Panel
Open SourceThe powerful data exploration & web app framework for Python.
Published 29 May 2026 · Last updated 27 September 2026
Scores
Popularity1/5
Mostly used within the HoloViz and PyData ecosystem; low general awareness outside that community.
Learning Curve4/5
Reactive and Param-based APIs offer power but multiple abstraction levels take time to navigate.
Flexibility5/5
HoloViz ecosystem combines Bokeh, Param, and Holoviews for complex, highly custom dashboards.
Performance4/5
Bokeh-backed rendering is efficient; scales well with large Holoviews datasets.
Portability3/5
HoloViz ecosystem has some transferability; deeper Param and Bokeh usage creates dependency.
About Panel
Panel is an open-source Python library for building interactive dashboards, data exploration tools, and web apps, developed as part of the HoloViz ecosystem with support from Anaconda. It is aimed at scientists, analysts, and engineers who already work in notebooks and want to turn that work into shareable apps.
Unlike Streamlit, which re-runs the whole script on every interaction, Panel offers a reactive API (functions bound to widgets with pn.bind) and a lower-level callback API, so developers control exactly what updates. Its Param library adds declarative, typed parameters that drive widgets and state, which suits larger apps built as classes.
Panel's widest advantage is visualisation support: it renders plots from Bokeh, Matplotlib, Plotly, Altair and Vega, HoloViews, hvPlot, and more, plus dataframes, maps, video, and custom components, and interoperates with the rest of HoloViz (HoloViews, GeoViews, Datashader for very large data). Streaming updates support live dashboards, and templates give apps a finished layout.
The same code runs in a Jupyter notebook, as a standalone server (panel serve), inside FastAPI or Django, or in the browser with no server at all by converting the app to WebAssembly through Pyodide. Panel is free under the BSD licence. It has a smaller community than Streamlit or Dash, more concepts to learn, and a plainer default look than Streamlit or Gradio.
Key Features
- Reactive (pn.bind) and callback APIs for interactivity
- Supports Bokeh, Matplotlib, Plotly, Altair, Vega, HoloViews, and hvPlot
- Runs in Jupyter notebooks and as standalone servers
- Param-based declarative parameters for app state
- Templates for finished dashboard layouts
- WebAssembly export via Pyodide for serverless deployment
- Streaming data support for live dashboards
- Interoperates with HoloViews, GeoViews, and Datashader
Pros
- Broadest plotting-library support of any Python dashboard framework
- Works natively in Jupyter, so exploration and app share code
- Finer control over updates than Streamlit's re-run model
- WebAssembly export allows server-free static dashboards
- Strong in scientific and research communities
Cons
- Smaller community and ecosystem than Streamlit or Dash
- More concepts to learn (Param, reactive and callback APIs)
- Plainer default look than Streamlit or Gradio
- Fewer community templates and extensions
Panel Pricing
Open SourceTech Stacks with Panel
Python Dashboard Starter
ProjectEverything a beginner data scientist needs: Python + pandas for analysis, Streamlit (or Panel or Dash) for interactive apps, and PostgreSQL for structured data storage.
Tools Related to Panel
Works well with Panel(2)
Panel's plotting components consume NumPy arrays directly, enabling high-performance data visualization dashboards with HoloViews.
Panel's DataFrame and tabular widgets wrap Pandas DataFrames for interactive dashboarding with minimal boilerplate.
Integrates with Panel(1)
Hugging Face publishes an official Docker Space template for Panel, so a Panel app deploys via the Docker SDK rather than a dedicated native runtime.
Built on (1)
Panel is a Python framework for creating interactive dashboards and apps.
Alternatives to Panel(3)
Both Python dashboard frameworks; Panel supports more complex multi-page layouts and production dashboards, Streamlit is faster to prototype with.
Both more production-capable than Streamlit; Dash is built on React/Plotly, Panel supports multiple plotting libraries with more widget flexibility.
Gradio is ML demo-focused with typed UI widgets; Panel is a general dashboard framework — different primary audiences.