Top Python Libraries to Turn Scripts into Stunning Web Apps
Explore a curated list of popular pure-Python libraries—including Streamlit, Gradio, Dash, Voila, and PyWebIO—that let you quickly transform data scripts into attractive, shareable web interfaces, complete with usage stats, recent updates, and visual examples.
Today I share several practical pure-Python packages for building visual interface services. When you have scripts you don’t want to share as code, these packages let you quickly create attractive interfaces as services for others. The list includes the latest update times and current star counts (statistics as of Friday).
Streamlit (23.3k ★, updated 2 hours ago)
Streamlit lets you turn data scripts into shareable web applications in minutes instead of weeks. It is completely free, open-source, and built on Python. After creating an app you can deploy, manage, and share it via Streamlit’s community cloud platform.
Gradio (13.9k ★, updated 1 hour ago)
Gradio is an open-source Python library for building machine-learning and data-science demos and web apps. With Gradio you can quickly create a beautiful UI around a model or workflow, allowing users to drag-and-drop images, paste text, record audio, and interact through a browser.
Dash (18.3k ★, updated 11 hours ago)
Dash is the most downloaded and trusted Python framework for building ML and data-science web applications. It is built on Plotly.js, React, and Flask, linking modern UI elements such as dropdowns, sliders, and graphs directly to your analysis code.
Voila (4.6k ★, updated 16 hours ago)
Voila is a Jupyter Notebook extension that converts notebooks into interactive web applications. It provides a simple interface so you can rapidly build data-visualization and machine-learning apps from notebooks.
PyWebIO (3.7k ★, updated 3 days ago)
PyWebIO is a Python library for building web applications. It offers a simple API that enables you to create interactive data-visualization and machine-learning apps directly in the browser.
All the above libraries can be explored on their respective GitHub repositories for more examples.
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