panel

What it is and what it does

Panel is a Python web application framework that lets you build interactive dashboards and data tools by combining widgets, plots, and tables into layouts without leaving Python. It sits on top of Param for parameter binding and integrates with visualization libraries like bokeh, Plotly, Matplotlib, and Altair. You write Python functions, bind them to interactive widgets, and Panel handles the reactivity and state management.

You can develop in Jupyter notebooks or standard editors and deploy the same code to multiple targets: as a web server using Tornado, Flask, Django, or FastAPI; as a client-side app via Pyodide or PyScript; as a notebook component; or as static HTML, PNG, or GIF exports. The framework relies on 15 runtime dependencies including bokeh, pandas, narwhals, markdown, and markdown-it-py, making it a comprehensive but heavyweight solution for data exploration and application delivery.

Use it for:

• Build interactive financial dashboards that react to user selections and display real-time data summaries
• Create exploratory data analysis tools in notebooks that can be converted to standalone web apps without code changes
• Deploy multi-page applications with complex interactivity and custom layouts to a web server for team collaboration
• Convert Jupyter notebooks to production-ready web applications using panel serve without rewriting logic
• Build client-side data apps that run entirely in the browser via Pyodide or PyScript for offline use

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Panel is a Python framework for building interactive data applications, dashboards, and web apps with widgets, plots, and tables that can be deployed as web services, notebooks, or static exports.

Yes. Panel is actively maintained, permissively licensed, and has low install friction. It is Production/Stable with strong community adoption (top 5000 PyPI packages, 3717238 monthly downloads). Install it if you need to turn Python data work into interactive web apps or dashboards without learning JavaScript or web frameworks. The 15 dependencies are a trade-off for batteries-included functionality; verify they fit your deployment model before committing.

Install

panel on PyPI

pip install panel

uv add panel

poetry add panel

Installing panel

Before you install

Low friction install via pip or conda. Active maintenance with a recent release 74 days ago and 5730 GitHub stars. Supports Python 3.10 through 3.14 with 15 runtime dependencies from the PyData ecosystem.

License in practice

BSD-licensed under permissive terms, allowing commercial use, modification, and distribution with minimal restrictions—suitable for proprietary applications.

Quickstart

pip install panel

import panel as pn
from bokeh.plotting import figure

pn.extension()
slider = pn.widgets.IntSlider(value=5, start=1, end=10)

def model(n):
    return "⭐" * n

interactive = pn.bind(model, n=slider)
layout = pn.Column(slider, interactive)
layout.servable()

Requires Python 3.10 or later. Deployment to web servers requires Tornado, Flask, Django, or FastAPI.

Verify before relying

• Performance characteristics for large datasets or high-concurrency web deployments
• Maturity and stability of panel-material-ui relative to core Panel functionality
• Browser compatibility and JavaScript runtime requirements for Pyodide or PyScript deployments

Package facts

Evidence: panel-1.9.3-py3-none-any.whl

Tags

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