bokeh
Interactive plots and applications in the browser from Python
Decision gist · record as of 2026-08-14
Yes. Bokeh is a mature, actively maintained library with no known vulnerabilities, low install friction, and broad applicability across data science, finance, healthcare, and research. Its permissive license and institutional backing make it a reliable choice for interactive visualization projects. Install it if you need browser-based interactivity.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- Installation is straightforward with low friction; the package is actively maintained with a recent release and strong community backing through NumFOCUS sponsorship.
License · maintenance · safety
BSD-3-Clause (permissive) — BSD-3-Clause is a permissive license that allows commercial and private use with minimal restrictions, making it suitable for most projects.
last release 2026-07-25 (20 days) · last repo commit 2026-08-14 · 20,431 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 12,119,700 downloads/mo, #1,340 on PyPI
Alternatives
Verify before relying
pip install bokeh
from bokeh.plotting import figure, show
plot = figure(title="Example")
plot.line([1, 2], [3, 5])
show(plot)- Whether narwhals is used as a dataframe abstraction layer or for a specific feature.
- Performance characteristics on very large datasets and typical latency expectations.
- Whether the package supports real-time streaming updates or requires data to be pre-loaded.
What it is and what it does
Bokeh is a Python library for creating interactive, browser-based visualizations. It generates standalone HTML files or integrates with web frameworks to deliver plots and dashboards that respond to user interaction—panning, zooming, selection, and hover tooltips—without requiring JavaScript knowledge. The library handles both static plots and streaming data, making it suitable for exploratory analysis, real-time monitoring, and embedded applications.
The package depends on Jinja2 for templating, NumPy and contourpy for numerical operations, Pillow for image handling, PyYAML for configuration, Tornado for web serving, and xyzservices for map tile integration. It targets modern Python versions and is maintained as a production-stable project with active development and institutional support.
Use it for
- Build interactive dashboards for real-time data monitoring and business intelligence applications.
- Create exploratory data analysis tools where users can interact with plots to zoom, pan, and select subsets.
- Embed interactive visualizations in web applications using Tornado or other Python web frameworks.
- Generate standalone HTML reports with interactive plots that can be shared without requiring a server.
- Visualize large datasets with linked plots and cross-filtering for multi-dimensional analysis.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Bokeh is a mature, actively maintained library with no known vulnerabilities, low install friction, and broad applicability across data science, finance, healthcare, and research. Its permissive license and institutional backing make it a reliable choice for interactive visualization projects. Install it if you need browser-based interactivity.
Install
bokeh on PyPI
Before you install
Installation is straightforward with low friction; the package is actively maintained with a recent release and strong community backing through NumFOCUS sponsorship.
Requires Python 3.10 or later.
License in practice
BSD-3-Clause is a permissive license that allows commercial and private use with minimal restrictions, making it suitable for most projects.
Quickstart
pip install bokeh
from bokeh.plotting import figure, show
plot = figure(title="Example")
plot.line([1, 2], [3, 5])
show(plot)Verify before relying
- Whether narwhals is used as a dataframe abstraction layer or for a specific feature.
- Performance characteristics on very large datasets and typical latency expectations.
- Whether the package supports real-time streaming updates or requires data to be pre-loaded.
Package facts
| License | BSD-3-Clause permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 9 packagesJinja2contourpynarwhalsnumpypackagingpillowPyYAMLtornadoxyzservices |
| Maintenance | Actively maintained 20 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 12,119,700 / month, #1,340 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: End Users/DesktopIntended Audience :: Financial and Insurance IndustryIntended Audience :: Healthcare IndustryIntended Audience :: Information TechnologyIntended Audience :: Legal IndustryIntended Audience :: Other AudienceIntended Audience :: Science/ResearchProgramming Language :: JavaScriptProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3 :: OnlyProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Office/BusinessTopic :: Office/Business :: FinancialTopic :: Scientific/EngineeringTopic :: Scientific/Engineering :: Information AnalysisTopic :: Scientific/Engineering :: MathematicsTopic :: Scientific/Engineering :: VisualizationTopic :: Utilities |
Evidence: bokeh-3.9.2-py3-none-any.whl
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