Bokeh
Python library for interactive data visualization
Bokeh is a Python library for building interactive plots, dashboards, and data applications that run in modern web browsers. It addresses the need to move from static charts to browser-based visualizations without requiring JavaScript, covering workflows from exploratory analysis in Jupyter to published web pages and live Python applications.
Bokeh provides high-level plotting through `bokeh.plotting`, alongside lower-level layouts, widgets, annotations, models, themes, and extensions for custom applications. Built-in interaction includes pan, zoom, hover, selection, linking, filtering, and editable data. It supports streaming and patching data without replacing the full data source, with WebGL acceleration available for supported glyphs. Plots can be displayed in Jupyter and JupyterLab, saved as standalone HTML, embedded in existing pages, or run through the Bokeh server. It can also be mounted in ASGI applications such as FastAPI, Starlette, and Django, served with Uvicorn or Hypercorn.
Bokeh is aimed at Python developers, data scientists, and analysts working with interactive visualizations and browser-based applications. It is open source under a BSD license and is a fiscally sponsored NumFOCUS project.
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