jupyter-sphinx
Jupyter Sphinx Extensions
Decision gist · record as of 2026-08-14
Yes, if you maintain Sphinx documentation for a Jupyter-based project and want executable examples in your docs. The package is actively maintained, has low install friction, and solves a real problem—keeping code examples current and showing actual output. The unclear license treatment is a minor flag; verify it with the project if compliance is critical, but the raw text appears to be standard BSD.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python >=3.8 and a working Sphinx documentation setup with Jupyter kernel available at build time.
- Low friction installation with a pure-Python wheel.
- Active maintenance as of 2026-08-03 with 194 repository stars.
License · maintenance · safety
(unclear) — License treatment is unclear in the metadata. The raw text is a revised BSD license (permissive), but the SPDX field is null. Verify the exact license classification with the project before relying on it for compliance-sensitive work.
last release 2023-12-28 (960 days) · last repo commit 2026-08-03 · 194 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 110,724 downloads/mo, #12,447 on PyPI
Alternatives
Verify before relying
pip install jupyter_sphinx
# In conf.py (Sphinx configuration):
extensions = ['jupyter_sphinx']
# In .rst file:
.. jupyter-execute::
print('Hello from Jupyter Sphinx')- Whether the 'unclear' license treatment reflects a genuine ambiguity or a metadata gap that the project has since clarified.
- Support status for Python versions beyond 3.8 (current support statement is 'supports_current', but exact upper bound is unknown).
- Specific syntax and directive names for embedding executable code blocks in documentation.
What it is and what it does
Jupyter Sphinx Extensions is a Sphinx plugin that executes Python code blocks embedded in your documentation at build time and captures their output—text, plots, tables, and interactive Jupyter widgets—inserting it into the final HTML or other output formats. It bridges the gap between static documentation and live, runnable examples by letting you write code directly in your .rst files and have it execute during the doc build, keeping examples in sync with your actual code.
The package depends on the full Jupyter ecosystem (ipykernel, ipython, ipywidgets, nbconvert, nbformat) plus Sphinx itself, so it's designed for projects that already use Jupyter and want to embed executable examples in their Sphinx docs. It's maintained by the Jupyter project and remains actively developed.
Use it for
- Embed live Python examples in API documentation that execute and display output at doc build time.
- Create tutorial documentation with executable code blocks and rendered plots or tables.
- Include interactive Jupyter widgets in your Sphinx docs for exploratory examples.
- Ensure code examples in documentation stay synchronized with actual behavior by running them during builds.
- Build scientific or data-science project docs with embedded computational results and visualizations.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you maintain Sphinx documentation for a Jupyter-based project and want executable examples in your docs.
The package is actively maintained, has low install friction, and solves a real problem—keeping code examples current and showing actual output. The unclear license treatment is a minor flag; verify it with the project if compliance is critical, but the raw text appears to be standard BSD.
Install
jupyter-sphinx on PyPI
Before you install
Low friction installation with a pure-Python wheel. Active maintenance as of 2026-08-03 with 194 repository stars. Depends on six common Jupyter ecosystem packages (ipykernel, ipython, ipywidgets, nbconvert, nbformat, sphinx), all widely used and well-maintained.
Requires Python >=3.8 and a working Sphinx documentation setup with Jupyter kernel available at build time.
License in practice
License treatment is unclear in the metadata. The raw text is a revised BSD license (permissive), but the SPDX field is null. Verify the exact license classification with the project before relying on it for compliance-sensitive work.
Quickstart
pip install jupyter_sphinx
# In conf.py (Sphinx configuration):
extensions = ['jupyter_sphinx']
# In .rst file:
.. jupyter-execute::
print('Hello from Jupyter Sphinx')Verify before relying
- Whether the 'unclear' license treatment reflects a genuine ambiguity or a metadata gap that the project has since clarified.
- Support status for Python versions beyond 3.8 (current support statement is 'supports_current', but exact upper bound is unknown).
- Specific syntax and directive names for embedding executable code blocks in documentation.
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesipykernelipythonipywidgetsnbconvertnbformatsphinx |
| Maintenance | Actively maintained 960 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 110,724 / month, #12,447 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: jupyter_sphinx-0.5.3-py3-none-any.whl
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