https://github.com/daizutabi/mkdocs-nbsync
Seamlessly sync Jupyter notebook visualizations with MkDocs docs - no more broken screenshots!
https://github.com/daizutabi/mkdocs-nbsync
data-science documentation jupyter markdown mkdocs-plugin python visualization
Last synced: 4 months ago
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Seamlessly sync Jupyter notebook visualizations with MkDocs docs - no more broken screenshots!
- Host: GitHub
- URL: https://github.com/daizutabi/mkdocs-nbsync
- Owner: daizutabi
- License: mit
- Created: 2025-04-23T07:36:13.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2026-01-16T22:58:07.000Z (5 months ago)
- Last Synced: 2026-01-17T11:27:54.030Z (5 months ago)
- Topics: data-science, documentation, jupyter, markdown, mkdocs-plugin, python, visualization
- Language: Python
- Homepage: https://daizutabi.github.io/mkdocs-nbsync/
- Size: 842 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# mkdocs-nbsync
[![PyPI Version][pypi-v-image]][pypi-v-link]
[![Python Version][python-v-image]][python-v-link]
[![Build Status][GHAction-image]][GHAction-link]
[![Coverage Status][codecov-image]][codecov-link]
Connect Jupyter notebooks to your MkDocs documentation
mkdocs-nbsync is a MkDocs plugin that seamlessly embeds Jupyter notebook
visualizations in your documentation, solving the disconnect between
code development and documentation.
## Why Use mkdocs-nbsync?
### The Documentation Challenge
Data scientists, researchers, and technical writers face a common dilemma:
- **Development happens in notebooks** - ideal for experimentation and visualization
- **Documentation lives in markdown** - perfect for narrative and explanation
- **Connecting the two is painful** - screenshots break, exports get outdated
### Our Solution
This plugin creates a live bridge between your notebooks and documentation by:
- **Keeping environments separate** - work in the tool best suited for each task
- **Maintaining connections** - reference specific figures from notebooks
- **Automating updates** - changes to notebooks reflect in documentation
## Key Benefits
- **True Separation of Concerns**:
Develop visualizations in Jupyter notebooks and write documentation
in markdown files, with each tool optimized for its purpose.
- **Intuitive Markdown Syntax**:
Use standard image syntax with a simple extension to reference
notebook figures: `{#figure-id}`
- **Automatic Updates**:
When you modify your notebooks, your documentation updates
automatically in MkDocs serve mode.
- **Clean Source Documents**:
Your markdown remains readable and focused on content, without
code distractions or complex embedding techniques.
- **Enhanced Development Experience**:
Take advantage of IDE features like code completion and syntax
highlighting in the appropriate environment.
## Quick Start
### 1. Installation
```bash
pip install mkdocs-nbsync
```
### 2. Configuration
Add to your `mkdocs.yml`:
```yaml
plugins:
- mkdocs-nbsync:
src_dir: ../notebooks
```
### 3. Mark Figures in Your Notebook
In your Jupyter notebook, identify figures with a comment:
```python
# #my-figure
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(8, 4))
ax.plot([1, 2, 3, 4], [10, 20, 25, 30])
```
### 4. Reference in Markdown
Use standard Markdown image syntax with the figure identifier:
```markdown
{#my-figure}
```
## The Power of Separation
Creating documentation and developing visualizations involve different
workflows and timeframes. When building visualizations in Jupyter notebooks,
you need rapid cycles of execution, verification, and modification.
This plugin is designed specifically to address these separation of
concerns, allowing you to:
- **Focus on code** in notebooks without documentation distractions
- **Focus on narrative** in markdown without code interruptions
- **Maintain powerful connections** between both environments
Each environment is optimized for its purpose, while the plugin
handles the integration automatically.
## Contributing
Contributions are welcome! Please open an issue or submit a pull request.
## License
This project is licensed under the MIT License.
[pypi-v-image]: https://img.shields.io/pypi/v/mkdocs-nbsync.svg
[pypi-v-link]: https://pypi.org/project/mkdocs-nbsync/
[python-v-image]: https://img.shields.io/pypi/pyversions/mkdocs-nbsync.svg
[python-v-link]: https://pypi.org/project/mkdocs-nbsync
[GHAction-image]: https://github.com/daizutabi/mkdocs-nbsync/actions/workflows/ci.yaml/badge.svg?branch=main&event=push
[GHAction-link]: https://github.com/daizutabi/mkdocs-nbsync/actions?query=event%3Apush+branch%3Amain
[codecov-image]: https://codecov.io/github/daizutabi/mkdocs-nbsync/coverage.svg?branch=main
[codecov-link]: https://codecov.io/github/daizutabi/mkdocs-nbsync?branch=main