-looking dashboards out of the box

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.

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