⚡️ Turn Jupyter Notebooks into Blog Posts
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⚡️ Turn Jupyter Notebooks into Blog Posts

Jul 15, 2024·
Martin Roa Villescas
Martin Roa Villescas
· 3 min read
Image credit: HugoBlox

As a researcher or data scientist, your work often lives in Jupyter Notebooks. But sharing those insights effectively usually means taking screenshots, messy copy-pasting, or exporting to PDF.

Hugo Blox changes that. With the {{< notebook >}} shortcode, you can render your actual .ipynb files directly as beautiful, interactive blog posts or project pages. Keep your code, outputs, and narrative in one place.

Table of Contents

Why publish notebooks?

Tip

Reproducible Research: By publishing the actual notebook, you allow others to download and run your code, verifying your results and building upon your work.

  • No more screenshots – Render crisp code and vector plots directly from your source.
  • Theme consistent – Notebooks automatically adapt to your site’s theme (including dark mode).
  • Flexible sourcing – Display notebooks from your assets/ folder, page bundles, or even directly from a remote GitHub URL.
  • Interactive – Users can copy code blocks or download the full notebook to run locally.

Example: Data Science Workflow

Below is a live example of a notebook rendered right here in this post. Notice how the markdown, code, and outputs (text, HTML, and JSON) are all preserved and styled.

Launch Readiness Analysis

Python · Kernel: Python 3 · nbformat 4.5 · 6 cells

Download notebook
Markdown

Ship Notebook Stories in Minutes

Hugo Blox Notebook renderer turns your .ipynb experiments into beautiful long-form posts. Use this sample to see how markdown, code, and outputs flow together.

Markdown
  1. Drop notebooks inside assets/notebooks/ (or import them as page resources).
  2. Reference them with {{</* notebook src="your.ipynb" */>}}.
  3. Control code, outputs, metadata badges, and download links via shortcode params.
In [1]
demo quickstart
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import math
accuracy = 0.982
print("Collecting data...")
print("Training notebook-ready block...")
print("Done!")
accuracy
Collecting data...
Training notebook-ready block...
Done!
0.982
In [2]
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from IPython.display import HTML
HTML("<div style='font-family:Inter,ui-sans-serif;'><strong>Launch Readiness:</strong> <span style='color:#22c55e;'>98.2% confidence</span><br><em>Notebook blocks are theme-aware and dark-mode friendly.</em></div>")
Launch Readiness: 98.2% confidence
Notebook blocks are theme-aware and dark-mode friendly.
In [3]
metrics
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metrics = {
    'metrics': {
        'engagement_rate': 0.73,
        'read_time_minutes': 4.6,
        'subscribers': 1280
    }
}
metrics
{
  "metrics": {
    "engagement_rate": 0.73,
    "read_time_minutes": 4.6,
    "subscribers": 1280
  }
}
Markdown

Tip: Pair this block with Call-to-Action cards or the Embed shortcode to link to GitHub repos, datasets, or ARXIV preprints.

Powered by Hugo Blox Builder - https://github.com/HugoBlox/hugo-blox-builder

How to add a notebook

  1. Save your notebook. Place your .ipynb file in assets/notebooks/ (for global access) or inside a page bundle (like content/blog/my-post/analysis.ipynb).
  2. Add the shortcode. In any Markdown page, simply use: {{< notebook src="analysis.ipynb" >}}
  3. Customize. You can hide code cells for non-technical audiences (show_code=false) or just show the output (show_outputs=true).
Important

Hugo Blox respects your privacy. Notebook rendering happens statically at build time—no third-party services required.

Next steps

  • Try it out: Drop one of your existing notebooks into this site and see how it looks.
  • Link your papers: Use the Embed shortcode to link your notebook to your latest arXiv preprint or GitHub repository.
  • Get help: Join the community on Discord or check the documentation.

Happy researching! 🚀

Martin Roa Villescas
Authors
Teacher & Researcher
Martin Roa Villescas holds a BSc in Electronic Engineering from the National University of Colombia and an MSc in Embedded Systems from Eindhoven University of Technology (TU/e). He worked at Philips Research as an embedded software designer from 2013 to 2018. He later returned to TU/e for his doctoral research in model-based machine learning, carried out within the PhD-Teaching Assistant trajectory combining research and teaching. Since 2023, he has been working at Fontys University of Applied Sciences in the Netherlands, where he teaches in the Information and Communication Technology program and conducts research in robotics and smart industry.